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DTSTART;TZID=America/Los_Angeles:20260202T104000
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SUMMARY:ECE Seminar: Advanced Packaging as the Engine of the AI Systems Era
DESCRIPTION:Presenter: Tolga Acikalin\, System and Package Architect\, Lumilens \nDescription: The rapid rise of artificial intelligence and machine learning—most notably recent breakthroughs in large language models—is reshaping the trajectory of the semiconductor industry and ushering in a new era of system innovation. As performance scaling at the device level slows\, heterogeneous integration (HI) has emerged as a foundational technology to sustain advances in computing and communication. By integrating separately manufactured components with diverse functions into a single system\, HI enables new levels of functionality\, performance\, and efficiency that are no longer achievable through traditional scaling alone. \nRealizing the full potential of heterogeneous systems demands a shift toward holistic system-level co-design\, with advanced packaging assuming a central and strategic role. This talk will briefly review the evolution of packaging technologies and then focus on advanced packaging architectures that enable heterogeneous integration.Topics will include advances in 2D and 3D interconnect technologies\, the introduction of novel packaging materials such as glass substrates\, and the growing role of photonic links\, including co-packaged optics enabled by silicon photonics. The talk will conclude with a discussion of power delivery and thermal management as system-level challenges and opportunities that will shape the next generation of high-performance\, energy-efficient systems. \nBio: Tolga Acikalin received his Bachelor of Science degree in Mechanical Engineering from Middle East Technical University in Ankara\, Turkey\, and his Master of Science and Ph.D. degrees from Purdue University in West Lafayette\, Indiana. \nHe joined Intel in 2007 as a Research and Development Engineer\, working on assembly and test pathfinding projects within the Technology and Manufacturing Group in Chandler\, Arizona. From 2013 to 2025\, he was a Principal Engineer at Intel Labs in Santa Clara\, California\, where he led and influenced innovative strategies for heterogeneous system integration\, spanning package- to wafer-scale solutions\, with a strong emphasis on next-generation interconnect technologies. Tolga is currently a System and Package Architect at Lumilens\, where he focuses on next-generation photonic interconnect solutions\, ranging from near-packaged optics to co-packaged optics. \nHis technical interests include co-packaged optics and silicon photonics\, optical and sub-THz to THz RF high-speed interconnects and the associated advanced package architectures\, novel advanced packaging solutions such as glass substrates\, and optical computing. Tolga has authored or co-authored more than 15 peer-reviewed journal and conference publications in leading APS\, ASME\, and IEEE venues\, including best paper awards at IEEE RFIC and JSCC. He holds nine issued patents and more than 27 additional patent filings. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-seminar-advanced-packaging-as-the-engine-of-the-ai-systems-era/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260202T120000
DTEND;TZID=America/Los_Angeles:20260202T130000
DTSTAMP:20260417T152555
CREATED:20260122T191932Z
LAST-MODIFIED:20260128T171007Z
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SUMMARY:Statistics Seminar: Mathematical Foundations for Machine Learning from a Nonlinear Time Series Perspective
DESCRIPTION:Presenter: Jiaqi Li\, William H. Kruskal Instructor\, University of Chicago \nDescription:Modern machine learning (ML) algorithms achieve remarkable empirical success\, yet providing rigorous statistical guarantees remains a major challenge\, particularly in distributional theory and online inference methods. In this talk\, we will introduce a novel framework to provide mathematical foundations for ML by bringing powerful tools in nonlinear time series. First\, we focus on the stochastic gradient descent (SGD) with constant learning rates. By interpreting the SGD sequence as a nonlinear AR(1) process\, we can establish the geometric moment contraction (GMC) for SGD regardless of initializations. By this GMC property\, we can derive refined asymptotic theory of SGD and its averaging variant\, including general moment convergence\, quenched central limit theorems\, quenched invariance principles\, and sharp Berry- Esseen bounds. Then\, we extend this theoretical framework to SGD with dropout regularization\, a widely used but theoretically underexplored technique in deep learning. By establishing GMC under explicit learning-rate and dimensional scaling regimes\, we obtain asymptotic normality and invariance principles for dropout SGD and its averaged version. These results enable online inference\, for which we introduce a fully recursive estimator of the long-run covariance matrix appearing in the limiting distributions. The proposed online confidence intervals with asymptotically correct coverage can be generalized to many other ML algorithms. Overall\, viewing online learning algorithms as nonlinear time series provides a powerful toolkit for deriving statistical guarantees in modern ML\, with implications for high-dimensional stochastic optimization and real-time uncertainty quantification. \nBio:Jiaqi Li is a William H. Kruskal Instructor in the Department of Statistics at the University of Chicago. She obtained her PhD in Statistics from Washington University in St. Louis in 2024. Her research focuses on developing theoretical guarantees and statistical inference methods for machine learning algorithms. She also works on time series data\, especially in the high- dimensional settings with complex temporal and cross-sectional dependency structures. She also\ncollaborates with neuroscientists on applications in fMRI and EEG data. \nHosted by: Statistics Department \nZoom link: https://ucsc.zoom.us/j/96647674332?pwd=rCHfeGpKslaGS5iIPP5Jh29mQiMJID.1
URL:https://events.ucsc.edu/event/statistics-seminar-mathematical-foundations-for-machine-learning-from-a-nonlinear-time-series-perspective/
LOCATION:https://ucsc.zoom.us/j/96647674332?pwd=rCHfeGpKslaGS5iIPP5Jh29mQiMJID.1
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260202T160000
DTEND;TZID=America/Los_Angeles:20260202T170000
DTSTAMP:20260417T152555
CREATED:20260128T184233Z
LAST-MODIFIED:20260128T184233Z
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SUMMARY:AM Seminar: Are Graph Learning Methods Actually Learning?
