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  • ICLR 2026 Workshop: Principled Design for Trustworthy AI – Interpretability, Robustness, and Safety across Modalities

    International Conference on Learning Representations (ICLR)

    Modern AI systems, particularly large language models, vision-language models, and deep vision networks, are increasingly deployed in high-stakes settings such as healthcare, autonomous driving, and legal decisions. Yet, their lack of transparency, fragility to distributional shifts between train/test environments, and representation misalignment in emerging tasks and data/feature modalities raise serious concerns about their trustworthiness. This […]

  • TILOS-HDSI Seminar with Ellen Vitercik (Stanford)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Ellen Vitercik is an Assistant Professor at Stanford with a joint appointment between the Management Science and Engineering department and the Computer Science department. Her research interests include machine learning, algorithm design, discrete and combinatorial optimization, and the interface between economics and computation. Before joining Stanford, Dr. Vitercik was a Miller […]