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DTSTART;TZID=America/Los_Angeles:20251210T130000
DTEND;TZID=America/Los_Angeles:20251210T150000
DTSTAMP:20260430T164658
CREATED:20251204T161744Z
LAST-MODIFIED:20251205T222136Z
UID:10005732-1765371600-1765378800@events.ucsc.edu
SUMMARY:Singh\, A. (ECE) - Quantum Key Distribution Using Entangled Pairs with Random Grouping
DESCRIPTION:Quantum Key Distribution (QKD) provides information-theoretic security for cryptographic key establishment\, but existing protocols exhibit limited noise tolerance\, restricting their applicability in practical quantum channels with finite resources. This work introduces a QKD protocol based on entanglement swapping that significantly enhances error tolerance and key generation rates. The protocol encodes six-bit classical symbols into six-qubit entangled states organized as three Bell pairs. Key contributions include: (1) maintaining positive secrecy rates under 100% intercept-resend attacks\, unprecedented among existing protocols\, (2) proven security against collective attacks up to 29.29% quantum bit error rate (QBER)\, substantially exceeding BB84’s 11% threshold\, and (3) finite-key security analysis demonstrating viable key generation under practical block size constraints. These results establish that structured multi-qubit encoding fundamentally broadens the operational capabilities of quantum key distribution\, enabling secure communication in high-noise environments such as free-space satellite links and urban channels where conventional protocols fail. \nHost: Archana Jayprakash Singh\, Ph.D. Student\, Electrical and Computer Engineering  \nAdvisor: Zouheir Rezki  \nZoom- https://ucsc.zoom.us/j/92875779810?pwd=xIWhFkOw5WR3vyBvVhBCkd7ueJs2m2.1 \nPasscode- 530049
URL:https://events.ucsc.edu/event/singh-a-ece-quantum-key-distribution-using-entangled-pairs-with-random-grouping/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251209T160000
DTEND;TZID=America/Los_Angeles:20251209T170000
DTSTAMP:20260430T164658
CREATED:20251202T204536Z
LAST-MODIFIED:20251209T182652Z
UID:10005719-1765296000-1765299600@events.ucsc.edu
SUMMARY:Zhu\, R. (ECE) -  From Neuromorphic Principles to Efficient Neural Language Architectures
DESCRIPTION:While Large Language Models exhibit remarkable capabilities\, their reliance on the standard Transformer architecture imposes prohibitive computational costs and quadratic memory complexity. To bridge the gap between biological efficiency and high-performance AI\, we have established foundational work in linearizing attention and maximizing hardware utilization through architectures such as RWKV and MatMul-Free networks. Addressing the remaining bottlenecks in long-term memory consolidation and optimization stability\, we propose a research roadmap focused on “In-Place Test-Time Training” (TTT) to enable compositional memory via dynamic weight updates\, and the Muon optimizer to stabilize deep reasoning through orthogonal gradient updates. Ultimately\, this work aims to unify neuromorphic principles with scalable deep learning to enable robust performance in resource-efficient environments. \nEvent Host: Ridger Zhu\, Ph.D. Student\, Electrical and Computer Engineering  \nAdvisor: Jason Eshraghian \nZoom- https://ucsc.zoom.us/j/95241268060?pwd=WDMgDWhhSyXNh8NZpBDvgpbcMVbvUz.1 \nPasscode- 256794
URL:https://events.ucsc.edu/event/ridger-z-ece-from-neuromorphic-principles-to-efficient-neural-language-architectures/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251208T130000
DTEND;TZID=America/Los_Angeles:20251208T140000
DTSTAMP:20260430T164658
CREATED:20251202T163305Z
LAST-MODIFIED:20251202T163305Z
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SUMMARY:de Priester\, J. (ECE) - Hybrid Reinforcement Learning
DESCRIPTION:Reinforcement Learning (RL) is a machine learning paradigm that trains a decision maker\, or policy\, by learning from interaction with an environment. The power of RL lies in its ability to learn complex strategies without explicit human instruction\, which can lead to better solutions that human designers overlook in domains ranging from robotics to scientific discovery. Despite these successes\, applying RL to safety-critical control systems remains a significant challenge due to the fragility of black-box policies. Standard RL controllers are prone to “chattering” or indecisiveness\, which is rapid\, detrimental switching between decisions induced by small disturbances\, and lack formal closed-loop safety\, stability\, and robustness guarantees. Furthermore\, existing discrete and continuous-time RL paradigms struggle