Behavioral, Econometrics and Theory Seminar Series Presents: Kevin Chen
2025-10-23 13:40 - 15:00 (America/Los_Angeles) | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Economics Behavioral, Econometrics, & Theory Seminar
Date: Thursday, October 23, 2025
Time: 1:40-3:00 p.m.
Location: Engineering 2, Rm 499

Speaker: Kevin Chen
Title: Assistant Professor of Economics
Affiliation: Stanford University
Host: Michael Leung

Seminar title: Compound Selection Decisions: An Almost SURE Approach

ABSTRACT: This paper proposes methods for producing compound selection decisions in a Gaussian sequence model. Given unknown, fixed parameters µ_{1:n} and known σ_{1:n} with observations Yᵢ ∼ 𝒩(μᵢ, σᵢ²), the aim is to select a subset of units S to maximize utility Σ_{i∈S}(μᵢ − Kᵢ) for known costs Kᵢ. Inspired by Stein’s unbiased risk estimate (SURE), we introduce an almost unbiased estimator, ASSURE, for the expected utility of a proposed decision rule. ASSURE allows a user to choose a welfare-maximizing rule from a pre-specified class by optimizing the estimated welfare, thereby producing selection decisions that borrow strength across noisy estimates. We show that ASSURE yields decision rules that are asymptotically no worse than the optimal but infeasible rule in the pre-specified class. We apply ASSURE to p-value decision procedures in A/B testing, selecting Census tracts for economic opportunity, and identifying discriminating firms.

BME 280B Seminar: Preconfigured neuronal firing sequences in human brain organoids
2025-10-30 11:40 - 13:15 | Physical Sciences Building, Physical Sciences Building, Santa Cruz, CA, 95064
Presenter: Tjitse (TJ) van der Molen, Ph.D. (Postdoc, Sharf Lab, UC Santa Cruz and PhD Kosik Lab, UC Santa Barbara)
Description: Neuronal firing sequences are thought to be the building blocks of information and broadcasting within the brain. Yet, it remains unclear when these sequences emerge during neurodevelopment. Here we demonstrate that structured firing sequences appear in spontaneous activity of human and murine brain organoids, both unguided and forebrain identity directed, as well as ex vivo neonatal murine cortical slices. We observed temporally rigid and flexible firing patterns in human and murine brain organoids and early postnatal murine somatosensory cortex, but not in dissociated primary cortical cultures. These results suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by a preconfigured architecture established during neurodevelopment. By demonstrating the developmental recapitulation of neural firing patterns, these findings highlight the potential of brain organoids as a model for neuronal circuit assembly.
Bio: Tjitse van der Molen studies spontaneous and evoked neural circuit activity in human and mouse stem cell derived brain organoids using dense multi electrode arrays. His main goal is to gain a better understanding of how healthy neural circuits process information and how possible malfunctions in neural circuit activity may result in disease, in order to develop appropriate treatments. Tjitse recently completed his PhD in the Kosik lab at UC Santa Barbara and is now continuing his research as a postdoc in the Sharf lab at UC Santa Cruz.
In this talk, Tjitse will present his latest manuscript that is currently in press with Nature Neuroscience, focused on spontaneously occurring repeated sequential firing patterns that are present in the intrinsic activity of both brain organoids and neonatal mouse brain slices but not in 2D primary cultures. Similar sequential firing patterns have recently been shown to be important for information encoding and learning in the human cortex. The presence of these sequential firing patterns in the spontaneous activity of brain organoids that have never received external stimuli supports the notion that they develop in an experience-independent manner.
Hosted by: Professor Josh Stuart, BME Department
Zoom Link: https://ucsc.zoom.us/j/99970819390?pwd=[REDACTED]
Full Schedule: https://docs.google.com/document/d/1xD09vITwd_Pj9Ge6hHEuBFa5zBUYu2O-bjpSibt7VHE/edit?tab=t.0
Room: PSB-240

