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
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Publications
Most updated list available at Google Scholar
A selected list of recent papers that I'm particularly fond of:
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Teaching Arithmetic to Small TransformersICLR 2024 [arxiv]
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Looped Transformers are Better at Learning Learning AlgorithmsICLR 2024 [arxiv]
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Looped Transformers as Programmable ComputersICML 2023 [arxiv]
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Transformers as Algorithms: Generalization and Stability in In-context LearningICML 2023 [arxiv]
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LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning TasksNeurIPS 2022 [arxiv]
Research Group
I am very fortunate to work with and learn from the following amazing colleagues
Members
Alumni
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Postdoc, UT-Austin
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Research Scientist, Mosaic AI/Databricks
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Research Scientist, Mosaic AI/Databricks
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Assistant Professor, Yonsei University, Statistics
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Assistant Professor, Rutgers, CS
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Research Scientist, Google
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ECE Ph.D., UT Austin
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CS Ph.D., UMontreal
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ML Engineer, Facebook
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EECS Ph.D., MIT
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CS Ph.D, Harvard