to model hybrid systems\, where continuous state evolution is intertwined with instantaneous discrete updates. Consequently\, standard RL approaches cannot effectively be applied to safety-critical hybrid dynamical systems\, as such approaches suffer from discretization artifacts\, computational inefficiency\, and a lack of closed-loop safety\, stability\, and robustness guarantees. \nTo bridge the gap between hybrid control theory and RL\, this research proposal is organized into four interconnected thrusts. Thrust 1 addresses the fragility of existing standard RL-based policies by designing RL algorithms to construct robust hybrid supervisors to eliminate chattering. Thrust 2 establishes the theoretical bedrock of a native hybrid RL formulation. By leveraging insights from discounted MPC\, the hybrid RL problem is formulated with intrinsic closed-loop stability\, safety\, and robustness properties. Thrust 3 extends standard RL components to the hybrid domain to create RL algorithms capable of solving the hybrid RL problem defined in Thrust 2. Finally\, Thrust 4 provides comprehensive empirical validation\, confirming the robustness of the supervisors from Thrust 1 and demonstrating the advantages of the native hybrid RL formulation developed in Thrusts 2 and 3 over a standard RL formulation. \nHost: Jan de Priester\, Ph.D. Student\, Electrical and Computer Engineering  \nAdvisor: Ricardo Sanfelice \nZoom- https://ucsc.zoom.us/j/95229790206?pwd=ICevzd4QdEE7ZAlYALZIYbhU2bCU4W.1 \nPasscode-  981137
URL:https://events.ucsc.edu/event/de-priester-j-ece-hybrid-reinforcement-learning/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251124T104000
DTEND;TZID=America/Los_Angeles:20251124T114500
DTSTAMP:20260430T164658
CREATED:20251117T231136Z
LAST-MODIFIED:20251117T231136Z
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SUMMARY:ECE 290 Seminar: Fundamental Nanopower Analog Circuits
DESCRIPTION:Presenter: Joey Sankman\, Analog/Power Designer\, Analog Devices \nDescription: 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. \nBio: 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. \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-fundamental-nanopower-analog-circuits/
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251121T140000
DTEND;TZID=America/Los_Angeles:20251121T160000
DTSTAMP:20260430T164658
CREATED:20251021T182427Z
LAST-MODIFIED:20251022T181942Z
UID:10004960-1763733600-1763740800@events.ucsc.edu
SUMMARY:Torres\, S. (ECE) - An Integrated Platform for Real-time Monitoring and Support of 3D Tissue Growth
DESCRIPTION:Organoids are three-dimensional tissue cultures that model real organs and serve as valuable tools for studying development\, disease\, and treatment response. Traditional methods\, which rely on manual handling and incubators\, limit consistency and real-time monitoring. To address these issues\, we developed a modular microfluidic platform that integrates automated feeding\, live fluorescence imaging\, and environmental control without the need for a standard incubator. The core of the system is a vertically oriented PDMS-glass chip that enables precise media delivery and continuous imaging of small 3D structures such as organoids. Using fluorescent dyes to mimic molecules\, such as nutrients or drugs\, we tracked their movement through tissue in real time without invasive sensors. This setup maintains metabolic stability and provides detailed insight into molecular transport\, which improves applications in disease modeling\, drug testing\, and personalized medicine. \n  \nEvent Host- Sebastián Torres\, Ph.D. Candidate\, Electrical & Computer Engineering  \nAdvisor: Mircea Teodorescu \n  \nZoom- https://ucsc.zoom.us/j/2333595627?pwd=aWtwL3V2QnFTMkNDSWowZnRNS0xSQT09 \nPasscode- 579836
URL:https://events.ucsc.edu/event/torres-s-ece-an-integrated-platform-for-real-time-monitoring-and-support-of-3d-tissue-growth/
CATEGORIES:Ph.D. Presentations
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/10/option-3-1.png
LOCATION:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251121T123000
DTEND;TZID=America/Los_Angeles:20251121T140000
DTSTAMP:20260430T164658
CREATED:20251118T163526Z
LAST-MODIFIED:20251118T163526Z
UID:10005179-1763728200-1763733600@events.ucsc.edu
SUMMARY:Ramollari\, H. (ECE) - An Optofluidic Spectrometer and Applications in Biosensing