BME 280B Seminar: Anne Nakamoto, Alan Zhang, Shelbi Russell
2025-11-06 11:40 - 13:15 | Physical Sciences Building, Physical Sciences Building, Santa Cruz, CA, 95064
Presenter 1: Anne Nakamoto, BME PhD Candidate, Corbett-Detig Lab, UC Santa Cruz
Talk: Investigating deleterious mutation burden across populations and landscapes in the California Conservation Genomics Project
Description: Biodiversity is being lost at an accelerated rate due in part to anthropogenic forces, posing a threat to the sustainability of Earth’s ecosystems as well as to human health. A major goal of conservation genomics is to use genomic data to understand population health, which can inform management decisions for the preservation of biodiversity. The California Conservation Genomics Project (CCGP) is an extensive dataset containing species of conservation interest sampled across California, allowing a landscape genomics approach to conservation. Among the many metrics that can be used to assess population health is genetic load, which refers to the reduction in fitness imposed by deleterious mutations. In this work, we construct a bioinformatic analysis framework to identify deleterious genomic variants in CCGP species based on evolutionary constraint. This allows us to investigate patterns in genetic burden across populations and the landscape of California.
Presenter 2: Alan Zhang, BME PhD Candidate, Corbett-Detig Lab, UC Santa Cruz
Talk: Scalable Strain-Level Metagenomic Deconvolution and Assembly Using Pangenome Mutation-Annotated Networks
Description: Strain-level deconvolution of metagenomic samples is essential for pathogen surveillance, mixed infection diagnosis, and evolutionary genomics, yet remains computationally challenging as genomic databases expand. Existing methods scale poorly with database size or rely exclusively on single nucleotide polymorphism (SNP) information. SNP-based approaches rely on mutation-annotated trees and thus require well-established reference genomes, limiting their applicability to divergent species that lack alignable root references. We present panMAMA (panMAN Metagenomic Assignment and Metagenomic Assembly), a method that leverages the pangenome Mutation-Annotated Network (panMAN) data structure to enable accurate strain-level quantification across both closely related and divergent genomes. By employing k-min-mer-based pseudo-chaining with a seed-annotated tree index, panMAMA achieves substantial computational speedup compared to existing k-mer-based tools while maintaining high accuracy. We demonstrate that panMAMA accurately deconvolves both closely related SARS-CoV-2 genomes and divergent HIV and respiratory syncytial virus (RSV) genomes, outperforming existing tools including Freyja on simulated wastewater samples. Through a hybrid heuristic and maximum likelihood approach for read assignment and consensus calling, panMAMA effectively recovers variant genomes from low-heterogeneity samples of divergent species. These results establish panMAMA as a scalable and accurate platform that extends strain-level metagenomic analysis to previously intractable highly divergent species.
Presenter 3: Shelbi Russell, PhD, UC Santa Cruz, Ph.D., Organismic & Evol Bio, Harvard, PostDoc MCDB, UC Santa Cruz
Description: Many animals harbor bacterial symbionts that manipulate host reproduction to enhance bacterial survival and transmission. Obligate intracellular symbionts, such as Wolbachia pipientis, are particularly adept at host manipulation, influencing reproductive biology and even blocking viral replication. These bacterially induced traits have been harnessed in field studies to control mosquito populations and limit the spread of human pathogens like Dengue and Zika viruses. Despite these promising applications, the molecular mechanisms underlying Wolbachia’s interactions with host cells remain poorly understood. Furthermore, even less is known about the implications of these symbionts spreading to non-target hosts in the ecosystem. Previous work from my lab tackled these questions in vivo: we discovered that the wMel strain of Wolbachia can enhance host fertility and we discovered that even extremely low rates of horizontal symbiont transmission among hosts can influence bacterial genome evolution. However, in vivo systems offer limited resolution to identify the precise cellular mechanisms of fertility enhancement and the real-time genomic impacts of horizontal transmission. Here, we use an in vitro Drosophila system to 1) identify the cell type-specific impacts of Wolbachia infection on host-microbe interactions and 2) characterize how strains interact within host tissues during mixed infections. This simplified, easy to sample system enabled us to concentrate the effects of host cell type on Wolbachia gene expression and to control de novo strain infections and mixtures. Through these experiments, we discovered that different host cell types induce differential Wolbachia gene expression that feeds back to alter host gene expression and epigenetic silencing. These findings have motivated on-going single cell RNAseq work to resolve the process at the single cell level, during de novo infections. Results from the experimental mixed infections revealed highly reproducible strain and cell type-specific dynamics. We will leverage these discoveries to understand strain-specific tissue tropisms and how multiple strains can co-exist as superinfections in nature, which will inform future biocontrol strategies.
Bio: Shelbi is an Assistant Professor in the Department of Biomolecular Engineering at UCSC. She started her lab in 2022, after completing her PhD at Harvard University in 2016 and performing her postdoctoral work at UCSC. Her passion for studying symbiotic systems began as an undergraduate researcher at the University of Kansas describing new tapeworm species. She transitioned to studying the evolutionary genomics of bacterial-animal mutualisms in her PhD and was awarded the UC Chancellor’s Postdoctoral Fellowship and the NIH Career Development Award (K99) to test genomic hypotheses in the Wolbachia-Drosophila model system during her postdoc. As faculty, she is working to learn how hosts and microbes function and evolve so we can engineer associations for biological control. She has authored 24 papers and obtained $2.75 million in funding. Her interdisciplinary training makes her uniquely qualified to lead these investigations and has enabled novel breakthroughs in our understanding of symbiont evolution and microbe-induced host phenotypes.
Hosted by: Professor Josh Stuart, BME Department
Room: PSB-240

