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Dimitris Papailiopoulos
Genereret Januar 21 2026 23:56 PM
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Dimitris Papailiopoulos
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Overskrifter
| H1 | H2 | H3 | H4 | H5 | H6 |
| 0 | 6 | 1 | 1 | 8 | 0 |
- [H2] Dimitris Papailiopoulos
- [H2] News
- [H2] Publications
- [H2] Research Group
- [H2] Teaching
- [H2] Contact
- [H3] About
- [H4] Jay & Cynthia Ihlenfeld Associate Professor University of Wisconsin-Madison Electrical and Computer Engineering
- [H5] I am currently on leave at Microsoft Research.
- [H5] I am the Jay & Cynthia Ihlenfeld Associate Professor of Electrical and Computer Engineering (and CS by courtesy) at the University of Wisconsin-Madison, a faculty fellow at the Grainger Institute, and a faculty affiliate with the Optimization group at the Wisconsin Institute for Discovery. My research lies in the intersection of machine learning, coding theory, and optimization. I am particularly interested in the theory and practice of large-scale machine learning systems and the challenges that arise once we aim to build solutions that come with robustness and scalability guarantees. I am particuarly interested in these topics in the context of large language models and transformer architectures. Before coming to Madison, I spent two wonderful years as a postdoc at UC Berkeley, where I was a member of the AMPLab and BLISS, and had the pleasure to collaborate with Ben Recht and Kannan Ramchandran. I received my Ph.D. in 2014 from UT Austin, where I was fortunate to be advised by Alex Dimakis. Before UT, I spent 3.5 years as a grad student at USC. Before all that, I received my M.Sc. (2009) and ECE Diploma (2007) from the Technical University of Crete (TUC), located in the beautiful city of Chania. In 2018, I co-founded the conference on Machine Learning & Systems (MLSys), a new conference that targets research at the intersection of systems and machine learning. In 2018 and 2020, I was the program co-chair for MLSys. In 2019, I also co-chaired the 3rd Midwest Machine Learning Symposium (MMLS). gScholar bio, resume twitter
- [H5] ICML 2019 Does Data Augmentation Lead to Positive Margin?
- [H5] AISTATS 2019 A Geometric Perspective on the Transferability of Adversarial Directions
- [H5] Sony Faculty Innovation Award!! [link]
- [H5] Benjamin Smith Reynolds Award for Excellence in Teaching!! [link]
- [H5] NSF CAREER Award!! Coding Theory for Robust Large-Scale Machine Learning
- [H5] I am very fortunate to work with and learn from the following amazing colleagues
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| Anker | Type | Juice |
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| Dimitris | Intern | Sender Juice |
| About | Intern | Sender Juice |
| News | Intern | Sender Juice |
| Publications | Intern | Sender Juice |
| Research Group | Intern | Sender Juice |
| Teaching | Intern | Sender Juice |
| Contact | Intern | Sender Juice |
| University of Wisconsin-Madison | Ekstern | Sender Juice |
| Electrical and Computer Engineering | Ekstern | Sender Juice |
| Computer Sciences | Ekstern | Sender Juice |
| UC Berkeley | Ekstern | Sender Juice |
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| Technical University of Crete (TUC) | Ekstern | Sender Juice |
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| NSF CAREER Award | Ekstern | Sender Juice |
| Sony Faculty Innovation Awards | Ekstern | Sender Juice |
| MADLab | Ekstern | Sender Juice |
| ARPA-E Award | Ekstern | Sender Juice |
| American Family Data Science Research Grants | Ekstern | Sender Juice |
| AWS Cloud Credits for Research | Ekstern | Sender Juice |
| gScholar | Ekstern | Sender Juice |
| bio | Intern | Sender Juice |
| resume | Intern | Sender Juice |
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fall university research spring machine ece phd learning engineering systems
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Domæne : papail.io
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