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Published in Design Automation Conference (DAC), 2026
This paper presents EPIC, a hardware- and physics-co-guided distributed SciML framework for full-waveform inversion. It explores how edge-side encoding and physics-aware decoding can reduce communication latency and energy while preserving physical fidelity.
Recommended citation: Yuchen Yuan, Junhuan Yang, Hao Wan, Yipei Liu, Hanhan Wu, Youzuo Lin and Lei Yang. (2026). "Two Teachers Better Than One: Hardware-Physics Co-Guided Distributed Scientific Machine Learning." Proceedings of the 63rd Design Automation Conference (DAC).
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Teaching certificate, Stearns Center for Teaching and Learning, George Mason University, 2025
Spring 2025 — Completed the Inclusive Teaching for STEM Graduate Students Mini-Course offered by the Stearns Center for Teaching and Learning at George Mason University.
Graduate courses, George Mason University, Department of Electrical and Computer Engineering, 2025
Fall 2025 — I served as a Graduate Teaching Assistant for three courses in the ECE department at George Mason University.
Graduate course, George Mason University, Department of Electrical and Computer Engineering, 2026
Spring 2026 — I served as the Recitation Instructor for ECE 528: Introduction to Random Processes, a graduate-level course in the ECE department at George Mason University.