Unless indicated, all talks begin at 4 pm. Where available, flyers are linked in the Talk Title column.
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| Date | Speaker | Affiliation | Position | Talk Title | Location |
|---|---|---|---|---|---|
| 4/9/2024 | Lens Media Lab | Yale University | Characterizing Twentieth-Century Photographic Papers: A Multidisciplinary Approach | Taylor 203 (5:30–6:30 pm); Taylor Jade Room (6:30–7:30 pm) | |
| 4/8/2024 | Thomas Schmickl | University of Graz, Austria | Professor, Institute of Biology | Can Robots Save Nature? | Rockefeller 300 (Starts at 5:00 pm) |
| 2/7/2024 | Brenden Lake | New York University | Professor of Psychology and Data Science | Addressing two classic debates in cognitive science with deep learning | Rockefeller 300 (Starts at 5 pm) |
| 11/10/2023 | Rob Williams | Bayer Crop Science | Data Scientist Remote Sensing | Data Science for Plants | New England 206 (Starts at 5 pm) |
| 10/6/2023 | Jenna Lemonias | The Atlantic | Executive Director, Data Science | Our personalized web: The role – and consequences – of recommendation algorithms for news | New England 206 |
| 9/20/2023 | Mine Dogucu | University of California Irvine | Vice Chair for Undergraduate Studies, Department of Statistics | The Place of Accessibility in (Data) Science | Rockefeller 312 (Starts at 3 pm) |
| 4/28/2023 | Anurag Mehra | IIT-Bombay, India | Professor in Charge of IIT Bombay’s Centre for Liberal Education | Data-Based Surveillance During Covid-19 | Sanders Physics 105 |
| 4/7/2023 | Kristina Lerman | University of Southern California | Project Leader at the Information Sciences Institute | Biases in Data & Other Threats to Validity of Predictive Models | Rockefeller 310 |
| 12/1/2022 | Jeremy Springman | DevLab@Penn | Senior Research Associate | Machine Learning for Peace | Sanders Physics 105 |
| 11/4/2022 | Michael Burnam-Fink | First Republic Bank | Senior Software Engineer | What is Scientific About Data Science? | Rockefeller 312 |
| 10/7/2022 | Marie desJardins | Simmons University | Dean of the College of Organizational, Computational, and Information Sciences | Fairness and Equity in Data Science | New England 206 |