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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

Melanie Weber, University of Oxford: “Geometric Methods for Machine Learning and Optimization”

September 10, 2021October 5, 2021Myung-Hee Vabulas
Participant

Amanda Watson, University of Pennsylvania: “Computation of Human Performance”

September 9, 2021October 5, 2021Myung-Hee Vabulas
Participant

Maribel Torres-Velazquez, UW-Madison: “Multi-channel Deep Learning Networks as an Advanced Modeling Technique in Improving Epilepsy Workup”

September 9, 2021October 5, 2021Myung-Hee Vabulas
Participant

Mansi Sood, Carnegie Mellon University: “Heterogeneous models for designing resilient topologies and controlling spreading phenomena in real-world networks”

September 9, 2021October 5, 2021Myung-Hee Vabulas
Participant

Yuhan Shi, UCSD: “Neuro-inspired Computing using Resistive Memory Devices”

September 9, 2021October 5, 2021Myung-Hee Vabulas
Participant

Liyue Shen, Stanford University: “Exploiting Prior Knowledge in Physical World Incorporated with Machine Learning for Solving Medical Imaging Problems”

September 8, 2021October 5, 2021Myung-Hee Vabulas
Participant

Anshuka Rangi, Amazon: “Understanding the Limits of Poisoning Attacks in Multi-Armed Bandits and Reinforcement Learning”

September 8, 2021October 5, 2021Myung-Hee Vabulas
Participant

Yao Qin, Google: “Understanding and Improving Robustness in Machine Learning Models”

September 8, 2021October 5, 2021Myung-Hee Vabulas
Participant

Srilakshmi Pattabiraman, University of Illinois Urbana-Champaign: “Coding for Polymer and DNA Based Storage”

September 8, 2021October 5, 2021Myung-Hee Vabulas
Participant

Yuval Moskovitch, University of Michigan: “Towards Reliable Data-Driven Decision Tools”

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

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