ECE 290 Seminar: Low-Power and Miniaturized Medical Electronics for in vivo Localization and Tracking
2025-11-17 10:40 - 11:45 | CA
Presenter: Dr. Saransh Sharma, Postdoctoral Scholar, MIT
Description: Accurate in vivo localization of medical devices is central to applications ranging from ingestible pills in the GI tract to endovascular and minimally invasive procedures. However, current clinical methods rely on endoscopy or repeated ionizing imaging (CT/X-ray), and are poorly suited for continuous or out-of-hospital use. In this talk, I will present a radiation-free platform for high-precision localization of wireless miniaturized devices in vivo, using engineered magnetic field gradients. We design battery-less ingestible microdevices that measure and transmit their local magnetic field, while planar coils generate monotonically varying fields in X, Y, and Z. This architecture uniquely encodes spatial position and achieves <100 μm 3D accuracy—to our knowledge, the highest reported. We then translate this to in vivo large-animal studies to localize ingestible devices in the GI tract in real time with mm-scale resolution, without radiation or hospital-grade imaging. This enables continuous monitoring relevant to constipation, incontinence, motility disorders, medication adherence, and quantitative GI transit-time. Next, I will show how this platform generalizes to surgical navigation. By embedding the same localization architecture into catheters and guidewires, we can track device position without fluoroscopy, offering a pathway toward image-free vascular navigation and minimally invasive interventions. Finally, to further shrink devices and power, I developed a monolithic 3D magnetic sensor in 65 nm CMOS (4 mm², 14.8 μW, <10 μT_rms noise). This fully CMOS-compatible architecture enables high-sensitivity magnetic sensing at μW power, and can serve as the core for future miniaturized, radiation-free localization systems.
Bio: Dr. Saransh Sharma received the B.Tech. degree in Electronics and Electrical Communication Engineering from the Indian Institute of Technology (IIT), Kharagpur, India, in 2017, and the M.S. and Ph.D. degrees in Electrical Engineering from the California Institute of Technology (Caltech), Pasadena, CA, USA, in 2018 and 2023, respectively. He is currently a postdoctoral research scholar at the Massachusetts Institute of Technology (MIT), Cambridge, USA, working on low-power analog and mixed-signal integrated circuits and system design for bio-medical applications. Dr. Sharma was a recipient of the Wilts Prize and the Demetriades-Tsafka-Kokkalis Award for outstanding Ph.D. thesis in Electrical Engineering, Biotechnology and related fields at Caltech, Lewis Winner Award for outstanding paper at ISSCC 2024, Best Student Paper Award at CICC 2025, Charles Lee Powell Fellowship at Caltech, and Excellence in Mentorship Award at Caltech for mentoring undergraduate and graduate students.
Hosted by: Professor Soumya Bose, ECE Department
Zoom Link: https://ucsc.zoom.us/j/97975378707?pwd=[REDACTED]

