School of Engineering
Showing 1,101-1,163 of 1,163 Results
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Yanjie Ze
Ph.D. Student in Computer Science, admitted Autumn 2024
BioYanjie Ze is a PhD student of Computer Science at Stanford University. His research centers around building intelligence for general-purpose robots. He has published several papers with Oral Presentation/Spotlight on top-tier conferences such as RSS, CoRL, IROS, and ICLR. His personal website: https://yanjieze.com
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Mayshu (Meixu) Zhan
Ph.D. Student in Modern Thought and Literature, admitted Autumn 2023
Ph.D. Minor, Communication
Ph.D. Minor, Computer ScienceCurrent Research and Scholarly InterestsMy interdisciplinary research examines digital media through the lens of critical race, gender, and sexuality studies. I am primarily interested in investigating how we can leverage the power of media to reinvent and promote social equality. Specifically, my research focuses on digital games and their prosocial influence on 21st- century China.
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Xingyuan Zhang
Ph.D. Student in Chemistry, admitted Autumn 2023
Ph.D. Minor, Computer ScienceBioPhD candidate in Chemistry and Computer Science, affiliated with the Wu Tsai Neurosciences Institute and the ChEM-H Institute at Stanford. Investigating the molecular mechanisms underlying chronic diseases, cancer and fibrosis, with interest on applying ML/DL approaches to drug discovery and disease modeling.
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Richard Zhuang
Masters Student in Computer Science, admitted Autumn 2025
BioI’m broadly interested in understanding and improving the capabilities of Large Language Models (LLMs) in a data-centric way. Specifically, I’m intrigued by how certain data “foster” skills that are essential for LLM agents (e.g. reasoning and planning). I have also had a long-standing passion in Sports Analytics. Outside the realm of AI, you will usually find me playing basketball!
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Orr Zohar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Masters Student in Computer Science, admitted Autumn 2023BioOrr Zohar is a PhD candidate in Electrical Engineering at Stanford University and a Knight-Hennessy Scholar. He builds large-scale multimodal foundation models - spanning data curation, pretraining, and post-training - with a focus on video understanding, long-horizon reasoning, and robust transfer under real-world distribution shift. His work includes open-source model and dataset efforts and methods for evaluation and alignment of multimodal systems, with an emphasis on turning research into deployment-ready learning systems.
Before Stanford, he earned a BSc in Chemical Engineering (summa cum laude) and an MSc in Electrical Engineering from the Technion–Israel Institute of Technology, and worked as a machine learning and algorithms engineer at proteanTecs. Earlier research experiences include applied sensing and medical-imaging work.
