Stanford University
Showing 31-40 of 53 Results
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Anders Gjølbye Madsen
Graduate Visiting Researcher Student, Computer Science
BioAnders Gjølbye Madsen is a PhD fellow at the Technical University of Denmark. His research focuses on trustworthy machine learning for healthcare, with an emphasis on explainability, interpretability, and reliable evaluation of models in high-stakes settings. He works broadly with modern deep learning methods, including self-supervised learning, and is interested in questions of robustness and alignment. He is the author of PatternLocal, a NeurIPS 2025 paper on reducing false-positive attributions in explanations of non-linear models by refining local explanation approaches. He earned a BSc in Artificial Intelligence and Data from DTU and completed an MSc in Engineering in Applied Mathematics at DTU, including a study exchange in Computational Science and Engineering at ETH Zürich. Anders will spend 2026 as a visiting researcher at Stanford University’s Trustworthy AI Research (STAIR) Lab, working with Professor Sanmi Koyejo.
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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.
