From left to right, Yunhao Ge, Sina Shaham, and Jiao Sun
From left to right, Yunhao Ge, Sina Shaham, and Jiao Sun are PhD students at USC who have been named as Amazon ML Fellows. The students will receive fellowship funding and will also be mentored by Amazon scientists.

Amazon and USC name three new ML Fellows

PhD students will receive fellowship funding and be mentored by Amazon scientists.

The USC + Amazon Center on Secure and Trusted Machine Learning, established in January 2021 to support fundamental research and development of new approaches to machine learning (ML) privacy, security, and trustworthiness, today announced it has selected three PhD students as Amazon ML Fellows for the 2022-23 academic year.

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Center to support novel approaches to trust-centric machine learning and AI innovation.

The students will receive fellowship funding through the USC + Amazon Center. They will also be mentored by Amazon scientists.

“We are delighted by the high quality of the fellowship nominations,” said Prem Natarajan, Alexa AI vice president of natural understanding. “The research being conducted by the fellows supports our goal of addressing some of the hardest challenges in AI, democratizing access to the innovative outcomes of this work, and investing in the AI leaders of tomorrow.”

“Amazon ML fellowships provides a unique opportunity to recognize our most talented students and further pave the way for their future success,” said Salman Avestimehr, inaugural director of the USC + Amazon Center and the Dean’s Professor of electrical and computer engineering, and computer science. “This year we received about 50% more nominations than last year for Amazon ML PhD fellowships. We were all very much impressed by the quality and exceptional achievements of our PhD students.”

Below is information about the three recipients and their areas of research:

  • Yunhao Ge is a third-year PhD student in the computer science department at USC. He is advised by professor Laurent Itti. His research interests are in machine learning and computer vision, as well as their applications toward more explainable and trustworthy AI. His dissertation focuses on fairness in machine learning. “Being an Amazon fellow is not only an honor, but a motivation for me,” Ge said. “It encourages me to keep exploring the challenging task of understanding the reasoning logic of AI models.”
  • Sina Shaham is a third-year PhD candidate within the computer science department at USC, advised by professor Cyrus Shahabi. His research is on the interaction of privacy and fairness in machine learning and its application for geospatial data. Previously, he worked on fairness in social media and has held positions as a researcher and data scientist. He has contributed to several publications on enhancing privacy and fairness in decision-making. “Amazon has a long-standing reputation for technological innovation and support for creativity,” Shaham said. “Being an Amazon fellow provides a unique opportunity for me to explore new ideas and contribute to the journey of responsible AI in shaping the future.”
  • Jiao Sun is a computer science PhD candidate at USC. She is advised by professor Xuezhe (Max) Ma, and collaborates closely with professors Nanyun (Violet) Peng and Swabha Swayamdipta. Her papers on trustworthy natural language generation have appeared in top NLP conferences, including a best paper recommendation at ACL 2021 and a best paper honorable mention at CHI 2022. “Words cannot express how excited I am to be an Amazon ML fellow,” Sun said. “It is a great recognition and encouragement for me to continue working on trustworthy text generation. With the fellowship, I hope we can push one step further towards improving and applying state-of-the-art text generation models in fruitful use cases.”

“It is remarkable to see the growth of the program, its attractiveness to our students and its promise for exceptional contributions,” said Yannis Yortsos, dean of the USC Viterbi School of Engineering. “This is a testament to the thriving partnership of USC Viterbi with Amazon, and the leadership of our colleagues at both institutions.”

Research areas

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