Yuanyuan Wei

University of California, Department of Neurology

<p>Dr. Yuanyuan Wei is a Postdoctoral Scholar in the Department of Neurology at the David Geffen School of Medicine at the University of California, Los Angeles (UCLA). She received her PhD in biomedical engineering from The Chinese University of Hong Kong in 2023. She received her B.Eng. degree in precision instrumentation from Tsinghua University in 2018. Her interdisciplinary research integrates artificial intelligence, computational biology, and biomedical engineering to advance therapeutic discovery, molecular diagnostics, and quantitative bioanalysis. Her recent work focuses on protein structure-guided AI drug discovery, computer vision for digital diagnostics, and closed-loop computation-experimental platforms that combine computational prediction with biological validation.</p><p><br></p><p>Dr. Wei has published 22 peer-reviewed publications in high-impact journals, including <em>Advanced Science</em>, <em>Chemical Society Reviews</em>, <em>Small Methods</em>, and <em>Biosensors and Bioelectronics</em>, and currently serves as a reviewer for multiple international journals. Her research seeks to establish autonomous, closed-loop AI systems that accelerate biomedical discovery and translation.</p>

Zhaoyu Liu

University of California San Diego

<p>Zhaoyu Liu is a PhD student at the University of California, San Diego. He graduated with a Bachelor of Engineering (B.Eng.) in Biomedical Engineering from The Chinese University of Hong Kong and earned his master's degree from Johns Hopkins University. His research focuses on brain probes and neural interface technologies, particularly the design, fabrication, and application of implantable devices to record and modulate neural activity. He is interested in developing high-performance brain probe systems that support basic neuroscience research as well as future biomedical applications. His broader academic interests include microfabrication, bioelectronics, neuroengineering, and the integration of advanced materials with neural devices.</p>

Jingjie (Ethan) Ning

Carnegie Mellon University, School of Computer Science

<p>Jingjie is a student in the School of Computer Science at Carnegie Mellon University. His research focuses on AI for science, particularly the development of automated research and agentic AI methods that support scientific discovery, hypothesis generation, experimental planning, and evidence-based model improvement. His work explores how large language models, retrieval-augmented generation, agentic search, and multi-agent reasoning can be applied to scientific research workflows, including biomedical discovery, cheminformatics, and computational science. At CMU, he has contributed to research on Deep Research evaluation, neural retrieval, and automated scientific reasoning systems over large-scale corpora. He has also worked on drug–GPCR interaction prediction and interpretable AI models for molecular and protein data. Prior to CMU, he worked as a senior data scientist at Tencent.</p>