School of Engineering
Showing 6,001-6,100 of 6,507 Results
-
Theodora Worledge
Ph.D. Student in Computer Science, admitted Autumn 2022
BioTheodora (Teddi) Worledge is a PhD student in Computer Science at Stanford University, where she works on making machine learning models more reliable and trustworthy. Her research focuses on developing interpretability and attribution tools that help users verify and understand language model outputs. She is advised by Carlos Guestrin and supported by the NSF Graduate Research Fellowship. Before Stanford, she earned her BA in Computer Science from UC Berkeley.
-
Jiajun Wu
Assistant Professor of Computer Science and, by courtesy, of Psychology
BioJiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, robotics, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, the Okawa research grant, the AI's 10 to Watch by IEEE Intelligent Systems, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, ICRA, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from Google, J.P. Morgan, Samsung, Amazon, and Meta.
-
Katie Wu
Ph.D. Student in Environment and Resources, admitted Autumn 2022
Ph.D. Minor, Civil and Environmental EngineeringBioKatie's research explores how community-driven social interventions and infrastructure development impact community and climate resilience in informal settlements. Her work advances how we operationalize resilience to better inform community-based strategies, policy, and investments that support urban transformation for vulnerable populations. She incorporates participatory methods essential for driving community-led efforts, ensuring a community's deep participation in every step of the iterative analysis, planning, and decision-making processes, in collaboration with multi-sectoral partners and decision-makers. Katie integrates advanced data science techniques, including network science and graph neural networks (GNNs), with community-generated, ground-truthed data to redefine how resilience is measured and applied for more equitable, community-driven strategies for sustainable development. She uses unconventional data sources, such as satellite imagery and citizen-sourced data, to model the built and natural environment in areas with limited conventional data.
Prior to Stanford, Katie studied data science and AI for Product Innovation at Duke University, where she obtained a Master of Engineering Management (MEM). She was a Sustainability Graduate Intern at Lyft, Inc., where she completed and rebuilt their 2020 Greenhouse Gas (GHG) Inventory and Report and designed an air quality model forecasting potential health benefits of EV adoption for underserved communities. She received an M.S. in Medical Science from the University of Colorado School of Medicine and a B.S. in Animal Science with Distinction in Research from Cornell University. Katie is a Dean's Graduate Scholar in the Doerr School of Sustainability, an Emerson Consequential Scholar with the Stanford Technology Ventures Program (STVP), a Graduate Fellow at the Stanford Institute for Human-Centered AI (HAI), and a Stanford Dalai Lama Fellow. -
Min Wu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsResponsible AI, AI safety, trustworthy AI, robustness, explainability and interpretability.
Formal methods, automated verification, verification of deep neural networks, formal explainable AI. -
Tiange Xiang
Ph.D. Student in Computer Science, admitted Autumn 2022
BioTiange Xiang is a Ph.D. student in Computer Science at Stanford University, where he is a member of the Stanford AI Lab (SAIL) and Stanford Vision and Learning Lab (SVL). His research interests include machine learning and computer vision in general. He received a bachelor's degree in Computer Science and Technology (Advanced)(Honors) from the University of Sydney, where he was awarded Honors Class I and the University Medal.
-
Chenghan Xie
Ph.D. Student in Management Science and Engineering, admitted Autumn 2024
Current Research and Scholarly InterestsOptimization, theory & practice. Energy-aware AI, nerual-network structure & data center management.
-
Peter Xie
Ph.D. Student in Mechanical Engineering, admitted Autumn 2023
BioResearch:
Engineer developing hydrogels for cancer immunotherapies -
Lei Xing
Jacob Haimson and Sarah S. Donaldson Professor and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly Interestsartificial intelligence in medicine, medical imaging, Image-guided intervention, molecular imaging, biology guided radiation therapy (BGRT), treatment plan optimization
-
熊剑 (Jian Xiong)
Postdoctoral Scholar, Chemical Engineering
BioI thrive to understand the roles of lysosomes in physiological and pathological conditions. Lysosomes are both degradation compartment and metabolic controlling hub, and dysregulation of lysosomal functions are frequently implicated in a vast number of diseases including neurodegenerative diseases, however, the systematic knowledge of the molecular mechanism by which lysosomal contributes to these diseases is lacking. Ion channels are the primary mediators of neuronal activity, defects in neuronal ion channel activity are linked with many kinds of neurodegenerative diseases. Interestingly, besides typical ion channels that are involved in the neuronal activity, defects in lysosomal ion channels, such as TRPML1, CLN7 and CLC-7 are also implicated in neuropathy. My previous work as Ph.D student in University of Texas MD Anderson Cancer Center focused on regulation of lysosomal function by ion channels and metabolites. I discovered a mechanism of lysosomal Na+ channel regulate mTORC1 activation by regulating lysosomal amino acid accumulation. I also discovered role of glutamine in controlling lysosomal degradation capacity. In the meantime, I developed novel methods to isolate organelles. My ultimate research goal is to understand the key developmental pathways and how alterations in gene sequences and expression contribute to human disease, therefore, I am pursuing independent academic researcher as my career goal. Starting Feb 2022, I work with Dr. Monther Abu-Remaileh at Stanford University on role of lysosomes in neurodegenerative diseases. I use genetics, chemical biology and omics approaches to study lysosome function under various physiological and pathological conditions, especially age-associated neurodegenerative disorders, and monogenic neurodegenerative lysosome storage diseases. In Stanford, I aim to integrate ionic regulation, metabolomic regulation and functional proteomic regulation to systematically understand the biology of lysosome in physiological conditions and pathological conditions.
-
Kuang Xu
Associate Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical Engineering
BioKuang Xu is an Associate Professor of Operations, Information and Technology at Stanford Graduate School of Business, and Associate Professor by courtesy with the Electrical Engineering Department, Stanford University. Born in Suzhou, China, he received the B.S. degree in Electrical Engineering (2009) from the University of Illinois at Urbana-Champaign, and the Ph.D. degree in Electrical Engineering and Computer Science (2014) from the Massachusetts Institute of Technology.
His research primarily focuses on understanding fundamental properties and design principles of large-scale stochastic systems using tools from probability theory and optimization, with applications in queueing networks, healthcare, privacy and machine learning. He received First Place in the INFORMS George E. Nicholson Student Paper Competition (2011), the Best Paper Award, as well as the Kenneth C. Sevcik Outstanding Student Paper Award at ACM SIGMETRICS (2013), and the ACM SIGMETRICS Rising Star Research Award (2020). He currently serves as an Associate Editor for Operations Research and Management Science. -
Kun Xu
Postdoctoral Scholar, Mechanical Engineering
Current Research and Scholarly InterestsMaterials characterization by using advanced electron microscopy
-
Pei Xu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly Interestscharacter animation, physics-based character control, crowd simulation
-
Renyuan Xu
Assistant Professor of Management Science and Engineering
BioRenyuan Xu is an assistant professor of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she held positions at New York University (2024-2025) and the University of Southern California (2021–2024), and was a Hooke Research Fellow at the Mathematical Institute, University of Oxford (2019–2021). She received her Ph.D. in Operations Research from the University of California, Berkeley in 2019. Renyuan's current research interests include mathematical finance, stochastic analysis, stochastic controls and games, and machine learning theory. She received an NSF CAREER Award in 2024, the SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize in 2023, and two JP Morgan AI Faculty Research Awards in 2022 and 2025.