DESCRIPTION:Presenter: Seshadhri Comandur\, Professor of Computer Science\, UCSC \nDescription: There has been a lot of literature on graph machine learning over the past few years\, and a bewildering array of new methods. This talk is based on a series of results making a provocative argument. Maybe many graph machine learning methods are not really that effective\, and the progress we are seeing is an artifact of experimental design and measurement. I will talk about some results showing that low-dimensional embeddings with dot product similarity (arguably the most common graph ML technique) cannot capture salient aspects of real-world graphs. Follow-up work demonstrates that simple benchmarks seem to outperform fancier methods\, and that there are significant shortcomings in existing accuracy measurement. \nBio: C. Seshadhri (Sesh) is a professor of Computer Science at the University of California\, Santa Cruz and an Amazon scholar. Prior to joining UCSC\, he was a researcher at Sandia National Labs\, Livermore in the Information Security Sciences department\, during 2010-2014. His primary interest is the theoretical study of algorithms\, especially those with a mix of graphs and randomization. By and large\, Sesh works at the boundary of theoretical computer science (TCS) and data mining. His work spans many areas: sublinear algorithms\, graph algorithms\, graph modeling\, scalable computation\, and data mining. In the theory world\, his work has resolved numerous open problems in monotonicity testing and graph property testing. A number of his papers in the interface of TCS and applied algorithms have received paper awards at KDD\, WWW\, ICDM\, SDM\, and WSDM. He received the 2019 SDM/IBM Early Career Award for Excellence in Data Analytics. Sesh got his Ph.D from Princeton University and spent two years as a postdoc in IBM Almaden Labs. \nHosted by: Ashesh Chattopadhyay\, Applied Mathematics Department
URL:https://events.ucsc.edu/event/am-seminar-are-graph-learning-methods-actually-learning/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260204T120000
DTEND;TZID=America/Los_Angeles:20260204T130000
DTSTAMP:20260417T152555
CREATED:20260128T170858Z
LAST-MODIFIED:20260128T170858Z
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SUMMARY:Statistics Seminar: Statistical Inference for Multi-Modality Data in the AI Era
DESCRIPTION:Presenter: Qi Xu\, Postdoctoral Researcher\, Department of Statistics & Data Science\, Carnegie Mellon University \nDescription: Multi-modality data are increasingly common across science medicine and technology\, such as imaging\, text\, sensors\, and genomics. These modalities are often high dimensional or unstructured and naturally exhibit blockwise (nonmonotone) missingness where different samples observe different subsets of modalities. Such missingness creates a major obstacle for statistical analyses since classical methods either discard large portions of data or rely on strong modeling assumptions. Recent advances in AI make it possible to generate or predict unobserved modalities from observed ones\, opening new opportunities for data integration. In this talk\, I will focus on statistical inference for blockwise-missing multi-modality data\, while rigorously incorporating modern AI tools. Rooted in semiparametric theory\, there is a long-term open problem that theoretically optimal estimating function under non-monotone missingness is computationally intractable\, even under the missing completely at random mechanism. I introduce a tractable approximation to the optimal estimating equation through a novel Restricted ANOVA hierarchY or RAY decomposition and its almost-eigen-operator property. This leads to a new class of estimators that leverage predictive or generative AI models to borrow information across datasets while remaining unbiased and asymptotically normal. Motivated by the property of the RAY estimator\, we extend the RAY estimator to a class of unbiased\, consistent\, and computationally tractable estimators. The most efficient estimator in this class is then derived\, named as Adaptive RAY estimator\, which optimally integrating all available data and prediction from AI. Simulation studies and a single cell multi-omics application demonstrate that the proposed framework enables stable and efficient inference for complex multi modality data in the AI era. This is a joint work with Lorenzo Testa\, Jing Lei and Kathryn Roeder\, and the paper is available on arXiv: https://arxiv.org/abs/2509.24158 \nBio: Qi Xu is a postdoctoral researcher in the Department of Statistics & Data Science at Carnegie Mellon University. His research interests lie broadly in statistics and machine learning\, especially in data integration and AI for statistics\, with their applications in genomics and mobile health. He received his Ph.D. from the Department of Statistics at University of California\, Irvine\, and the Master degree from University of Illinois Urbana Champaign\, and the Bachelor degree (with honors) from Tongji University. \nHosted by: Statistics Department \nZoom link: https://ucsc.zoom.us/j/91740050783?pwd=joK9hfwvM7FZ48acaiow8OY4ZlBDXA.1
URL:https://events.ucsc.edu/event/statistics-seminar-statistical-inference-for-multi-modality-data-in-the-ai-era/
LOCATION:https://ucsc.zoom.us/j/91740050783?pwd=joK9hfwvM7FZ48acaiow8OY4ZlBDXA.1
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260206T121500
DTEND;TZID=America/Los_Angeles:20260206T130000
DTSTAMP:20260417T152555
CREATED:20260112T191838Z
LAST-MODIFIED:20260112T191838Z
UID:10008344-1770380100-1770382800@events.ucsc.edu
SUMMARY:GDAC Portfolio Workshop
DESCRIPTION:Workshop\n\nPart of the GDA Conference on campus – come and learn best practices for creating a portfolio to use in the gaming industry! \n  \nKNOW OUR POLICIES \nJob postings and employer announcements are made without endorsement\, direct or implied\, by Career Success or UCSC. Career Success educates students about various opportunities and ensures equity of access to campus recruiting activities for all employers who abide by our Employer Policies. Individual students are encouraged to determine which employers align with their diverse talents\, values\, and interests. \n  \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications. \nOnline Safety Tips \nUC Santa Cruz Career Success〡Hahn 125 \nEmail Career Success: csuccess@ucsc.edu \nVisit Career Success Website: https://careers.ucsc.edu
URL:https://events.ucsc.edu/event/gdac-portfolio-workshop/
LOCATION:Cultural Center – Merrill College\, 641 Merrill Rd\, Santa Cruz\, 95064\, United States
CATEGORIES:Lectures & Presentations,Meetings & Conferences,Seminars,Workshop
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Cultural Center – Merrill College 641 Merrill Rd Santa Cruz 95064 United States;X-APPLE-RADIUS=500;X-TITLE=641 Merrill Rd:geo:-122.0534175,37.0003908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260209T104000
DTEND;TZID=America/Los_Angeles:20260209T234500
DTSTAMP:20260417T152555
CREATED:20260202T233432Z
LAST-MODIFIED:20260202T233432Z
UID:10009148-1770633600-1770680700@events.ucsc.edu
SUMMARY:ECE Seminar: Integrated Micro- and Nanosystems for Biosensing\, Neural Therapy\, and Nanotoxicity
DESCRIPTION:Presenter: Dr. Ke Du\, Associate Professor of Chemical and Environmental Engineering\, University of California\, Riverside \nDescription: Miniaturized micro- and nanofluidic systems\, integrated with biochemistry\, microscopy\, nanomaterials\, and computer vision algorithms\, provide powerful platforms for diverse biomedical applications\, including molecular diagnostics\, biophysics\, and optogenetics. In this presentation\, we introduce a pneumatically controlled nano-sieve device with nanolithography-defined microstructures designed to enhance target capture efficiency in bodily fluids. This system incorporates sheath flow configurations\, surface-enhanced Raman probes\, and CRISPR reactions for the sensitive and multiplexed detection of drug-resistant bacteria in nanoconfined environments. We also highlight our recent advancements in implantable devices for adeno-associated virus (AAV) delivery and the treatment of neurological disorders in mouse models. These devices\, fabricated via high-resolution 3D printing\, utilize total internal reflection at the liquid–air–microstructure interface to efficiently stimulate neurons. Finally\, we integrate experimental approaches with molecular dynamics simulations to study the interactions between arbitrary nanoparticles and living cells—advancing our understanding of nanotoxicity and guiding the design of next-generation drug delivery systems. \nBio: Dr. Ke Du is an Associate Professor of Chemical and Environmental Engineering at the University of California\, Riverside. He established his independent research lab in 2018 following postdoctoral training with Richard Mathies at the University of California\, Berkeley\, and Holger Schmidt at the University of California\, Santa Cruz. His research team focuses on molecular diagnostics for infectious diseases such as sepsis\, in vivo bioimaging\, and nanotoxicology. Dr. Du has received numerous honors\, including the EIPBN Inaugural Early Career Award (2024) and the NIH Maximizing Investigators’ Research Award (2021). He was recognized as an Emerging Investigator by Lab on a Chip (2024) and Nanoscale (2025)\, and named a Global Rising Star in Sensing by ACS Sensors. His research is supported by federal agencies and industry partners\, including NIH NIGMS\, NIH NIAID\, NSF CBET\, NSF CMMI\, USDA\, DOE\, the Burroughs Wellcome Fund\, Mammoth Biosciences\, and Biological Mimetics. Beyond his research activities\, Dr. Du serves as an Early Career Editorial Advisory Board member for Biomicrofluidics (AIP Publishing) and Sensors and Actuators Reports (Elsevier). \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-seminar-integrated-micro-and-nanosystems-for-biosensing-neural-therapy-and-nanotoxicity/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260209T123000