Global Learning Alumni Panel: Study Abroad & Away Experiences
2025-11-17 12:00 - 13:00 | CA
Have you ever wondered what it’s like to study abroad or participate in a domestic study away program?
Join us for a virtual alumni panel where past participants of global learning programs will share their unique experiences, personal stories, and advice for making the most of your journey. This is your chance to ask questions, get inspired, and connect with alumni who have been where you’re headed. Don’t miss out!
Register here for the Global Learning Alumni Panel
Date: Monday, November 17
Time: 12:00 – 13:00
Location: Zoom
This event is part of UCSC’s International Education Week. If you have any questions, please contact us at globallearning@ucsc.edu.

CM Seminar: "Playful Design to Empower Climate Adaptation - What are we missing for real-life impact?"
2025-11-17 12:30 - 13:30 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Presented by: Linda Hirsch

Description: “Games and playful interventions have been researched to increase awareness of climate change impacts and educate about mitigation and adaptation measures. However, besides increased awareness, what real-life impact and adapted behaviors can we actually observe from such interventions? In this talk, I will reflect on the differences between short-term and long-term community empowerment through playful interventions and discuss three outstanding research directions for designing real-life climate adaptation.”
Bio: Linda Hirsch is a postdoctoral researcher at Computational Media, UCSC, under the supervision of Katherine Isbister. She holds a magna cum laude doctoral degree in Media Informatics from LMU Munich, Germany. Her research focuses on exploring, conceptualizing, and creating meaningful human-environment interactions to strengthen communities toward increased climate resilience. Linda Hirsch has been an elected executive committee member of the German group “Be-greifbare Interaktion” since 2021, an expert research group within the German Society of Information Technology regarding topics for tangible and embedded interfaces.

Hosted by: Professor Katherine Isbister
When: Monday, November 17, 2025 from 12:30PM to 1:30PM
Location:
IN-PERSON @ UCSC Main Campus, E2-280.
Viewing room @ SVC 3212.
LUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend.

Zoom info:
https://ucsc.zoom.us/j/97750591512?pwd=[REDACTED]
Meeting ID: 977 5059 1512
Passcode: [REDACTED]

ECE 290 Seminar: Fundamental Nanopower Analog Circuits
2025-11-24 10:40 - 11:45 | CA
Presenter: Joey Sankman, Analog/Power Designer, Analog Devices
Description: With the rising interest in edge computing, and the addition of AI/ML functionality, nanopower circuits are in great demand to reduce the quiescent power consumption of remote sensors. In this tutorial, fundamental building blocks for nanopower circuits will be covered, including startup-less low-voltage references, low-frequency clocks, and LDO regulators. Attendees can expect a deep dive into fundamental and practical analog techniques to design nanopower systems.
Bio: Joey Sankman received the B.S. degree from the University of Arizona, Tucson, AZ, and Ph.D. degree from the University of Texas at Dallas, TX in electrical engineering in 2010 and 2014, respectively. At the University of Texas at Dallas, his research included energy harvesting circuits and systems as well as high-performance switch mode power converters. He is currently an analog/power designer at Analog Devices, Principal Member of Technical Staff, working on automotive PMICs. Previously, he was an Analog R&D Engineer working on audio amplifiers, ultra-low power circuits, and radhard gate drivers at Kilby Labs, TI, Dallas, TX. He was the recipient of the U.S. National Science Foundation Graduate Research Fellowship and the 2011 Texas Instruments/Semiconductor Research Corporation Graduate Fellowship. He has authored or co-authored 20 publications in various IEEE journals and conferences. He currently serves on the IEEE ISSCC power subcommittee.
Hosted by: Professor Soumya Bose, ECE Department
Zoom Link: https://ucsc.zoom.us/j/97975378707?pwd=[REDACTED]

