Lightning Talks by the 2022 Amazon Fellows

In 2021 Amazon and UCLA collaborated to establish the Science Hub for Humanity and Artificial Intelligence. Recently, the Science Hub advisory group selected twelve Amazon Fellows for 2022, all Ph.D. students from the UCLA Samueli School of Engineering.

Capturing our imaginations during a round of lightning talks, they presented their research, which spans machine learning, natural language processing, robotics, and beyond. Each fellow wrapped up their presentation with a brief Q&A session.

2022 Amazon Fellows’ Individual Slide Decks

Antonious M. Girgis

Advisor: Suhas Diggavi

Communication-Efficient and Privacy-Preserving Machine Learning

Zijie Huang

Advisors: Yizhou Sun & Prof. Wei Wang

Deep Learning for Reasoning Over Graph Structured Dynamic Data

Yifan Qiao

Advisors: Harry Xu and Miryung Kim

Democratize Large-scale ML Training with Full-stack Systems

Liunian Harold Li

Advisor: Kai-Wei Chang

Learning Vision-Language Alignment from Natural Data

Michael Kleinman

Advisor: Johnathan Kao

Usable Information and Evolution of Optimal Representations During Training

Akash Deep Singh

Advisor: Mani Srivastava

Deep Scene Understanding Using RF and its Fusion with other Modalities

Weitong Zhang

Advisor: Quanquan Gu

Towards Explainable and Accountable Reinforcement Learning Systems

Huajing Zhao

Advisor: Veronica Santos

Human-centered Approaches to Semiautonomous Robots for Manipulation

Tao Meng

Advisor: Kai-Wei Chang

Constrained Inference for Bridging the Distributional Gap in Natural Language Processing

Xiangning Chen

Advisor: Cho-Jui Hsieh

Automated Machine Learning

Ziniu Hu

Advisor: Yizhou Sun

Differentiable Symbolic Reasoning with Graph Neural Networks

Ruchao Fan

Advisor: Abeer Alwan

On the Accuracy and Inference Efficiency for Low-resource Automatic Speech Recognition