DTEND;TZID=America/Los_Angeles:20260209T133000
DTSTAMP:20260417T152555
CREATED:20260126T235923Z
LAST-MODIFIED:20260204T204343Z
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SUMMARY:CM Seminar - “The ‘Social’ Side of Social Virtual Reality”
DESCRIPTION:Presented by: Bree McEwan \nDescription: One of the potential use cases of virtual reality is to create spaces where humans can interact with each other or virtual agents across distances. However\, despite many of the technological challenges of social VR being solved\, social VR does not see poised for widespread adoption. Multi-user social VR needs to be perceived not just as a technology to be solved but an emerging communication channel. Social science approaches\, particularly from communication scholars\, are needed to truly understand the way that humans engage with VR and each other in these new environments. McEwan’s talk will outline a program of research using qualitative and quantitative approaches to understand communication processes\, effects\, and user perceptions of VR design to deepen our understanding of how people engage with environments and each other in social VR. \nBio: Bree McEwan is a Professor in the Institute of Communication\, Culture\, Information and Technology\, an associate director of the Data Sciences Institute\, and a faculty affiliate of the Schwartz Reisman Institute for Technology and Society at the University of Toronto. She is a co- organizer and founder of the Questioning Reality conference\, a social VR research incubator. McEwan authored Navigating New Media Networks and co-authored Interpersonal Encounters. She directs the McEwan Mediated Communication Lab which researches the intersection of technology and social interaction. McEwan has published on relational maintenance on social network sites\, perceived social affordances of communication channels\, linguistic patterns in online communities\, and the diffusion of information through social media. In addition\, McEwan has metascience interests focused on transparency and replication in the social sciences. Current studies of the McMC Lab focus on affordances of social virtual environments\, cognition and heuristics related to learning in VR spaces\, and nonverbal communication patterns of avatars and agents. \nHosted by: Professor Katherine Isbister \nWhen: Monday\, February 9\, 2026 from 12:30PM to 1:30PM \nLocation:  \nIN-PERSON @ UCSC Main Campus\, E2-280. \nViewing room @ SVC 3212.   \nLUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend. \nZoom info: \nhttps://ucsc.zoom.us/j/91469785121?pwd=F0jplMgh4eTjy6qNZI0lEhlljs0XhG.1 \nMeeting ID: 914 6978 5121\nPasscode: 183098
URL:https://events.ucsc.edu/event/cm-seminar-the-social-side-of-social-virtual-reality/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260209T160000
DTEND;TZID=America/Los_Angeles:20260209T170000
DTSTAMP:20260417T152555
CREATED:20260114T182449Z
LAST-MODIFIED:20260114T182750Z
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SUMMARY:AM Seminar: Data Driven Modeling for Scientific Discovery and Digital Twins
DESCRIPTION:Presenter: Dongbin Xiu\, Professor\, Ohio State University \nDescription:We present a data-driven modeling framework for scientific discovery\, termed Flow Map Learning (FML). This framework enables the construction of accurate predictive models for complex systems that are not amenable to traditional modeling approaches. By leveraging data and the expressiveness of deep neural networks (DNNs)\, FML facilitates long-term system modeling and prediction even when governing equations are unavailable. FML is particularly powerful in the context of Digital Twins\, an emerging concept in digital transformation. With sufficient offline learning\, FML enables the construction of simulation models for key quantities of interest (QoIs) in complex Digital Twins\, when direct mathematical modeling of the QoIs is infeasible. During the online execution of a Digital Twin\, the learned FML model can simulate the QoIs without reverting to the computationally intensive Digital Twin simulation model. As a result\, FML serves as an enabling methodology for real-time control and optimization for complex systems. \nBio: Dongbin Xiu received his Ph.D degree from the Division of Applied Mathematics of Brown University in 2004. He joined the Department of Mathematics of Purdue University in 2005 and moved to the University of Utah in 2013. In 2016\, He joined The Ohio State University as Professor of Mathematics and Ohio Eminent Scholar. He received NSF CAREER award in 2007 and was elected to SIAM Fellow in 2023. He is currently the Editor-in-Chief of the Journal of Computational Physics and the founding Editor-in-Chief of Journal of Machine Learning for Modeling and Computing (JMLMC). His current research focuses on developing efficient numerical methods for scientific machine learning\, data driven discovery and digital twins. \nHosted by: Daniele Venturi\, Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-data-driven-modeling-for-scientific-discovery-and-digital-twins/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260211T150000
DTEND;TZID=America/Los_Angeles:20260211T160000
DTSTAMP:20260417T152555
CREATED:20260120T172348Z
LAST-MODIFIED:20260120T172457Z
UID:10008675-1770822000-1770825600@events.ucsc.edu
SUMMARY:EOP Students - "Words That Impress: Creating a Great Résumé & Cover Letter"
DESCRIPTION:Crafting a fantastic Resume and Cover Letter are the key to getting an interview and landing a job!  Join us for this informative workshop that will cover best practices for resume and cover letter development.  You’ll gain understanding about the perfect format\, navigating AI filters\, and how to write captivating resume bullet points and engaging cover letter paragraphs.  The presentation will be 30 minutes\, followed by 30 minutes of optional worktime here in our office with coaches to give you brief input. \nWe will provide captions for the presentation. If you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/eop-students-words-that-impress-creating-a-great-resume-cover-letter/
LOCATION:Career Success Student Lounge (125 Hahn)\, 1156 High Street\, Santa Cruz\, CA\, 95064\, United States
CATEGORIES:Meetings & Conferences,Seminars,Training,Workshop
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260212T100000
DTEND;TZID=America/Los_Angeles:20260212T140000
DTSTAMP:20260417T152555
CREATED:20260202T180539Z
LAST-MODIFIED:20260202T180539Z
UID:10009142-1770890400-1770904800@events.ucsc.edu
SUMMARY:Virtual Resume Review
DESCRIPTION:Meet with actual recruiters for this virtual resume review! You’ll get a chance to show them your resume and get feedback from professionals. \nGet career ready with Career Success! \nYou Belong Here: The programs and services described here are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. \nTo learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications. \nHandshake is committed to building an accessible product\, as well as an ongoing\, sustainable process for maintaining accessibility. Please contact slugtalent@ucsc.edu if you need accessibility support at least 5 days prior to the event date. \nQuestions? Email slugtalent@ucsc.edu
URL:https://events.ucsc.edu/event/virtual-resume-review/
LOCATION:
CATEGORIES:Drop-In Support,Lectures & Presentations,Seminars,Training,Workshop
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260212T114000
DTEND;TZID=America/Los_Angeles:20260212T133000
DTSTAMP:20260417T152555
CREATED:20260211T234225Z
LAST-MODIFIED:20260211T234252Z
UID:10009212-1770896400-1770903000@events.ucsc.edu
SUMMARY:BME Seminar: Population Genetics in an Era of Genomic Health