AM Seminar: Linear Stochastic Emulators of the Ocean Circulation based on Balanced Truncation: A Caution, perhaps, for Machine Learning?
2025-11-24 16:00 - 17:00 | CA
Presenter: Professor Andy Moore, UCSC Ocean Sciences
Description: Linear inverse models have enjoyed considerable popularity in the geosciences, particularly in the arena of climate research and climate prediction, for several decades as a straightforward approach to dimension reduction and streamlining computational efficiency. The most common approach is to truncate the system by retaining the leading Empirical Orthogonal Functions (EOFs) which represent the left singular vectors of the transition matrix. While singular value decomposition is the best low rank approximation of the transition matrix, ignoring information contained in the right singular vectors, as is commonly done in linear inverse models, has consequences for the dynamics that approximate the system. Dimension reduction based on balanced truncation simultaneously preserves information from the right and left singular vectors. This talk will review some of these ideas and present examples from the ocean. Since EOF decomposition is quite commonly used for dimension reduction in some machine learning approaches, there may be some lessons here for the machine learning community to consider.
Bio: Professor at UCSC since 2016.
Hosted by: Professor Julie Simons

AM Seminar: Denoising: A Powerful Building Block for Imaging, Inverse Problems and Machine Learning
2025-12-01 16:00 - 17:00 | https://ucsc.zoom.us/j/93681175800?pwd=[REDACTED]
Presenter: Peyman Milanfar, Distinguished Scientist, Google
Description: Denoising, the process of reducing random fluctuations in a signal to emphasize essential patterns, has been a fundamental problem of interest since the dawn of modern scientific inquiry. Recent denoising techniques, particularly in imaging, have achieved remarkable success, nearing theoretical limits by some measures. Yet, despite tens of thousands of research papers, the wide-ranging applications of denoising beyond noise removal have not been fully recognized. This is partly due to the vast and diverse literature, making a clear overview challenging. This article aims to address this gap. We present a clarifying perspective on denoisers, their structure and their desired properties. We emphasize the increasing importance of denoising and showcase its evolution into an essential building block for complex tasks in imaging, inverse problems and machine learning. Despite its long history, the community continues to uncover unexpected and groundbreaking uses for denoising, further solidifying its place as a cornerstone of scientific and engineering practice.
Bio: Peyman is a Distinguished Scientist at Google, where he leads the Computational Imaging team. Prior to this, he was a Professor of Electrical Engineering at UC Santa Cruz for 15 years, two of those as Associate Dean for Research. From 2012-2014 he was on leave at Google-x, where he helped develop the imaging pipeline for Google Glass. Over the last decade, Peyman’s team at Google has developed several core imaging technologies that are used in many products. Among these are the zoom pipeline for the Pixel phones, which includes the multi-frame super-resolution (Super Res Zoom) pipeline, and several generations of state of the art digital upscaling algorithms. Most recently, his team led the development of Pro Res Zoom, and Unblur, features launched in Pixel 10 devices and Google Photos. Peyman received his undergraduate education in electrical engineering and mathematics from the UC Berkeley, and the MS and PhD degrees in electrical engineering from MIT. He holds more than two dozen patents. He founded MotionDSP, which was acquired by Cubic Inc. Along with his students and colleagues, his research work has had deep impact in several areas of computational imaging, and applications of AI thereto – including the introduction of adaptive kernel regression to imaging; pioneering use of learning for fast, content-adaptive image upscaling (RAISR); Neural Image quality Assessment (NIMA), Regularization by Denoising (RED); and most recently (2024) Inversion by Direct Iteration (InDI). All of these works have been recognized with best paper awards. He’s been a Distinguished Lecturer of the IEEE Signal Processing Society, and is a Fellow of the IEEE “for contributions to inverse problems and super-resolution in imaging”
Hosted by: Professor Julie Simons, Applied Mathematics
Zoom link: https://ucsc.zoom.us/j/93681175800?pwd=[REDACTED]
Meeting ID: 936 8117 5800
Passcode: [REDACTED]

When Less is More: Applications of Type-Based Underapproximate Reasoning
2025-12-03 11:00 - 12:30 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Presenter: Suresh Jagganathan, Purdue University

Abstract:
Unlike program verifiers, symbolic execution and property-based testing tools underapproximate program behavior: they aim to report only real bugs (no false positives), at the cost of potentially missing some (false negatives). Recent work has sought to place such tools on a more formal footing, primarily through the development of incorrectness logics that capture a program’s ‘must’ rather than ‘may’ behavior. This talk explores how to transplant these ideas of underapproximation into an expressive refinement type system. Our development enables us to:

(a) Typecheck the completeness of property-based testing (PBT) generators, ensuring that a well-typed generator produces all values (i.e., fully covers) its output type;

(b) Synthesize effectful generators by extending the type system to model underapproximations of sequences of effects rather than just values; and

(c) Guide symbolic execution in effectful functional programs, prioritizing execution paths capable of falsifying data structure safety properties.

