using https://events.vtools.ieee.org/meetings/xml/0/90/asc/6/OREGON
19099 bytes
2 meetings
- Title:
- SusTech Talk March 2026 - Sand-Like Particles for High-Temperature Thermal Energy Storage
- Date:
- March 3rd
6:00 PM (1 hour) - Abstract:
- “Sand-Like Particles for High-Temperature Thermal Energy Storage: Enabling a Resilient Renewable Energy Future”
with Shin Young Jeong, faculty member of the Center for Advanced Turbomachinery and Energy Research, University of Central Florida.
Date/Time: Tuesday, March 3, 6pm - 7 pm Pacific Time
Abstract:
The transition to renewable energy has increased the need for reliable, large-scale storage to balance intermittent generation with continuous demand. Thermal energy storage (TES) offers a cost-effective solution by capturing excess energy as heat and releasing it when needed, supporting long-duration storage and grid stability. Unlike batteries, TES can scale to industrial levels, provide process heat, and deliver electricity through power cycles. Recent advances use abundant, low-cost materials such as sand-like particles serving as both heat transfer media and storage. This talk will highlight emerging TES technologies and their role in a resilient, decarbonized energy future.
- Title:
- IEEE SSCS Oregon Chapter March Meeting and Seminar (Hybrid)
- Date:
- March 27th
11:00 AM (1 hour) - Location:
- Jones Farm Conference Center
Hillsboro - Abstract:
IEEE SSCS Oregon Chapter November Meeting and Seminar
Join us for a talk from SSCS Distinguished Lecturer Prof. Vanessa Chen from Carnegie Mellon University on Friday, March 27th, 2026. The seminar will be held from 11:00am to 12:00pm (PST) via a Hybrid format. Please register for the meeting link and information.
Topic:
AI-Enhanced RF/Mixed-Signal Circuits for Reliable Operations
Abstract:
AI-driven design and optimization are revolutionizing RF and mixed-signal circuits for operation in extreme environments, including high radiation and wide temperature ranges. This talk explores the use of reinforcement learning (RL) and generative models to improve circuit robustness and adaptability. RL-based self-healing techniques leverage embedded electromagnetic sensors for real-time monitoring and dynamic fault recovery, while generative models accelerate design space exploration, enabling resilient and efficient circuit topologies. The presentation will highlight AI-enhanced designs such as adaptive power amplifiers, PMICs, and multispectral sensors that enhance performance and reliability in harsh environments.
Speaker Biography:
Vanessa Chen received her Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2013, where she worked on energy-efficient, ultra-high-speed ADCs with real-time calibration and interned at IBM T. J. Watson Research Center. She previously held circuit design roles at Qualcomm in San Diego and Realtek in Taiwan, focusing on self-healing RF and mixed-signal circuits. Her research explores AI-enhanced circuits and systems, including intelligent sensory interfaces, RF/mixed-signal hardware security, and ubiquitous sensing and computing. Dr. Chen is a recipient of the NSF CAREER Award, the CMU College of Engineering Dean’s Early Career Fellowship, Apple NSI Faculty Fellow, and the IBM PhD Fellowship. She has served on program committees for ISSCC, VLSI Symposium, CICC, A-SSCC, and DAC, as an Associate Editor for several IEEE journals, and is currently an IEEE SSCS Distinguished Lecturer for 2025–2026.
2 meetings. Generated Tuesday, February 24 2026, at 6:11:57 PM. All times America/Los_Angeles