DESCRIPTION:Presenter: Dr. Eimear Kenny\, Founding Director of the Institute for Genomic Health and a Endowed Chair and Professor for Genomic Health at the Icahn School of Medicine at Mount Sinai \nDescription: The overarching goal of my work is to advance genomics in medicine and research through diversity and innovation. The work of my group seeks to enrich our understanding of human genomic diversity by focusing on populations underrepresented in genomics\, developing and disseminating computational genomic tools to enhance precision and accuracy in diverse populations\, unveiling genetic architectures of diseases that can track with demographic history\, and advancing diversity large-scale genomic databases. We also work to integrate new paradigms of genomic medicine into routine clinical practice\, ensuring genomic insights are appropriately applied in real-world healthcare settings and lead to improved patient care and health equity. I will discuss aspects of this work with emphasis on why we should promote inclusivity\, innovate methodologies\, and harness the potential of diverse populations in genomic health.  \nBio: Eimear Kenny\, PhD\, is the Founding Director of the Institute for Genomic Health\, building resources for integrating genomic information and AI in routine clinical care\, and supporting the sequencing and return of results to a diverse patients in the Mount Sinai Health System. She also the Founding Director of the Center for Translational Genomics and a Endowed Chair and Professor of Genomic Health\, at the Icahn School of Medicine at Mount Sinai\, working on computational and translational genomic research. She is Principal Investigator in many large NIH-funded international consortium focused on computational genomics and genomic medicine\, including eMERGE\, PRIMED\, CSER\, GSP\, TOPMed\, PAGE\, and HPRC. She is a strong advocate for the importance of diversity in genomic research\, is improving the accessibility of genetics to global populations\, and has led multiple genetics-based clinical trials. Her exceptional contributions to the field earned her the prestigious Early Career Award from the American Society of Human Genetics in 2022. In addition to her academic and research roles\, Dr. Kenny serves as a scientific advisor to various genomic medicine initiatives in government\, non-profit\, and industry sectors. \nHosted by: Professor Karen Miga\, BME Department
URL:https://events.ucsc.edu/event/8123/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260223T104000
DTEND;TZID=America/Los_Angeles:20260223T114500
DTSTAMP:20260417T152555
CREATED:20260219T235259Z
LAST-MODIFIED:20260219T235259Z
UID:10009257-1771843200-1771847100@events.ucsc.edu
SUMMARY:ECE 290 Seminar: High-Frequency Circuits for Next-Generation Communication: From Beyond-5G mm-Wave MIMO to Co-Packaged Optics
DESCRIPTION:Presenter: Susnata Mondal\, Research Scientist\, Intel \nDescription: \nRapid growth in wireless connectivity\, cloud computing\, and AI infrastructure is driving an urgent need for communication systems that can deliver higher data rates with improved energy efficiency. Meeting these demands requires advances in high-frequency circuit design across both wireless and wireline domains\, spanning millimeter-wave radios to optical interconnects. \nThis seminar will present recent developments in two complementary directions. The first focuses on millimeter-wave MIMO systems for beyond-5G communication. Conventional phased arrays are typically limited to single-stream beamforming\, while fully digital solutions\, although flexible\, incur significant power and area overhead. Emerging hybrid architectures enable multi-stream\, multi-band operation with improved spectral efficiency by combining RF and baseband beamforming\, supporting carrier aggregation\, adaptive spatial processing\, and full-duplex operation. Prototype systems have demonstrated scalable multi-antenna transceivers operating across 28/37 GHz bands\, integrating RF front-ends\, beamforming networks\, and system-level signal processing. \nThe second direction addresses high-performance computing interconnects\, where electrical links increasingly struggle with loss and energy efficiency at high data rates. Co-packaged optics offers a promising alternative by placing optical engines in close proximity to compute and switch chips\, improving link efficiency. The seminar will discuss circuit and system innovations enabling scalable optical I/O\, including equalization\, clocking\, and high-linearity design techniques for high-speed optical links\, along with recent prototype demonstrations achieving high data rates with low energy per bit. \nBio: Susnata Mondal received the B.Tech. and M.Tech. degrees in E&ECE from IIT Kharagpur in 2015 and the Ph.D. degree in ECE from Carnegie Mellon University\, Pittsburgh\, in 2020. Since then\, he has been a Research Scientist at Intel\, Hillsboro\, working on co-packaged optics and high-speed I/O. He has authored several lead-author papers in ISSCC and JSSC and holds 18 U.S. patents. He is a Technical Program Committee member of RFIC and an Associate Editor for TCAS-I\, TCAS-II\, and SSCL. His honors include the SSCS Predoctoral Achievement Award\, the Best Ph.D. Thesis Award from CMU ECE\, and selection as an SSCS Rising Star. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-high-frequency-circuits-for-next-generation-communication-from-beyond-5g-mm-wave-mimo-to-co-packaged-optics/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/01/BElogoWHITE.png
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260223T160000
DTEND;TZID=America/Los_Angeles:20260223T170000
DTSTAMP:20260417T152555
CREATED:20260114T175234Z
LAST-MODIFIED:20260219T193254Z
UID:10008383-1771862400-1771866000@events.ucsc.edu
SUMMARY:AM Seminar: Multiscale Modeling of Cellular Membranes and Oncogenic Proteins
DESCRIPTION:Presenter: Liam Stanton\, Professor\, San Jose State University \nDescription: In this talk\, I will present a multiscale model for cellular membranes\, which is trained on molecular dynamics simulations. The model is constructed within the formalism of dynamic density functional theory and can be extended to include features such as the presence of proteins and membrane deformations. This new framework has enabled simulations that can access length-scales on the order of microns and time-scales on the order of seconds\, all while maintaining near fidelity to the underlying molecular interactions. Such scales are significant for accessing biological processes associated with signaling pathways within cells and experimentally relevant regimes. As applications\, we consider the cellular interactions of two membrane proteins of biological interest: G protein-coupled receptors (GPCRs) and RAS-RAF complexes\, the latter being implicated in roughly 30% of human cancers. \nBio: Dr. Stanton received his PhD in Applied Mathematics from Northwestern University in 2009. He went on to do a postdoc at Lawrence Livermore National Laboratory (LLNL)\, where he later became a staff scientist at the Center for Applied Scientific Computing. In 2018\, he joined the faculty at San Jose State University in the Department of Mathematics and Statistics\, where he is now an associate professor and a recent recipient of the Dean’s Scholar Award in Research Excellence. Dr. Stanton’s current research interests are in the multiscale modeling of non-equilibrium\, many-body systems. In particular\, he focuses on areas such as fusion energy\, biophysical systems and statistical mechanics. \nHosted by: Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-multiscale-modeling-of-cellular-membranes-and-oncogenic-proteins/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/01/Liam-Stanton-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260223T160000
DTEND;TZID=America/Los_Angeles:20260223T170000
DTSTAMP:20260417T152555
CREATED:20260126T202042Z
LAST-MODIFIED:20260126T202042Z
UID:10009108-1771862400-1771866000@events.ucsc.edu
SUMMARY:Statistics Seminar: Rotated Mean-Field Variational Inference and Iterative Gaussianization
DESCRIPTION:Presenter: Sifan Liu\, Assistant Professor\, Department of Statistical Science\, Duke University \nDescription:Mean-field variational inference (MFVI) approximates a target distribution with a product distribution in the standard coordinate system\, offering a scalable approach to Bayesian inference but often severely underestimating uncertainty due to neglected dependence. We show that MFVI can be greatly improved when performed along carefully chosen principal component axes rather than the standard coordinates. The principal components are obtained from a cross-covariance matrix of the target’s score function and identify orthogonal directions that capture the dominant discrepancies between the target distribution and a Gaussian reference. Performing MFVI in a rotated system defines a rotation followed by a coordinatewise transformation that moves the target closer to Gaussian. Iterating this procedure yields a sequence of transformations that progressively Gaussianize the target. The resulting algorithm provides a computationally efficient construction of normalizing flows\, requiring only MFVI sub-problems and avoiding large-scale optimization. In posterior sampling tasks\, we demonstrate that the proposed method greatly outperforms standard MFVI while achieving accuracy comparable to normalizing flows at a much lower computational cost. \nBio: Sifan Liu is an Assistant Professor in the Department of Statistical Science at Duke University. She was previously a research scientist at the Flatiron Institute and received her Ph.D. in Statistics from Stanford University. Her research interests include sampling\, generative modeling\, and selective inference. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-rotated-mean-field-variational-inference-and-iterative-gaussianization/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/01/ph.d.-presentation-graphic-option-1-2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260224T120000
DTEND;TZID=America/Los_Angeles:20260224T130000
DTSTAMP:20260417T152555
CREATED:20260112T193435Z
LAST-MODIFIED:20260112T193435Z
UID:10008346-1771934400-1771938000@events.ucsc.edu
SUMMARY:Arts Division - Application and Interview Skills That Will Get You A Great Job!
