AI Keynotes Summer Semester 2022
Archive
Events*
| # | Date | Speaker | Topic |
|---|---|---|---|
| 1 | 05.05.2022, 12:00-13:30 | Nicolas Banholzer, ETH Zurich | Modeling the effects of non-pharmaceutical interventions during the COVID-19 pandemic |
| 2 | 12.05.2022, 18:30-20:00 | Prof. Tim Althoff, University of Washington |
Human-AI Collaboration Enables More Empathic Conversations in Mental Health Support |
| 3 | 19.05.2022, 12:00-13:30 | Prof. Robert West, École Polytechnique Fédérale de Lausanne | United States Politicians' Tone Became More Negative with 2016 Primary Campaigns |
| 4 | 02.06.2022, 16:00-17:30 | Prof. Daniel Neill, New York University | Machine Learning and Event Detection for Urban Public Health |
| 5 | 09.06.2022, 12:00-13:30 session cancelled and postponed to winter semester |
Ioana Bica, University of Oxford | From Longitudinal Patient Observational Data to Personalised Treatment Effects Using Causal Inference |
| 6 | 23.06.2022, 16:00-17:30 | Prof. Nathan Kallus, Cornell University | Smooth Contextual Bandits: Bridging the Parametric and Nondifferentiable Regret Regimes Post-Contextual-Bandit Inference |
| 7 | 30.06.2022, 12:00-13:30 | Tobias Hatt, ETH Zurich ——— Daniel Tschernutter, ETH Zurich |
Personalized Medicine using Real-World Data: A Causal Machine Learning Approach ——— Advances in Data-Driven Decision-Making: A Mathematical Optimization Perspective |
| 8 | 07.07.2022, 12:00-13:30 | Prof. Damian Borth, Universität St. Gallen | Trustworthy AI & Hyper-Representation Learning |
| 9 | 14.07.2022, 18:00-19:30 | Prof. Hamsa Bastani, Wharton, University of Pennsylvania | Efficient and targeted COVID-19 border testing via reinforcement learning |
| 10 | 21.07.2022, 12:00-13:30 | Prof. Sebastian Gabel, Rotterdam School of Management | Market Basket Analysis with Context Aware Product Embeddings |
| 11 | 28.07.2022, 16:00-17:30 | Prof. Maytal Saar-Tsechansky, McCombs, University of Texas at Austin | Cost-Effective Learning from Imperfect and Biased Humans Labelers |
*Please note
- We aim to provide an overview of current trends in AI research
- The weekly sessions, on Thursdays, consist of 45-60 minutes of presentation, followed by discussion, feedback and QA
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