Our results demonstrate that viewing types through the lens of underapproximation offers a principled foundation for designing, implementing, and reasoning about program analyzers and test generators, significantly improving their reliability and practical utility in the process.

Bio:
Suresh Jagannathan is the Samuel D. Conte Professor of Computer Science at Purdue University. His interests span functional programming, program verification, distributed and concurrent systems, and trustworthy machine learning. In recent years, he has spent time as an Amazon Scholar, a program manager at the Information Innovoation Office (I2O) at DARPA, and a visiting researcher at the University of Cambridge. He serves an Associate Editor of ACM TOPLAS, and has served as both General and PC Chair of POPL (ACM Symposium on Programming Languages).

Hosted by: Professor Mohsen Lesani

Location: E2-180
*Refreshments such as coffee and pastries will be provided

Zoom: https://ucsc.zoom.us/j/93445911992?pwd=[REDACTED]

BME 280B Seminar: Gali Bai & David Haussler
2025-12-04 11:40 - 13:15 | Physical Sciences Building, Physical Sciences Building, Santa Cruz, CA, 95064
Presenter 1: Gali Bai, BME/PBSE Doctoral Candidate, Brooks Lab, UC Santa Cruz
Title 1: Dissecting the contribution of chromatin accessibility to RNA transcription and processing with long-read sequencing
Description: Although all cells in an organism share the same genomic sequence, transcriptional programs vary dramatically across cell types. This diversity is governed by epigenetic regulation involving the coordinated activities of chromatin remodelers, histone modifiers, and histone chaperones that precisely modulate chromatin accessibility. While previous studies have shown that chromatin accessibility at DNase I–hypersensitive sites such as promoters and enhancers is closely associated with gene expression, much less is known about how chromatin influences transcription and RNA processing. To study how chromatin regulates RNA processing, we perturbed yeast chromatin accessibility by deleting two highly conserved chromatin remodelers ISW1 and CHD1. With Oxford Nanopore long-read sequencing, we profiled nascent RNA, full-length mRNA, and chromatin fibers in wild-type and chd1 isw1 double-mutant yeast cells. Loss of ISW1 and CHD1 led to increased chromatin accessibility within intragenic regions, accompanied by aberrant transcription initiation. Leveraging long-read data, we associated distinct chromatin states with specific RNA processing events and isoform expression outcomes. Despite a similar level of chromatin perturbations across the genome, genes with low baseline expression showed extensive transcriptional reprogramming, whereas highly expressed genes remained largely unaffected. These discrepancies can be partially explained by differences in the enrichment of transcription initiation motifs. In intron-containing genes, loss of ISW1 and CHD1 reduced splicing efficiency and increased intron retention, likely due to disrupted RNAPII elongation in the double mutant. Together, our findings highlight the crucial role of ATP-dependent chromatin remodelers in maintaining nucleosome organization and coordinating co-transcriptional RNA processing.
Presenter 2: David Haussler, Distinguished Professor, UC Santa Cruz
Title 2: Brain Organoids
Bio: Haussler received his PhD in computer science from the University of Colorado at Boulder. He is a member of the National Academy of Sciences, the National Academy of Engineering, the American Academy of Arts and Sciences and a fellow of AAAS and AAAI. He has won a number of awards, including the 2015 Dan David Prize, the 2011 Weldon Memorial Prize from University of Oxford, the 2009 ASHG Curt Stern Award in Human Genetics, the 2008 Senior Scientist Accomplishment Award from the International Society for Computational Biology, the 2005 Dickson Prize for Science from Carnegie Mellon University, and the 2003 ACM/AAAI Allen Newell Award in Artificial Intelligence.
Hosted by: Professor Josh Stuart, BME Department