DESCRIPTION:Having a stand-out application and exceptional interview skills are essential for landing a great job! Join us for this fast-paced and interactive one-hour online workshop where we’ll explore how to submit an application that makes an employer WANT to interview you\, as well as top-notch tips and techniques to prepare for and answer  interview questions with intentionality\, confidence\, and skill. \nWe will provide captions for the presentation. If you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/arts-division-application-and-interview-skills-that-will-get-you-a-great-job/
LOCATION:https://ucsc.zoom.us/j/2614256373?pwd=WVdISUN0Q3ZHTXhSak5VVWN5OVc3dz09
CATEGORIES:Meetings & Conferences,Seminars,Workshop
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/12/Career-Success-logo-circle-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260225T150000
DTEND;TZID=America/Los_Angeles:20260225T170000
DTSTAMP:20260417T152555
CREATED:20260211T203445Z
LAST-MODIFIED:20260218T010402Z
UID:10009206-1772031600-1772038800@events.ucsc.edu
SUMMARY:February 25\, 2026 | Works-in-Progress with Geoffrey Bowker
DESCRIPTION:Wednesday\, February 25\, 2026 \n3:00 – 5:00 PM \nHumanities 1\, Room 210 or Zoom (Registration) \nJoin SJRC scholars in Humanities 1\, room 210 or on Zoom for an open discussion of works-in-progress! This is a wonderful chance to engage with one another’s ideas\, and support our own internal work. \nAt this session\, we will hear from Geoffrey Bowker\, Emeritus Professor in Irvine and Science & Justice Advisor about works-in-progress and ongoing work on the death of infrastructure\, AI\, and underwater network cables and his collaborative comic book on Actor Network Theory. SJRC members Warren Sack and Dimitris Papadopolous will act as “warm up” discussants. \nContact Colleen Stone (colleen@ucsc.edu) or Maria Puig de la Bellacasa (puig@ucsc.edu) for the readings\, including a new comic book on the graveyard of machines! \nRegister for Zoom here. \nGeoffrey C. Bowker is Emeritus Professor at the School of Information and Computer Science\, University of California at Irvine\, where he directed a laboratory for Values in the Design of Information Systems and Technology. He was also Professor of and Senior Scholar in Cyberscholarship at the University of Pittsburgh School\, and Executive Director\, Center for Science\, Technology and Society\, Santa Clara. He was awarded the prestigious 4S Bernal Prize in 2024 for his distinguished\, career-long contributions to the field of Science and Technology Studies (STS). His book Memory Practices in the Sciences (MIT Press 2008) won the 2007 Ludwig Fleck Prize of the Society for Social Studies of Science\,  and was awarded “Best Information Science Book” by the American Society for Information Science and Technology (ASIS&T). \nCo-sponsored by earthecologies x technoscience conversations\, History of Consciousness
URL:https://events.ucsc.edu/event/february-25-2026-works-in-progress-with-geoffrey-bowker/
LOCATION:CA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260225T173000
DTEND;TZID=America/Los_Angeles:20260225T190000
DTSTAMP:20260417T152555
CREATED:20260130T054047Z
LAST-MODIFIED:20260209T232119Z
UID:10009139-1772040600-1772046000@events.ucsc.edu
SUMMARY:Exploring Research Pathways at Baskin Engineering
DESCRIPTION:Curious how being part of a research lab can supercharge your experience as a Baskin Engineer?   \nJoin us for this informative event to learn about opportunities to solve open-ended problems\, build deeper technical skills\, and learn how to think like an engineer. \nWe’ll kick things off with a quick overview of the kinds of research opportunities available to undergrads and how to get started\, then you’ll hear directly from students who’ve worked in research labs as undergraduates. They’ll share what they actually did day-to-day\, the skills they built (technical and professional)\, and how research shaped their confidence\, career goals\, and next steps. We’ll then have pizza and networking to end the evening. \nWhether you’re aiming for industry\, graduate school\, or just want hands-on experience that goes beyond coursework\, this panel will help you understand how undergraduate research can set you apart—academically\, professionally\, and personally! \n\nRegister via Handshake. \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/exploring-research-pathways-at-baskin-engineering/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/01/BElogoWHITE.png
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260226T114000
DTEND;TZID=America/Los_Angeles:20260226T131500
DTSTAMP:20260417T152555
CREATED:20260212T231636Z
LAST-MODIFIED:20260212T231636Z
UID:10009217-1772106000-1772111700@events.ucsc.edu
SUMMARY:BME 280B Seminar: The evolution of structural variation across vertebrate genomes
DESCRIPTION:Presenter: Peter Sudmant\, Assistant Professor of Integrative Biology\, University of California\, Berkeley \nDescription: Structural variants (SVs) contribute substantially to genetic variation and play vital roles in adaptation and disease. However\, SVs are poorly captured by short read sequencing and thus are understudied\, particularly in non-model organisms. Here\, taking advantage of recently generated haplotype-resolved genome assemblies from >600 vertebrate species\, we present the most comprehensive survey of the diversity of SVs and single nucleotide variants (SNVs) across the vertebrate tree of life to date. \nBio: Peter Sudmant is an Assistant Professor of Integrative Biology at the University of California Berkeley. Prior to joining UC Berkeley\, Dr Sudmant completed his PhD at the University of Washington in the Lab of Dr Evan Eichler as HHMI International Fellow. Dr Sudmant went on to complete a postdoc with Christopher Burge at MIT as a Genentech fellow of the Life Sciences Research Foundation. Dr Sudmant is a recipient of the American Foundation for Aging Research Junior Faculty Award and a Hellman Fellow. \nHosted by: Professor Russ Corbett-Detig\, BME Department
URL:https://events.ucsc.edu/event/bme-280b-seminar-the-evolution-of-structural-variation-across-vertebrate-genomes/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/PeterHSudmant.jpg
GEO:36.9996638;-122.0618552
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Physical Sciences Building Physical Sciences Building Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Physical Sciences Building:geo:-122.0618552,36.9996638
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260227T160000
DTEND;TZID=America/Los_Angeles:20260227T170000
DTSTAMP:20260417T152555
CREATED:20260218T234050Z
LAST-MODIFIED:20260218T234050Z
UID:10009251-1772208000-1772211600@events.ucsc.edu
SUMMARY:"Career Success Resources" for UTC Transfer/Continuing Students
DESCRIPTION:Come and find out ALL that Career Success has to offer to UCSC students – every resources is FREE for you!  Resume/Cover Letter feedback\, Career Coaching Appointments\, Graduate School Preparation\, Interviewing Skills\, Networking Opportunities\, Career Fairs\, Professional Development Workshops and MORE! \nAll students are welcome. The presentation will last 30 minutes\, followed by a 15-minute Q&A. \nWe will provide captions for the presentation. If you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \n  \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/career-success-resources-for-utc-transfer-continuing-students/
LOCATION:CA
CATEGORIES:Exhibits,Seminars,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260302T104000
DTEND;TZID=America/Los_Angeles:20260302T114500
DTSTAMP:20260417T152555
CREATED:20260224T232851Z
LAST-MODIFIED:20260224T232851Z
UID:10009353-1772448000-1772451900@events.ucsc.edu
SUMMARY:ECE 290 Seminar: Precision Nuclear Medicine: Engineering Solutions from Acquisition to Analysis
DESCRIPTION:Presenter: Spencer L. Bowen\, Assistant Professor in the Departments of Radiology and Biomedical Engineering\, UT Southwestern Medical Center \nDescription: The Bowen Lab focuses on the development of tools for positron emission tomography (PET) and hybrid systems (e.g. PET/CT)\, to advance precision imaging for the care and study of oncology\, neurology\, and cardiology patients. Quantitative metrics from PET are integral to both patient workup and clinical research. However\, current approaches to enable quantitative imaging have substantial performance limitations that can compromise study conclusions\, fail to generalize across exams and scanners\, expose patients to additional ionizing radiation\, or necessitate invasive procedures. To address these key barriers\, Dr. Bowen and his team investigate advanced acquisition techniques\, image reconstruction algorithms\, and post-processing methods. Their studies span from digital simulations to human subjects research. This lecture will cover recent developments by the Bowen Lab\, including 1) advanced PET data correction methods for low-dose and standalone exams\, 2) non-invasive fully quantitative imaging\, and 3) leveraging topical sensors to detect faulty radiotracer injections. \nBio: Spencer L. Bowen\, Ph.D.\, is an Assistant Professor in the Departments of Radiology and Biomedical Engineering at UT Southwestern Medical Center. He earned his doctorate in biomedical engineering from University of California\, Davis\, where he developed hardware and algorithmic solutions to enable quantification with a breast PET/CT scanner. Dr. Bowen then worked as a research fellow at Massachusetts General Hospital on precision PET imaging methods for combined PET/MR. Prior to joining the UT Southwestern faculty in 2020\, he served as a research assistant professor at the Fralin Biomedical Research Institute at Virginia Tech-Carilion. Dr. Bowen’s research program is funded by both industry and the NIH. His work has been featured on the cover of the Journal of Nuclear Medicine and detailed by the press. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-precision-nuclear-medicine-engineering-solutions-from-acquisition-to-analysis/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/02/BElogoWHITE.png
