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EECS Rising Stars 2021

EECS Rising Stars 2021

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Author: Myung-Hee Vabulas

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Participant

Michal Moshkovitz, Tel-Aviv University: “Foundations of Explainable Machine learning”

September 7, 2021October 5, 2021Myung-Hee Vabulas
Participant

Faidra Monachou, Stanford University: “Discrimination, diversity, and information in selection problems”

September 7, 2021October 5, 2021Myung-Hee Vabulas
Participant

Christine McGinn, Columbia University: “Role of Nanoparticle Composites in Active Devices”

September 7, 2021October 5, 2021Myung-Hee Vabulas
Participant

Lydia Tingruo Liu, UC Berkeley: “Designing distributive learning algorithms for the societal good”

September 6, 2021October 5, 2021Myung-Hee Vabulas
Participant

Qi Lei, Princeton University: “Provable Representation Learning: The Importance of Task Diversity and Pretext Tasks”

September 6, 2021October 5, 2021Myung-Hee Vabulas
Participant

Shalmali Joshi, Harvard University: “Towards Safe, Robust and Reliable Machine Learning for Healthcare”

September 5, 2021October 5, 2021Myung-Hee Vabulas
Participant

Mengdi Huai, University of Virginia: “Fostering Trustworthiness in Machine Learning Algorithms”

September 5, 2021October 5, 2021Myung-Hee Vabulas
Participant

Nasimeh Heydaribeni, University of Michigan: “Analysis and Design of Information Transmission in Networks of Strategic Agents”

September 4, 2021October 5, 2021Myung-Hee Vabulas
Participant

Bahareh Hadidian, University of Michigan: “High-Data-Rate and Energy-Efficient Wireless Transmitters for Beyond 5G Communication Networks”

September 4, 2021October 5, 2021Myung-Hee Vabulas
Participant

Neha Gupta, Stanford University: “Theoretical approaches to machine learning challenges”

September 4, 2021October 5, 2021Myung-Hee Vabulas

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