CSE Colloquium: Making Systems Secure with Information Flow
2025-12-08 09:30 - 10:45 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Presenter: Andrew Myers, Cornell University

Abstract:
Modern civilization depends on complex, interconnected software systems that must safeguard trustworthy or private data. We have ever-growing mountains of code yet lack principled ways to build large systems that are secure. What is missing is a way to securely build these systems compositionally: module by module and layer by layer. Information flow control, enforced throughout software and hardware, offers a plausible way to achieve compositional security, and is increasingly being used by industry. I describe how my research group has incorporated information-flow security into various languages and systems: hardware architectures resilient to timing and speculation attacks, smart contracts, and automatically synthesized cryptographic and distributed protocols. Information flow is inherently compositional and makes possible strong, provable security guarantees that can be connected to cryptographic security definitions. Importantly, it also guides developers during the design process, exposing security-critical decisions up front.
Bio:
Andrew Myers is the Class of 1912 Professor of Engineering in the Department of Computer Science at Cornell University. He received his Ph.D. in Electrical Engineering and Computer Science from MIT, advised by Barbara Liskov. His research interests include programming languages, computer security, and distributed and persistent programming systems. His work on computer security has focused on practical, sound, expressive languages and systems for enforcing information security. Myers is an ACM Fellow and has authored several award-winning papers. He currently serves as the chair of the ACM SIGPLAN Executive Committee.
Hosted By: Professor Mohsen Lesani
Location: Engineering 2, E2-180
Zoom: https://ucsc.zoom.us/j/97682837116?pwd=[REDACTED]

The Everett Program Presents: Envisioning Digital Justice Together | 7th Annual Project Showcase
2025-12-10 15:30 - 19:00 | Merrill Cultural Center, 200 McLaughlin Dr, Santa Cruz, CA, 95064
The Everett Program Presents: Envisioning Digital Justice Together | 7th Annual Project Showcase
This showcase aims to highlight the incredible work of our students, who have completed a year-long practicum conceptualizing and using digital technology to work with nonprofit organizations on social justice issues from climate justice to the racist impacts of the carceral state.
This year, Showcase is an event in which the audience can not only come together to support these wonderful students and their work, but also to envision a range of digital futures together.
All are welcome! RSVP with the QR Code found on the poster, we hope to see you there 🙂

CM Seminar - "How Technology-Mediated Food Interactions Support Family Connection and Routine Reconstruction"
2026-01-05 12:30 - 13:30 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Presented by: Aswati Panicker
Description: “In this talk, I draw on work in human-food interaction (HFI) to examine how food can serve as a rich interaction medium for connection and routine reconstruction in long-distance families. I highlight insights from three of my studies that explore this question across different technological forms. First, I discuss how families navigate shifting meanings of “healthy eating” during life transitions, and the tensions that arise when disclosing new goals and priorities in health-sharing or tracking tools. Second, I show how family members expressed hesitations, value conflicts, and visions for cultural or playful moments when imagining embodied technology such as a social robot within their domestic spaces. Third, through a mobile app probe for teaching food knowledge and recipes, I uncover the subtleties of how family members seek to initiate, learn, guide, or be guided through everyday food practices. Throughout, I outline design implications and close by reflecting on how technology-mediated food interactions might extend to other contexts and routines beyond family life.”
Bio: Aswati Panicker is a postdoctoral scholar at the University of California, Santa Cruz, working with Prof. Christina Chung. Her research is at the intersection of HCI and CSCW, focusing on how technologies are designed and used in social and health-related contexts. She takes a human-centered, participatory approach and draws on theories from family studies and sociology in her work. She earned her PhD in Informatics from Indiana University Bloomington in July 2025. You can read more at aswatipanicker.com

Hosted by: Professor Christina Chung
When: Monday, January 5, 2026 from 12:30PM to 1:30PM
Location:
IN-PERSON @ SVC 3212.
Viewing room @ UCSC Main Campus, E2-280.
LUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend.
Zoom info:
https://ucsc.zoom.us/j/98742808551?pwd=[REDACTED]
Meeting ID: 987 4280 8551
Passcode: [REDACTED]