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260302T123000
DTEND;TZID=America/Los_Angeles:20260302T133000
DTSTAMP:20260417T152555
CREATED:20260223T222143Z
LAST-MODIFIED:20260223T223626Z
UID:10009270-1772454600-1772458200@events.ucsc.edu
SUMMARY:CM Seminar - "From Sibelius to Game: Crafting Adaptive Music for 'Kingdom Come: Deliverance'"
DESCRIPTION:Presented by: Adam Sporka \nDescription: “This talk explores the technical and creative processes behind the music of Kingdom Come: Deliverance II\, where I served as a music programmer\, and soundtrack contributor. Using our proprietary Sequence Music Engine and music logic module\, we authentically scored the game’s 1400s Bohemia setting with segment-based adaptive music driven by in-game variables. Our workflow centers around the notation program Sibelius and our custom tool Converdi\, which streamlines the production by converting the score symbols to preliminary MIDI streams per individual VSTs and by extracting the precise timing data necessary for the segment transitions. This enabled us to spend more time on the creative aspects of music and less time on production and implementation.” \nThe key takeaways from the talk are as follows: \n* Production should start with a complete score\, and not just the MIDI exports therefrom\n* Custom automation tools can streamline the music creation workflow and reduce the production time\n* Resequencing is more suitable for classical and medievalesque music than layering\n* Rapid music prototyping allows for early testing of adaptive music directly in the game \nBio: Adam Sporka is a software developer by trade\, a musician by domain\, and a scientist by approach. As a researcher\, developer\, and educator in game audio\, he places a special focus on interactive music. He has served as the technical music director for Kingdom Come: Deliverance II (Warhorse Studios) and is the author of the Sequence Music Engine\, a proprietary adaptive music middleware used in both games. As a composer\, he contributed to the soundtrack of both Kingdom Come: Deliverance games\, writing some of the most memorable medievalesque and early renaissance pieces on the soundtrack. Currently\, he teaches game audio at the University of California\, Santa Cruz. He received his Ph.D. and habilitation in human-computer interaction from the Czech Technical University (Czech Republic) and was a postdoctoral researcher at the University of Trento (Italy). He has published more than 50 articles in the proceedings of international conferences and academic journals. Adam is currently appointed as a principal engineer at Embody\, a Sunnyvale-based game audio software company focused on the commercial applications of the head-related transfer function. \nHosted by: Professor Christina Chung \nWhen: March 2\, 2026 from 12:30PM to 1:30PM \nLocation:  \nIN-PERSON @  SVC 3212. \nViewing room @ UCSC Main Campus\, E2-280. \nLUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend. \nZoom info: \nhttps://ucsc.zoom.us/j/98763397019?pwd=XUG5pnMjgFgCEOlpunV41oRjNMZiO6.1 \nMeeting ID: 987 6339 7019\nPasscode: 273556
URL:https://events.ucsc.edu/event/cm-seminar-from-sibelius-to-game-crafting-adaptive-music-for-kingdom-come-deliverance/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Seminars
GEO:37.3796975;-121.9765484
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260302T160000
DTEND;TZID=America/Los_Angeles:20260302T170000
DTSTAMP:20260417T152555
CREATED:20260202T195322Z
LAST-MODIFIED:20260202T195322Z
UID:10009146-1772467200-1772470800@events.ucsc.edu
SUMMARY:Statistics Seminar: Decoding Phytoplankton Responses to a Changing Ocean
DESCRIPTION:Presenter: Francois Ribalet\, Research Associate Professor\, School of Oceanography\, University of Washington \nDescription: François Ribalet will present new observational technologies and computational approaches for studying phytoplankton responses to ocean warming. Using SeaFlow\, a custom-built automated flow cytometer deployed on over 100 research cruises\, his team has collected nearly 850 billion cell measurements across global oceans. Matrix population models applied to these data reveal how temperature affects phytoplankton division rates and biomass. The research shows that Prochlorococcus\, the ocean’s most abundant photosynthetic organism\, experiences sharp declines in growth above 28°C. Climate projections incorporating these metabolic constraints predict a 40-60% decrease in Prochlorococcus production in tropical regions by 2100\, with Synechococcus partially compensating through a 20-40% increase. These shifts between dominant phytoplankton groups will likely disrupt ocean food webs and carbon cycling\, raising questions about whether tropical ecosystems can adapt to warming oceans. \n\n\n\n\n\n\n\n\n\nBio: François Ribalet is a research associate professor at the University of Washington studying phytoplankton and their role in ocean food webs and carbon cycling. He combines field observations with statistical models to understand how environmental changes affect the growth and community dynamics of these microscopic organisms. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-decoding-phytoplankton-responses-to-a-changing-ocean/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/ph.d.-presentation-graphic-option2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260302T160000
DTEND;TZID=America/Los_Angeles:20260302T170000
DTSTAMP:20260417T152555
CREATED:20260225T181221Z
LAST-MODIFIED:20260225T181221Z
UID:10009355-1772467200-1772470800@events.ucsc.edu
SUMMARY:AM Seminar: The Evolving Landscape of AI for Science and Engineering: Bridging Simulation\, Experiment\, and Multi-scale Dynamics
DESCRIPTION:Presenter: Aditi Krishnapriyan\, Assistant Professor\, UC Berkeley \nDescription: Recent advances in large-scale scientific datasets are creating new opportunities for machine learning (ML) methods to more effectively capture scientific phenomena with greater accuracy and reach. In this talk\, I will discuss how these advances are both shifting ML design paradigms and enabling new scientific inquiries. This includes investigations into understanding if neural networks can autonomously discover fundamental physical relationships from data\, and demonstrating how more flexible machine learning modeling design choices enable capturing physical dynamics across multiple scales. I will also explore how generative modeling approaches rooted in statistical physics can be applied to accelerate the sampling of dynamic pathways\, and as a framework to align and bridge the gap between simulated data and experimental observations. \nBio: Aditi Krishnapriyan is an Assistant Professor at UC Berkeley where she is part of Chemical and Biomolecular Engineering\, Electrical Engineering and Computer Sciences\, and Berkeley AI Research; as well as a faculty scientist in the Applied Mathematics division at Lawrence Berkeley National Laboratory. She holds a PhD from Stanford University\, supported by the DOE Computational Science Graduate Fellowship\, was the Luis W. Alvarez Fellow in Computing Sciences at Lawrence Berkeley National Laboratory\, and is a recipient of the Department of Energy Early Career Award and RCSA Scialog. Her research focuses on developing physics-inspired machine learning methods that bridge machine learning with physical science applications to capture phenomena across multiple length and timescales. \nHosted by: Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-the-evolving-landscape-of-ai-for-science-and-engineering-bridging-simulation-experiment-and-multi-scale-dynamics/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260304T110000
DTEND;TZID=America/Los_Angeles:20260304T121500
DTSTAMP:20260417T152555
CREATED:20260217T182353Z
LAST-MODIFIED:20260217T182353Z