DESCRIPTION:Miniaturized spectrometers have the potential to replace bulky and expensive benchtop models. We have previously demonstrated a multimode interference (MMI) waveguide-based spectrometer that achieves high performance while minimizing its footprint. \nIn this talk\, the integration of the MMI spectrometer into an optofluidic device is proposed. This integration opens up applications such as the detection of single particle fluorescence spectra and absorption spectra. \nMoreover\, adding a metasurface to the spectrometer waveguide is expected to enhance the sensitivity of single particle detection and simplify the analysis methods. \nFinally\, to improve the MMI waveguide spectrometer a new nanophotonic platform is proposed. \nEvent Host: Helio Ramollari\, Ph.D. Student\, Electrical Engineering  \nAdvisor: Holger Schmidt  \nZoom- https://ucsc.zoom.us/j/99623652977?pwd=j2hy77fV9jdGuEzI0iGa5JVAa35W1b.1 \nPasscode- 576057
URL:https://events.ucsc.edu/event/ramollari-h-ece-an-optofluidic-spectrometer-and-applications-in-biosensing/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251117T104000
DTEND;TZID=America/Los_Angeles:20251117T114500
DTSTAMP:20260430T164658
CREATED:20251113T000837Z
LAST-MODIFIED:20251113T000837Z
UID:10005135-1763376000-1763379900@events.ucsc.edu
SUMMARY:ECE 290 Seminar: Low-Power and Miniaturized Medical Electronics for in vivo Localization and Tracking
DESCRIPTION:Presenter: Dr. Saransh Sharma\, Postdoctoral Scholar\, MIT \nDescription: 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. \nBio: 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. \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-low-power-and-miniaturized-medical-electronics-for-in-vivo-localization-and-tracking/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/11/BE-logomark_localist.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251113T163000
DTEND;TZID=America/Los_Angeles:20251113T190000
DTSTAMP:20260430T164658
CREATED:20251017T180809Z
LAST-MODIFIED:20251017T180809Z
UID:10004908-1763051400-1763060400@events.ucsc.edu
SUMMARY:Leveraging UC Resources To Launch Your Biotech Company
DESCRIPTION:Are you a UCSC faculty member\, postdoc\, or graduate student with an entrepreneurial mindset? \nJoin us for an insightful panel discussion on how to turn your biotech research into a successful startup. Learn how to tap into the University of California’s robust innovation ecosystem—from research commercialization and funding opportunities to mentorship and startup incubation. \nHear firsthand from UC-affiliated founders\, investors\, and innovation experts who have successfully navigated the path from lab discovery to market launch. Stay afterward for a networking reception to connect with peers\, panelists\, and campus innovation partners. \nOpen to: UCSC faculty\, postdocs\, and graduate studentsLight refreshments provided. \nRegistration requested: https://luma.com/2gmhjlbo
URL:https://events.ucsc.edu/event/uc-resources-to-launch-your-biotech-company/
LOCATION:Hay Barn\, 94 Ranch View Road\, Santa Cruz\, CA\, 95064\, United States
CATEGORIES:Meetings & Conferences
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251107T000000
DTEND;TZID=America/Los_Angeles:20251108T235959
DTSTAMP:20260430T164658
CREATED:20251013T212720Z
LAST-MODIFIED:20251023T232623Z
UID:10004811-1762473600-1762646399@events.ucsc.edu
SUMMARY:United Nations Reboot the Earth Hackathon
DESCRIPTION:The United Nations (UN) and the Baskin School of Engineering at the University of California\, Santa Cruz\, are collaborating to bring the “Reboot the Earth” hackathon to the West Coast for the first time. \nThis is a social event bringing together aspiring developers to create open source software solutions that address the climate crisis\, including wildfire response. It’s a chance to collaborate with peers\, use open data\, and apply your coding skills to real-world climate challenges! \n\n\n\nDate: November 7-8\, 2025\nLocation: UC Santa Cruz Silicon Valley Center.\nRegister here for the event. \n\nOrganized by the UN Office of Information and Communications Technology (OICT)\, the 2025  Reboot the Earth hackathons are focused on agriculture and artificial intelligence (AI). The California event will focus on the locally relevant challenges of wildfire detection\, response\, and impact. Participants can leverage open source\, AI\, and open data sets\, along with local expertise on the environment and emergency preparedness and response. The goal is to build solutions that can become a digital public good\, serving local community needs. \nUC Santa Cruz students interested in attending the event can take advantage of the Silicon Valley Connector shuttle\, which will be running on Saturday\, November 8\, in addition to the regular Friday schedule. \nTo learn more about the Reboot the Earth initiative\, visit: https://unite.un.org/en/reboot-earth.
