School of Engineering
Showing 21-40 of 48 Results
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Jing Liang
Postdoctoral Scholar, Computer Science
BioJing Liang is a postdoctoral scholar in the Department of Computer Science at Stanford University, where he is affiliated with the Stanford Robotics Center and the Stanford Center on Longevity. He received his Ph.D. in Computer Science from the University of Maryland, College Park.
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Jonas Ngnawe
Graduate Visiting Researcher Student, Computer Science
BioJonas Ngnawé is a visiting student researcher at the Stanford Trustworthy AI Research (STAIR) lab, led by Prof. Sanmi Koyejo. He is currently a Ph.D. candidate in Computer Science at Mila – Quebec AI Institute and Université Laval. With a background in Computer Engineering from Ecole Polytechnique Yaoundé (2016), he also holds master’s degrees in Mathematical Sciences from AIMS-African Institute for Mathematical Sciences (2017) and Machine Learning from AMMI-African Master's in Machine Intelligence funded by Meta and Google (2019). His research focuses on developing safe, efficient and trustworthy AI for high-stakes applications—such as transportation, finance and healthcare—with a particular focus on adversarial robustness and uncertainty estimation in deep learning models. Before beginning his Ph.D., Jonas was an AI Resident at Google.
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Alexander Spangher
Postdoctoral Scholar, Computer Science
BioAlexander Spangher is a post-doctoral researcher advised by Daniel Ho, Sanmi Koyejo and Diyi Yang. His research focuses on modeling human decision-making in creative domains, especially in contexts where data is limited and rewards and goals are less clear. He is building out a new domain of learning, called emulation learning, with the goal of training the next generation of reasoning-oriented language models to be more proficient in these domains. His research has been used at technology organizations like OpenAI, Google and EleutherAI. He is especially passionate about helping journalists and has framed tasks and trained reasoning LLMs to help journalists find stories and sources, structure narratives and track information updates. These tools have been incorporated into newsrooms at the New York Times, Bloomberg and Stanford Big Local News, impacting thousands of journalists; and his work is also informing the next generation of journalistic education at USC Annenberg. His work has received numerous awards including two outstanding paper awards at EMNLP 2024, one spotlight award at ICML 2024, one outstanding paper award at NAACL 2022 and a best paper award at CJ2023; and he has been supported by a 4-year Bloomberg PhD Fellowship. His work is broad: in addition to his work in NLP and computational journalism, he has studied misinformation at Microsoft Research and collaborated with the MIT Plasma Science and Fusion Center to model plasma fusion processes.
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Sanna Kaisa Wong Toropainen
Graduate Visiting Researcher Student, Computer Science
BioSanna Wong-Toropainen is an EU AI regulation expert and a visiting scholar at Stanford University, Graduate School of Education, SCANCOR. She is affiliated with the University of Helsinki, Faculty of Law and Legal Tech Lab, and she works at a research consortium exploring and designing trustworthy AI-enabled digital public infrastructures (Trust-M) funded by the Strategic Research Council of Finland. She is also a visiting Stanford University as a Visiting Researcher at SCANCOR. In her research, she examines the new data and AI-related laws, including the Digital Markets Act, Data Act and AI Act, and the construction of data-sharing ecosystems, also known as data spaces in the EU, as new legal infrastructures controlling the sharing and access to data. Her new book called 'The EU Data Regulations - Handbook to the Five New Acts' will be published in April 2025 by Edita Legal Publishing.
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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. -
Pei Xu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly Interestscharacter animation, physics-based character control, crowd simulation