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SUMMARY:CSE Colloquium - Improving Efficiency and Reliability of Foundation Models in Clinical AI
DESCRIPTION:Presenter: Vasiliki “Vicky” Bikia\, PhD\, Stanford Department of Biomedical Data Science and Institute for Human-Centered AI (HAI) \nAbstract: \nDeploying foundation models in health requires both computational efficiency and reliable generation. In this talk\, I present two studies that address these dimensions separately but with a shared goal of real-world clinical deployment. The first study focuses on reduced-resolution distillation for multimodal clinical data\, particularly medical imaging. As model and input sizes increase\, inference cost and memory constraints become major barriers to deployment. We investigate how high-capacity teacher models can transfer structured knowledge to compact student models trained on downsampled images\, using embedding-space supervision to preserve clinically meaningful representations while reducing computational footprint. The second study examines the reliability of AI-generated clinical text. Foundation models are increasingly used to produce discharge summaries and patient-facing explanations\, yet fluency does not guarantee safety. We develop a structured evaluation framework grounded in clinical error taxonomies and clinician-calibrated metrics to quantify hallucinations\, omissions\, and semantic misalignment. Together\, these studies emphasize that scalable clinical AI requires not only smaller and faster models\, but also rigorous evaluation of generative reliability before deployment. \nBio: \nVasiliki Bikia is a Postdoctoral Researcher at Stanford University\, affiliated with the Department of Biomedical Data Science and the Stanford Institute for Human-Centered Artificial Intelligence (HAI). She received an Advanced Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki\, and a Ph.D. in Bioengineering from the Swiss Federal Institute of Technology in Lausanne (EPFL). Her research focuses on medical foundation models\, structured representations of health data\, and the evaluation of generative systems in clinical settings. Previously\, she was a Machine Learning Scientist at the Mussallem Center for Biodesign at Stanford University\, where she developed software pipelines to improve data accessibility and interoperability in digital health applications. Vasiliki was selected as an MIT Rising Star in EECS (2025) and as an Emerson Consequential Scholar (2025)\, and is actively engaged with the Silicon Valley entrepreneurial ecosystem through collaborations at the intersection of research\, industry\, and healthcare. She is an organizing member of the Conference on Health\, Inference\, and Learning (CHIL) and serves as Unconference Chair for the 2025 and 2026 editions\, where she leads the design and execution of the entrepreneurship-focused track bridging academic research and real-world deployment. Her work has appeared in venues including IEEE journals\, npj Digital Medicine\, Nature Communications\, and leading AI conferences\, and she has contributed to multiple funded research proposals and clinical studies at the intersection of AI\, medicine\, and translational impact. \nHosted by: Professor Nikos Tziavelis \nLocation: Engineering 2\, E2-180 (*Refreshments such as coffee\, tea\, fresh fruit\, and pastries will be provided) \nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-improving-efficiency-and-reliability-of-foundation-models-in-clinical-ai/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260305T114000
DTEND;TZID=America/Los_Angeles:20260305T131500
DTSTAMP:20260417T152555
CREATED:20260223T183015Z
LAST-MODIFIED:20260227T202045Z
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SUMMARY:BME 280B Seminar: Artificial intelligence systems to advance engineered T cell immunotherapy designs
DESCRIPTION:Presenter: Zinaida Good\, Assistant Professor of Medicine in the Division of Immunology and Rheumatology and the Division of Computational Medicine\, Stanford University \nDescription: T cell immunotherapies have reshaped the treatment landscape for hematologic malignancies and are rapidly extending to solid tumors\, autoimmune diseases\, and transplant tolerance. Yet durable benefit remains inconsistent\, and toxicities remain clinically significant. The current discovery proceeds one edit at a time\, and existing preclinical models do not represent patient biology\, which often results in failure upon clinical translation. Overcoming these challenges to improve patient outcomes and reduce toxicities requires a systems-level understanding of the multiscale factors governing T cell function and toxicity in patients. Artificial intelligence (AI) approaches offer an exciting opportunity to tackle this problem by learning unified representations from diverse data types spanning molecular\, cellular\, and clinical modalities. I will provide an overview on our team’s approaches building AI systems that harness primary patient datasets to directly inform advanced T cell designs optimized for clinical outcomes\, with validation in preclinical models. \nBio: Zinaida Good\, Ph.D.\, is an Assistant Professor of Medicine in the Division of Immunology and Rheumatology and the Division of Computational Medicine at Stanford University. She also serves as the Director of the Stanford Center for Cancer Cell Therapy Data Hub. The goal of her research program is to understand and enhance engineered T cell immunotherapies for cancer and immune-mediated diseases through innovative computational approaches and systems immunology. Her lab leverages innovation in machine learning and clinical multiomic datasets to build artificial intelligence systems for advanced T cell therapy design. Dr. Good earned her Ph.D. in Computational & Systems Immunology from Stanford University. Her work includes 4 first-author papers (Nature Medicine 2018 & 2022\, Nature Biotechnology 2019\, Trends in Immunology 2019)\, 18+ co-authored papers (including Nature 2019\, 2022\, 2024\, Science 2021\, Nature Methods 2016\, 2022\, and NEJM 2024)\, and an initial senior author papers (ICML 2025\, NeurIPS 2025\, Frontiers in Immunology 2025). Her research is supported by the NIH/NCI Pathway to Independence Award\, NIH/OD Multimodal AI Initiative Award\, NIH/NCI Program Project Grant\, and the Weill Cancer Hub West. Dr. Good has been named an Arthur & Sandra Irving Cancer Immunology Fellow in 2022\, Parker Bridge Fellow in 2023\, and an AACR-Woman in Cancer Research Scholar in 2024. \nHosted by: Professor Vanessa Jonsson\, BMEbe Department
URL:https://events.ucsc.edu/event/bme-280b-seminar-artificial-intelligence-systems-to-advance-engineered-t-cell-immunotherapy-designs/
LOCATION:Biomedical Sciences\, Biomedical Sciences Building Red Hill Road\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260309T080000
DTEND;TZID=America/Los_Angeles:20260309T170000
DTSTAMP:20260417T152555
CREATED:20260225T190019Z
LAST-MODIFIED:20260225T190019Z
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SUMMARY:Statistics Seminar: Evaluating Predictive Algorithms Under Missing Data
DESCRIPTION:Presenter: Amanda Coston\, Assistant Professor\, University of California Berkeley \nDescription: Performance evaluation plays a central role in decisions about whether and how predictive algorithms should be deployed in high-stakes settings. Yet\, in many real-world domains\, evaluation is fundamentally difficult: the data available for assessment are often biased\, incomplete\, or noisy\, and the act of deploying a model can itself alter which outcomes are observed. As a result\, standard evaluation practices may substantially misrepresent both overall model performance and disparities across groups. In this talk\, we examine several common threats to valid evaluation—including measurement error\, selection bias\, and distribution shift—and present principled evaluation methods that enable valid performance assessment under these challenges when appropriate conditions are met. \nBio: From UC Berkeley website: Amanda Coston is an assistant professor of statistics at UC Berkeley. Her research addresses real-world data problems that challenge the validity\, reliability\, and equity of algorithmic decision support systems and data-driven policy-making. Her work draws on techniques from causal inference\, machine learning\, and nonparametric statistics. She earned her PhD in machine learning and public policy at Carnegie Mellon University and subsequently completed a postdoc at Microsoft Research on the Machine Learning and Statistics Team. She also holds a Bachelor of Science in Engineering from Princeton in computer science and a certificate in the Princeton School of Public and International Affairs. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-evaluating-predictive-algorithms-under-missing-data/2026-03-09/1/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/02/BElogoWHITE.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260309T104000
