School of Engineering
Showing 151-200 of 211 Results
-
Zhuo Zheng
Postdoctoral Scholar, Computer Science
BioMy research interests are Earth Vision and AI4Earth, especially multi-modal and multi-temporal remote sensing image analysis and their real-world applications.
First-author representative works:
- Our Change family: ChangeStar (single-temporal learning, ICCV 2021), ChangeMask (many-to-many architecture, ISPRS P&RS 2022), ChangeOS (one-to-many architecture, RSE 2021), Changen (generative change modeling, ICCV 2023)
- Geospatial object segmentation: FarSeg (CVPR 2020) and FarSeg++ (TPAMI 2023), LoveDA dataset (NeurIPS Datasets and Benchmark 2021)
- Missing-modality all weather mapping: Deep Multisensory Learning (first work on this topic, ISPRS P&RS 2021)
- Hyperspectral image classification: FPGA (first fully end-to-end patch-free method for HSI, TGRS 2020) -
Shiyuan Zhou
Postdoctoral Scholar, Materials Science and Engineering
BioShiyuan Zhou is a recipient of the 2026 Stanford Energy Postdoctoral Fellowship. He received his Ph.D. in Energy Chemistry in 2024 through a joint doctoral program between Xiamen University and Argonne National Laboratory, under the supervision of Prof. Shi-Gang Sun, Dr. Gui-Liang Xu, and Dr. Khalil Amine.
His research advances the frontiers of battery chemistry through the development of multimodal operando electrochemical scanning/transmission electron microscopy (EC-S/TEM) integrated with synchrotron X-ray characterization, enabling direct observation of real-time electrochemical and structural dynamics in energy materials. Trained as both a materials chemist and microscopist, his work focuses on visualizing highly sensitive and previously inaccessible electrochemical processes in batteries.
During his doctoral research, he developed in situ liquid-cell transmission electron microscopy techniques to probe real-time reaction dynamics in lithium–sulfur batteries. Following his Ph.D., he continued at Argonne as a postdoctoral fellow, where he expanded his research to multimodal and multiscale imaging approaches, integrating advanced electron microscopy with transmission X-ray microscopy to study all-solid-state batteries. His research has been recognized as one of China’s Top 10 Scientific Advances of 2023, and he has received the Tan Kah Kee Medal as well as the Argonne Impact Award. -
Yihong Zhu
Ph.D. Student in Aeronautics and Astronautics, admitted Summer 2025
Current Research and Scholarly InterestsReduction Order Modeling, Fluid Mechanics, Applied Mathematics
-
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!
-
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.