Chalmers AI Talks are inspiring seminars at Chalmers University of Technology from internationally acclaimed experts on artificial intelligence. Come listen to world-renowned leaders in computer science, machine learning and statistics discuss on a wide range of perspectives on how AI will affect research, business and society. AI Talks are organized by Devdatt Dubhashi, Fredrik Johansson, Fredrik Kahl and Umberto Picchini and supported by Chalmers AI Research Centre (CHAIR) and AI Sweden.

AI Talks are held on Zoom and/or in-person at Chalmers University of Technology and recordings are uploaded to YouTube. You can participate in the Zoom meeting by registering for the talk; for YouTube viewing, no registration is needed. If you would like to be notified of future events, please subscribe to our mailing list.

Previous talks can be found on the CHAIR YouTube Channel

Upcoming talks

  • Francisco J. R. Ruiz

    Nov 3, 2022, 10:00 (Swedish time)

    Location: ED (Chalmers) & Zoom

    Local host: Lennart Svensson

    Title: Discovering novel algorithms with AlphaTensor

    Francisco J. R. Ruiz is a Research Scientist working at DeepMind in the Deep Learning Team. His research is focused on probabilistic modeling and inference, generative models, and applications of machine learning in mathematics.

    Register for Zoom details here

Previous talks

  • Xiao-Li Meng

    Oct 17, 2022

    Title: A Multi-resolution Theory for Approximating Infinite-p-Zero-n: Transitional Inference, Individualized Predictions, and a World Without Bias-Variance Tradeoff​

    Xiao-Li Meng is the Whipple V. N. Jones Professor of Statistics in the Faculty of Arts & Sciences at Harvard University.

    » Watch recording here
  • Sandeep Juneja

    Jun 2, 2022

    Title: Shift, Scale and Restart Smaller Models to Estimate Larger Ones: Agent-based Simulators in Epidemiology

    Sandeep Juneja is a Senior Professor in the School of Technology and Computer Science at the Tata Institute of Fundamental Research, in Mumbai. His research interests lie in applied probability including in sequential learning, mathematical finance, Monte Carlo methods, and game theoretic analysis of queues.

  • Susan Athey

    May 10, 2022

    Title: AI for Social Impact: Applications and Opportunities

    Susan Athey is The Economics of Technology Professor at Stanford Graduate School of Business. Her research focuses on the economics of digitization, marketplace design, and the intersection of econometrics and machine learning.

    » Watch recording here
  • Pushmeet Kohli

    Apr 27, 2022

    Title: Leveraging AI for Science

    Pushmeet Kohli leads the AI for Science team at Google DeepMind which aims to leverage AI and ML techniques to accelerate progress on important scientific challenges. The team conducts research in many areas of Science and has made contributions in structural biology (protein folding), quantum chemistry, genomics and pure mathematics.

    » Watch recording here
  • Susan Murphy

    Jan 19, 2022

    Title: We used Reinforcement Learning; but did it work?​

    Susan A. Murphy is the Mallinckrodt Professor of Statistics and of Computer Science, Radcliffe Alumnae Professor at the Radcliffe Institute. She leads the Statistical Reinforcement Learning Lab working on the development of data analytic algorithms and methods for informing sequential decision making in health.

    » Watch recording here
  • Cynthia Rudin

    Dec 8, 2021

    Title: Interpretable Machine Learning

    Cynthia Rudin is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics & bioinformatics at Duke University, and directs the Interpretable Machine Learning Lab. She was recently awarded the AAAI Squirrel AI Award or pioneering socially responsible AI.

    » Watch recording here
  • Martin Danelljan

    Oct 20, 2021

    Title: Deep Visual Reasoning with Optimization-based Network Modules

    Martin Danelljan is a senior researcher at ETH Zürich, Switzerland. He received his Ph.D. degree from Linköping University, Sweden in 2018. His Ph.D. thesis was awarded the biennial Best Nordic Thesis Prize at SCIA 2019. His main research interests are meta and online learning, deep probabilistic models, and conditional generative models.

    » Watch recording here
  • Madhav Marathe

    Mar 11, 2021

    Title: Vaccine prioritization: The role of AI and computing in pandemic planning and response

    Madhav Marathe is a Distinguished Professor in Biocomplexity, the division director of the Network Systems Science and Advanced Computing Division at the Biocomplexity Institute and Initiative, and a Professor in the Department of Computer Science at the University of Virginia (UVA).

    » Watch recording here
  • Mihaela van der Schaar

    Feb 17, 2021

    Title: Why medicine is creating exciting new frontiers for machine learning

    Mihaela van der Schaar is John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Turing Fellow at The Alan Turing Institute in London. ​

    » Watch recording here » Slides
  • Kerrie Mengersen

    Feb 3, 2021

    Title: Calling all Citizen Scientists: using Bayesian Statistics to advance public input into scientific analysis

    Kerrie Mengersen is a Distinguished Professor in Statistics at the Queensland University of Technology in Brisbane, Australia. She is the Deputy Director of the Australian Research Council Centre of Excellence in Mathematical Frontiers and the Director of the QUT Centre for Data Science.

    » Watch recording here
  • Michael I. Jordan

    Dec 17, 2020

    Title: The Decision-Making Side of Machine Learning: Computational, Inferential and Economic Perspectives

    Michael Irwin Jordan is a professor at the University of California, Berkeley and researcher in machine learning, statistics, and artificial intelligence. He is one of the leading figures in machine learning, and in 2016 Science reported him as the world's most influential computer scientist.

    » Watch recording here
  • Nicolo Cesa-Bianchi

    Nov 26, 2020

    Title: Cooperation in networks of learning agents

    Nicolo Cesa-Bianchi is a professor of Computer Science in the Department of Computer Science and the Data Science Research Centre of University of Milan. He is currently head of the Computer Science programs. His main research interest is the design and analysis of machine learning algorithms, with special emphasis on sequential learning problems.

    » Watch recording here
  • Bill Dally

    Nov 20, 2020

    Title: Domain-Specific Accelerators

    Bill Dally is Professor (Research) of Computer Science and of Electrical Engineering at the Department of Computer Science at the Stanford University and Chief Scientist at Nvidia.

  • Aravind Srinivasan

    Nov 12, 2020

    Title: Fairness in AI and in Algorithms

    Aravind Srinivasan is a Distinguished University Professor of the University of Maryland. He is an elected Fellow of six professional societies: ACM, IEEE, AMS, AAAS, EATCS, and SIAM. His research interests include algorithms, combinatorial optimization and their interface with machine learning.​​​​

  • Arthur Gretton

    Oct 14, 2020

    Title: Critics for generative adversarial networks: results and conjectures

    Arthur Gretton is Professor with the Gatsby Computational Neuroscience Unit, and director of the Centre for Computational Statistics and Machine Learning at UCL. His research interests include the design and training of generative models, both implicit (e.g. GANs) and explicit (high/infinite dimensional exponential family models), nonparametric hypothesis testing, and kernel methods.

    » Watch recording here » Slides
  • Barbara Plank

    Oct 1, 2020

    Title: Learning across Adverse Conditions in Natural Language Processing

    Barbara Plank is Associate Professor of Natural Language Processing (NLP) in the Computer Science Department at ITU (IT University of Copenhagen) where she leads a research lab in natural language processing.​​​

    » Watch recording here
  • Thomas Schön

    Jun 18, 2020

    Title: AI for researc​h and some new results on deep regression

    Thomas B. Schön is Professor of the Chair of Automatic Control in the Department of Information Technology at Uppsala University, and has recently been appointed Beijer Professor of Artificial Intelligence at the same university.

    » Watch recording here