DTEND;TZID=America/Los_Angeles:20260309T114500
DTSTAMP:20260417T152555
CREATED:20260305T230039Z
LAST-MODIFIED:20260305T230039Z
UID:10009404-1773052800-1773056700@events.ucsc.edu
SUMMARY:ECE 290 Seminar: Dynamical Signatures: Harnessing the Hidden Language of In-Space Electric Propulsion
DESCRIPTION:Presenter: Dr. Christine Greve\, Research Engineer\,  Edwards AFB \nDescription: Low-thrust space electric propulsion systems offer long propulsion system lifetimes for satellite maintenance maneuvers. These thrusters operate by generating and accelerating plasmas\, making the thrusters throttleable\, propellant-efficient\, and scalable from low-to-high power operations. This talk will focus on efforts to leverage the underlying time-dependent dynamics of plasma to investigate and influence thruster research and development. Prior years of study have developed techniques to uniquely represent the dynamics of such systems that have since been used to open a new way to test and operate plasma systems. Additional work has investigated the correlations between time-dependent measurements of these dynamics to develop digital twins\, automate test processes with machine learning\, inform design of experiments\, and develop on-orbit system diagnostics. The talk will conclude with a look to the future as these tools are further applied both within the lab and potentially transitioned to on-orbit applications. \nBio: Dr. Christine Greve is a research engineer for the Air Force Research Laboratory at Edwards AFB. She received her Ph.D. in Aerospace Engineering from Texas A&M University under an NDSEG fellowship for her work in data-driven modeling of plasma-based systems. She now serves as the Electric Propulsion group lead with interests in high-power electric propulsion\, machine learning\, data-driven modeling\, and novel plasma diagnostic techniques. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-dynamical-signatures-harnessing-the-hidden-language-of-in-space-electric-propulsion/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/02/BElogoWHITE.png
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260309T160000
DTEND;TZID=America/Los_Angeles:20260309T170000
DTSTAMP:20260417T152555
CREATED:20260217T230434Z
LAST-MODIFIED:20260217T230434Z
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SUMMARY:AM Seminar: Solution Discovery in Fluids with High Precision Using Neural Networks
DESCRIPTION:Presenter: Ching-Yao Lai\, Assistant Professor\, Stanford University \nDescription: I will discuss examples utilizing neural networks (NNs) to find solutions to partial differential equations (PDEs) that facilitate new discoveries. Despite being deemed universal function approximators\, neural networks\, in practice\, struggle to fit functions with sufficient accuracy for rigorous analysis. Here\, we developed multi-stage neural networks (Wang and Lai\, J. Comput. Phys. 2024) that can reduce the prediction error to nearly the machine precision of double-precision floating points within a finite number of iterations. We use accurate NNs to tackle the challenge of searching for singularities in fluid equations (Wang-Lai-Gómez-Serrano-Buckmaster\, Phys. Rev. Lett. 2023). Unstable singularities\, especially in dimensions greater than one\, are exceptionally elusive. With NNs we demonstrate the first discovery of smooth unstable self-similar singularities to unforced incompressible fluid equations (Wang et al.\, arXiv:2509.14185). The example illustrates how deep learning can be used to discover new and highly accurate numerical solutions to PDEs. \nBio: Ching-Yao Lai (Yao) is an Assistant Professor in the Department of Geophysics and an Affiliated Faculty of the Institute for Computational and Mathematical Engineering (ICME) at Stanford. Before joining Stanford\, she was an Assistant Professor at Princeton University. She received an undergraduate degree (2013) in Physics from National Taiwan University and a PhD (2018) in Mechanical and Aerospace Engineering from Princeton University. She completed her postdoctoral research at Columbia University where she received the Lamont Postdoctoral Fellowship. Her current research focuses on enhancing the representation of machine-learning models to tackle multiscale problems. She was the recipient of the 2023 Google Research Scholar Award\, the 2024 Sloan Research Fellowship\, and the 2025 NSF CAREER Award. \nHosted by: Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-solution-discovery-in-fluids-with-high-precision-using-neural-networks/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/ph.d.-presentation-graphic-option2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260309T160000
DTEND;TZID=America/Los_Angeles:20260309T170000
DTSTAMP:20260417T152555
CREATED:20260225T190019Z
LAST-MODIFIED:20260225T190019Z
UID:10009357-1773072000-1773075600@events.ucsc.edu
SUMMARY:Statistics Seminar: Evaluating Predictive Algorithms Under Missing Data
DESCRIPTION:Presenter: Amanda Coston\, Assistant Professor\, University of California Berkeley \nDescription: Performance evaluation plays a central role in decisions about whether and how predictive algorithms should be deployed in high-stakes settings. Yet\, in many real-world domains\, evaluation is fundamentally difficult: the data available for assessment are often biased\, incomplete\, or noisy\, and the act of deploying a model can itself alter which outcomes are observed. As a result\, standard evaluation practices may substantially misrepresent both overall model performance and disparities across groups. In this talk\, we examine several common threats to valid evaluation—including measurement error\, selection bias\, and distribution shift—and present principled evaluation methods that enable valid performance assessment under these challenges when appropriate conditions are met. \nBio: From UC Berkeley website: Amanda Coston is an assistant professor of statistics at UC Berkeley. Her research addresses real-world data problems that challenge the validity\, reliability\, and equity of algorithmic decision support systems and data-driven policy-making. Her work draws on techniques from causal inference\, machine learning\, and nonparametric statistics. She earned her PhD in machine learning and public policy at Carnegie Mellon University and subsequently completed a postdoc at Microsoft Research on the Machine Learning and Statistics Team. She also holds a Bachelor of Science in Engineering from Princeton in computer science and a certificate in the Princeton School of Public and International Affairs. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-evaluating-predictive-algorithms-under-missing-data/2026-03-09/2/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/02/BElogoWHITE.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260311T110000
DTEND;TZID=America/Los_Angeles:20260311T121500
DTSTAMP:20260417T152555
CREATED:20260303T181914Z
LAST-MODIFIED:20260303T181914Z
UID:10009389-1773226800-1773231300@events.ucsc.edu
SUMMARY:CSE Colloquium: Co-Active AI-Assisted Programming
DESCRIPTION:Presenter: Nadia Polikarpova\, UCSD \nAbstract: \nAI-assisted programming has rapidly moved from novelty to default. Today\, most developers use AI coding tools\, and increasingly rely on agentic systems capable of making multi-step design and implementation decisions with minimal human guidance. While these systems boost productivity\, they also introduce new risks: developers may disengage from the reasoning behind generated code\, leading to shallow understanding\, loss of ownership\, and what is increasingly described as cognitive debt. \nIn this talk\, I argue that AI-driven software development must be co-active: humans and AI should remain continuously engaged in a shared process of understanding and decision-making. I will present two complementary research directions toward this goal. The first focuses on observability—helping developers understand\, validate\, and trace the behavior of AI-generated code. The second focuses on controllability—making AI decisions explicit\, persistent\, and steerable. Together\, these ideas restore programmer agency while maintaining the productivity gains of AI-assisted development. \nBio: \nNadia Polikarpova is an associate professor at UC San Diego\, and a member of the Programming Systems group. She received her Ph.D. in Computer Science from ETH Zurich in 2014\, and then spent some time as a postdoctoral researcher at MIT. Nadia’s research interests are at the intersection of programming languages\, AI\, human-computer interaction\, and social computing. \nHosted by: Professor Nikos Tziavelis \nLocation: Engineering 2\, Room E2-180 (*Refreshments such as coffee\, tea\, pastries\, and fresh fruit will be available.) \nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-co-active-ai-assisted-programming/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/02/BElogoWHITE.png
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END:VEVENT
END:VCALENDAR