URL:https://events.ucsc.edu/event/un-reboot-the-earth-hackathon/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Meetings & Conferences,Social Gathering
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251030T140000
DTEND;TZID=America/Los_Angeles:20251030T150000
DTSTAMP:20260430T164658
CREATED:20251028T190921Z
LAST-MODIFIED:20251028T190921Z
UID:10005011-1761832800-1761836400@events.ucsc.edu
SUMMARY:Human Acceptance of Autonomous Systems
DESCRIPTION:Speaker: Sina Nordhoff\, Postdoctoral Researcher\, Institute of Transportation Studies at UC Davis.\nTitle: Human Acceptance of Autonomous Systems.\nTime: Thursday\, Oct 30th\, 2025\, 2:00-3:00 pm.\nLocation: E2-506 or Zoom. \nAbstract: This seminar explores how society engages with autonomous transportation systems\, focusing on automated vehicles and Advanced Air Mobility (AAM). Dr. Sina Nordhoff will present research on human acceptance\, trust\, and safety\, emphasizing that public confidence and social readiness are essential alongside technological progress. Drawing on theoretical models\, real-world applications\, and extensive empirical data\, including over 220 interviews and 40\,000 surveys\, Dr. Nordhoff will identify key factors shaping acceptance\, such as socio-demographics\, personality traits\, perceived risks and benefits\, and the effects of misuse or miscalibrated trust. The seminar will highlight how ethical considerations\, societal norms\, and regulatory frameworks influence deployment. Attendees will gain insight into how this work can guide policymakers\, industry\, and communities in ensuring responsible\, equitable\, and safe implementation. Dr. Nordhoff will also briefly discuss future research directions. \nSpeaker Bio: Dr. Sina Nordhoff is a leading expert in the field of human factors and user acceptance of new and emerging transportation technologies. She holds a Ph.D. from Delft University of Technology and is affiliated with the University of California\, Davis. Dr. Nordhoff specializes in electric vehicles and automated vehicles (AVs)\, focusing on how to responsibly integrate these innovations into society. Her research spans theoretical models\, empirical studies\, and real-world applications\, involving over 220 interviews and 40\,000 analyzed surveys. She has developed innovative frameworks to understand human acceptance\, trust\, and safety\, addressing critical issues such as misuse\, trust miscalibration\, and cyber-physical attacks. Dr. Nordhoff’s research is published in top-tier journals and has garnered significant attention from policymakers and industry leaders. Her work aims to inform the design\, deployment\, and regulation of these technologies to ensure they are safe\, equitable\, and socially beneficial. Dr. Nordhoff’s current research agenda includes pioneering efforts in interdisciplinary theory development\, safety assessment\, and understanding cognitive measurements. Her overarching goal is to bridge the gap between technological advancements and societal well-being\, creating a future where transportation benefits all members of society.
