Computer Science and Engineering Department

Presenter Chenyu You, Stony Brook University Abstract In the rapidly growing area of machine learning, there is profound promise in crafting intelligent, data-driven methods for diverse real-world applications. Yet, in safety-critical domains like healthcare, some fundamental challenges remain: (1) The insufficiency of raw biomedical data emphasizes the need for data-efficient and robust learning approaches. (2) […]

Presenter: Philipp Haller, KTH Royal Institute of Technology Abstract: Distributed programming is notoriously difficult. Not only are distributed systems concurrent, they pose additional challenges including data consistency and fault tolerance. At the same time, the share of software systems that are necessarily distributed systems is growing rapidly. As a result, too many software developers are […]

Presenters: Prof. Karl-Erik Arzen (Co-Director of WASP and Lund University), Dr. Paul Townend (WASP Graduate School management and Umeå University), and Carl Magnus Bruhner (Linkoping University) Abstract: The Wallenberg AI, Autonomous Systems, and Software Program (WASP) is the largest research initiative in Swedish history, with a budget of over $700M and a research focus AI […]

Presenter: Chris Jay Hoofnagle, Frederik Zuiderveen Borgesius, Lothar Determann, Pieter T.J. Wolters Abstract: The European Union has enacted a comprehensive cybersecurity framework (the “Framework”) that imposes far-reaching obligations on developers of standalone software and connected products. This Article describes the European legislative approach before turning to a description of the Framework. Anchored by the Cyber […]

Presenter: Arman Zharmagambetov, Meta Abstract: Ensuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rely on sequential adversarial training: […]