AM Seminar with Dr. Truong Vu
2026-01-05 16:00 - 17:00 | Jack Baskin Engineering, 372
Presenter: Dr. Truong Vu, IPAM and MSU
Description: We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a penalty method to develop families of locally incompressible gradient flows that couple interface stretching or compression to local flux of interfacial mass. We establish the convergence of the penalty method to an incompressible flow both formally for a broad family of surface energies and rigorously for a more narrow class of surface energies.
Bio: Dr. Vu received a Ph.D. in Applied Mathematics from the Department of Mathematics, Statistics, and Computer Science at University of Illinois at Chicago. Dr. Vu is currently a Postdoctoral Fellow at the Institute for Pure and Applied Mathematics (UCLA) and a visiting faculty in the Department of Mathematics at Michigan State University.
Hosted by: Applied Mathematics

BME 280B Seminar: Nature’s Miniature Masterpieces - Nanobodies as Small but Mighty Antibodies for the next Pandemic
2026-01-08 11:40 - 13:15 | Physical Sciences Building, Physical Sciences Building, Santa Cruz, CA, 95064
Presenter: Katja Hanack, Founder and CEO, New/Era/Mabs
Description: Nanobodies combine remarkable simplicity with surprising power. Their small size allows them to reach targets that remain inaccessible to conventional antibodies, while maintaining high specificity and stability. Their compact architecture allows them to access targets that conventional antibodies cannot reach, yet they preserve the specificity and power that make antibody therapeutics so transformative. In this talk I will introduce the science behind selma, a cell based discovery platform developed over more than a decade to rapidly identify high quality antibodies and nanobodies. I will explore why these tiny binders matter, how they differ from classical antibodies, and what their unique biology enables for diagnostics and therapeutics.
The presentation will conclude with my current project on immune infrastructure and how pre validated nanobody archives can shift the pandemic response from a reactive model to proactive preparedness for future outbreaks.
Bio: Katja Hanack, PhD, MBA, is the Founder and CEO of new/era/mabs and a leading expert in antibody discovery for diagnostic and therapeutic applications, with a particular focus on nanobody technologies. With more than 20 years of experience, she has developed pioneering platforms that enable the efficient generation and selection of next-generation monoclonal antibodies and nanobodies. She holds a Biology degree from Humboldt University of Berlin and a PhD in Biotechnology from the University of Potsdam. As a former Professor of Biochemistry and Biology at the University of Potsdam, she built and led a research group of 25 scientists, secured over €16 million in external funding, and authored more than 40 peer-reviewed publications. Since 2017, Dr. Hanack has contributed to translational innovation as an industrial advisor for SPARK Stanford and SPARK Berlin, supporting academic teams in bringing biomedical discoveries to patients.
Hosted by: Professor Rebecca Dubois, BME Department

Kathleen Schmidt: Sequential Experimental Design for Materials Strength Model Calibration
2026-01-12 16:00 - 17:00 | Jack Baskin Engineering, 165
Presenter: Katie Schmidt, UQ & Optimization Group Leader, Lawrence Livermore National Laboratory
Description: Due to the time and expense associated with physical experiments, there is significant interest in optimal selection of the conditions for future experiments. Selection based on reduction in parameter uncertainty provides a natural path forward. We consider this type of optimal sequential design in the context of Bayesian calibration of materials strength models with the strength model characterizing the evolving resistance of a material to permanent strain. This problem is particularly challenging because different types of experiments and associated diagnostics are employed across strain rate regimes. For lower-strain-rate experiments, stress-strain curves can be measured directly. For higher-strain-rate experiments, strength must be inferred (e.g., from the deformation of a cylinder of material in a Taylor cylinder experiment). We employ data fusion in our sequential design methodology to incorporate these multiple experimental modalities.
LLNL-ABS-835231 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Bio: Katie Schmidt is the UQ & Optimization Group Leader at Lawrence Livermore National Laboratory. She joined LLNL in 2016 after earning a PhD in Applied Mathematics from North Carolina State University. During her time at the lab, Katie has been involved in a variety of uncertainty quantification problems related to national security as well as outreach and education through LLNL’s Data Science Institute. Her research interests include mixed-effects models, Bayesian inference, sequential design, and sensitivity analysis.
Hosted by: Statistics Department

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