URL:https://events.ucsc.edu/event/human-acceptance-of-autonomous-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/10/Sina-Nordhoff-web.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251028T100000
DTEND;TZID=America/Los_Angeles:20251028T120000
DTSTAMP:20260430T164658
CREATED:20251024T173428Z
LAST-MODIFIED:20251024T173853Z
UID:10005004-1761645600-1761652800@events.ucsc.edu
SUMMARY:Alatawi\, A. (ECE) - Learning-Based Channel Estimation for Next-Generation Wireless Communications
DESCRIPTION:Accurate Channel State Information (CSI) is critical for coherent detection\, equalization\, and adaptive resource allocation in modern wireless systems. Traditional estimators rely on stationary statistical models\, and many learning-based methods assume training and deployment conditions are matched. In practice\, these assumptions break down under user mobility and environmental dynamics\, leading to degraded performance. This proposal explores machine-learning approaches for channel estimation that address two complementary challenges. \nFirst\, we develop an adaptive deep neural network (ADNN) for single-input single-output links over slowly time-varying channels. The method converts readily available physical-layer feedback—cyclic redundancy check (CRC) and automatic repeat request (ARQ)—into reliable self-supervision. Specifically\, packets decoded without errors are re-estimated using least squares (LS) across all symbols to generate high-quality labels\, and the DNN weights are periodically updated online. This design eliminates the need for ground-truth labels at deployment and enables continual learning. Simulations show that the ADNN tracks distributional shifts and recovers near–linear minimum mean-square error (LMMSE) performance in both mean-square error (MSE) and symbol error rate (SER)\, whereas a fixed offline-trained DNN degrades as channel statistics change. \nSecond\, we propose a sequence-to-sequence LSTM estimator for orthogonal frequency-division multiplexing (OFDM). The model exploits both temporal and frequency correlation by taking LS pilot estimates from several previous OFDM blocks as input and reconstructing the full channel frequency response of the current block. Trained on realistic time-selective channels such as WINNER II\, the LSTM outperforms LS interpolation and recent super-resolution–based methods across a wide range of SNRs\, pilot densities\, and temporal window sizes. \nFinally\, the proposal outlines future research on semantic-aware channel estimation using CSI timeliness\, and enhanced sequence models with DNN-refined pilots\, whole-block inputs\, and efficient GRU architectures. \nEvent Host: Abdulaziz Alatawi\, Ph.D. Student\, Electrical & Computer Engineering \nAdvisor: Hamid Sadjadpour & Zouheir Rezki \nZoom- https://ucsc.zoom.us/j/94895993579?pwd=Bs1ppmjqFvNknefRAHoVGXPSXxdZ6i.1 \nPasscode- 884927
URL:https://events.ucsc.edu/event/alatawi-a-ece-learning-based-channel-estimation-for-next-generation-wireless-communications/
CATEGORIES:Ph.D. Presentations
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/10/option-3-1.png
LOCATION:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251023T140000
DTEND;TZID=America/Los_Angeles:20251023T150000
DTSTAMP:20260430T164658
CREATED:20251017T183348Z
LAST-MODIFIED:20251017T183421Z
UID:10004909-1761228000-1761231600@events.ucsc.edu
SUMMARY:Robots that Know What They Do Not Know: Assured AI-enabled Autonomy in Unknown Environments
DESCRIPTION:Speaker: Yiannis Kantaros\, Assistant Professor\, Electrical and Systems Engineering at WashU in St. Louis. \nTitle: Robots that Know What They Do Not Know: Assured AI-enabled Autonomy in Unknown Environments. \nTime: Thursday\, Oct 23rd\, 2025\, 2:00-3:00 pm. \nLocation: E2-553 or Zoom. \nAbstract: Designing robots that navigate unfamiliar environments to execute natural language (NL) commands is a cornerstone of advanced embodied intelligence. While recent AI-enabled architectures have made impressive empirical progress\, they often lack introspection\, leading to systems that act with unwarranted confidence\, unaware of their own limitations or whether they have successfully completed their tasks. As a result\, these systems offer limited performance and safety guarantees\, restricting their deployment in safety-critical settings.\nIn this talk\, I will present an introspective\, neuro-symbolic autonomy architecture that enables robots to complete NL tasks in unknown environments with assurance guarantees by explicitly quantifying their own uncertainty using uncertainty quantification (UQ) tools. The neural component employs large language models (LLMs) to translate NL commands into temporal logic specifications\, while leveraging conformal prediction\, a UQ tool\, to calibrate and quantify prediction uncertainty arising from LLM imperfections and potential NL ambiguity. When uncertainty exceeds user-defined thresholds\, uncertainty-aware feedback is solicited from auxiliary LLMs—or\, if necessary\, from human operators. We provide theoretical guarantees\, supported by empirical case studies\, that the proposed uncertainty-aware translation framework\, called ConformalNL2LTL\, achieves user-specified translation success rates under certain distributional settings. The symbolic component generates plans for mobile robots with AI-enabled perception systems to satisfy temporal logic tasks while explicitly reasoning over perceptual and environmental uncertainty. This allows robots to decide when to proceed confidently and when to actively gather additional sensor data\, ensuring task completion with the desired probability. Notably\, the developed planners are agnostic to specific sensor models or noise characteristics. The talk will conclude with case studies and demonstrations\, followed by a discussion of limitations and open problems. \nSpeaker Bio: Yiannis Kantaros is an Assistant Professor in the Department of Electrical and Systems Engineering\, Washington University in St. Louis (WashU)\, St. Louis\, MO\, USA. He earned a Diploma in Electrical and Computer Engineering in 2012 from the University of Patras\, Greece\, and M.Sc. and Ph.D. degrees in Mechanical Engineering from Duke University\, Durham\, NC\, in 2017 and 2018\, respectively. Prior to joining WashU\, he was a postdoctoral associate in the Department of Computer and Information Science\, University of Pennsylvania\, Philadelphia\, PA. His current research interests include machine learning\, distributed control and optimization\, and formal methods with applications in robotics. He received the Best Student Paper Award at the 2nd IEEE Global Conference on Signal and Information Processing (GlobalSIP) in 2014 and was a finalist for the Best Multi-Robot Systems Paper at the IEEE International Conference on Robotics and Automation (ICRA) in 2024 and a finalist for the Best Paper Award at the ACM/IEEE International Conference on Cyber-physical Systems (CPSWeek-ICCPS) in 2025. He also received the 2017-18 Outstanding Dissertation Research Award from the Department of Mechanical Engineering and Materials Science at Duke University and a 2024 NSF CAREER Award.
URL:https://events.ucsc.edu/event/assured-ai-enabled-autonomy-in-unknown-environments/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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SUMMARY:CITRIS Aviation Prize Information Session
DESCRIPTION:Join us for this virtual info session on the 2025–26 CITRIS Aviation Prize\, an exciting multi-campus student competition inviting teams to design innovative solutions for the future of air mobility across the University of California. \nThe session will cover this year’s competition guidelines\, key dates and requirements\, and available resources. Attendees will also have the opportunity for Q&A with members of the CITRIS Aviation Leadership Committee\, composed of aviation research faculty from UC Berkeley\, UC Davis\, UC Merced\, and UC Santa Cruz. \nRegister here to attend. \nFor any questions\, contact aviationprize@citris-uc.org. \n  \nDate: Tuesday\, October 21 \nTime: 12:00 pm – 1:00 pm \nLocation: Zoom (register to attend).
URL:https://events.ucsc.edu/event/citris-aviation-prize-info/
CATEGORIES:Meetings & Conferences
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DTSTART;TZID=America/Los_Angeles:20251015T110000
DTEND;TZID=America/Los_Angeles:20251015T110000
DTSTAMP:20260430T164658
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SUMMARY:2025 Fall STEM Career & Internship Fair
DESCRIPTION:Here is a chance to meet tech recruiters in person! \nIf you are interested in pursuing a career in science\, technology\, engineering\, mathematics or research\, then take advantage of this opportunity to meet recruiters from companies looking to fill various positions (both technical and non-technical). Learn more about internships and full-time career opportunities. Undergraduate students\, graduate students\, and recent alumni are all welcome to attend! \nPLEASE NOTE: You are encouraged to check in at the student registration table in order to participate in the career fair. Bring your student ID. \nWant more support? \n\nVisit a peer coach during drop-in hours\nSchedule a career coaching appointment with a Career Engagement Specialist\nFor PhD students looking to pursue careers in industry\, explore Beyond the Professoriate\n	(Scroll over "Login to Platform" at the top navigation bar and click "Through your institution")\nGet career tips on demand from our Career Success YouTube video library\nStay in the loop by following Career Success on Instagram\n\nYou will receive registration and additional information in your email from Career Success via Handshake. Please make sure to check your junk/spam folder if you are not receiving any communication.\n  \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. \nQuestions? Send to csuccess@ucsc.edu or visit Career Success at Hahn 125 East Entrance\nNeed accessibility support? Let us know at slugtalent@ucsc.edu at least two weeks prior to the fair date.
URL:https://events.ucsc.edu/event/2025-fall-stem-career-internship-fair/
LOCATION:Stevenson Event Center\, Stevenson Service Road\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
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