In January, eight scientists were named as 2021 Amazon AI4Science Fellows at Caltech, the world-renowned science and engineering research institution based in Pasadena, Calif. The Fellows program is a result of a collaboration between Caltech and Amazon around supporting the AI4Science initiative and its goal of sharing the latest advances in artificial intelligence (AI) and machine learning (ML) to benefit all branches of scientific and engineering research.
There’s a huge level of demand among graduate students and post-doctoral scholars across campus to leverage the techniques and advantages afforded by using AI and machine learning in their own research.
“Amazon’s gift will have a real impact on our program,” said Yisong Yue, professor of Computing and Mathematical Sciences and co-founder of the AI4Science initiative. “There’s a huge level of demand among graduate students and post-doctoral scholars across campus to leverage the techniques and advantages afforded by using AI and machine learning in their own research.”
“Caltech is uniquely placed to be a leader in AI4science given its interdisciplinary collaborations and small size,” added Anima Anandkumar, Bren Professor of Computing and Mathematical Sciences and co-founder of the AI4Science initiative. “We thank Amazon for supporting this groundbreaking initiative.”
For those students specializing in data sciences, Yue said, “it allows them to be exposed to the datasets and research questions faced by scientists in other fields, as well as in companies such as Amazon, and to push the boundaries of existing AI and machine-learning algorithms to effectively address these questions.”
“At Amazon, we strongly believe that AI should be an integral part of all science, not just computer science,” said Marzia Polito, AWS senior manager of applied science. “We are building products supporting the use of AI in many fields of science and many science-based business applications. We are thrilled to collaborate with Caltech, a world-class institution doing ground-breaking science work, and we are honored to have a chance to contribute to their amazing results. There could be no better evidence toward a future where AI and science thrive together.”
This year’s cohort of Fellows comes from the Division of Biology and Biological Engineering, the Division of Chemistry and Chemical Engineering, and the Division of Engineering and Applied Science, reflecting the broad range of research being explored. The Fellows will apply cutting-edge ML and AI techniques to research areas ranging from neural prosthetics and theoretical chemistry, to the human microbiome.
The Amazon AI4Science Fellows and research areas are:
- Carmen Amo Alonso, a graduate student pursuing her PhD in control and dynamical systems in the lab of John Doyle, Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and Bioengineering, is studying the application of AI to large-scale complex systems in areas as diverse as understanding the gut microbiome to designing optimized “smart” grids.
- Sara Beery, a graduate student pursuing her PhD in computing and mathematical sciences in the lab of Pietro Perona, Allen E. Puckett Professor of Electrical Engineering, is developing approaches to collect global-scale, real-time ecological data for conservation purposes.
- Charles Guan, a graduate student pursuing his PhD in bioengineering in the lab of Richard Andersen, James G. Boswell Professor of Neuroscience, T&C Chen Brain-Machine Interface Center Leadership Chair, and director of the T&C Brain-Machine Interface Center, is developing decoding algorithms for neural prostheses and studying the neural basis of movement.
- Kadina Johnston, a graduate student pursuing her PhD in bioengineering in the lab of Nobel-prize winner Frances Arnold, Linus Pauling Professor of Chemical Engineering, Bioengineering, and Biochemistry and director of the Donna and Benjamin M. Rosen Bioengineering Center, is applying deep learning techniques to the directed evolution approach for enzyme engineering.
- Nikola Kovachki, a graduate student pursuing his PhD in applied and computational mathematics in the lab of Andrew Stuart, Bren Professor of Computing and Mathematical Sciences, is using deep learning techniques for solving partial differential equations, which has applications for climate modeling, understanding turbulent flow of fluids, and a wide range of materials science problems.
- Zhuoran Qiao, a graduate student pursuing his PhD in chemistry in the lab of professor of chemistry Tom Miller, is developing physics-based machine learning methods for studying problems in complex chemical systems.
- Guannan Qu, a post-doctoral scholar working under the supervision of Steven Low, Frank J. Gilloon Professor of Computing and Mathematical Sciences and Electrical Engineering, and Adam Wierman, professor of computing and mathematical sciences and director of Information Science and Technology, is developing multi-agent reinforcement learning approaches that are scalable, distributed, and have provable guarantees such that they will be usable for safety-critical applications.
- He Sun, a post-doctoral scholar working under the supervision of Katie Bouman, assistant professor of computing and mathematical sciences, electrical engineering and astronomy and Rosenberg Scholar, is developing new machine learning algorithms that can improve current computational imaging approaches.
The diverse interests of the Fellows reflect a trend in AI and machine learning that emphasizes cross-disciplinary research and is in line with the AI4Science focus.
“Today we need students who are experts in their own fields, but who also can communicate across different fields,” Yue said. “Effective communication requires a mix of fundamentally sound rigorous thinking coupled with a broad perspective on how to apply that approach to wide range of domains, in order to reveal and distill the core technical challenges that underlie the pressing problems facing science and engineering research today.”
The AI4Science Fellows program is one component within a larger collaboration between Amazon and Caltech. In the area of AI4Science, Amazon is also providing funds for Caltech’s Carver Mead New Adventures Fund, AWS credits for research projects across campus, and support for AI4Science events to build community and share research results.
Beyond the AI4Science initiative, Caltech and Amazon are collaborating in a number of other areas. A group of scientists within AWS’s Amazon Rekognition team is a part of Caltech’s Innovation Center, a building near campus that houses Caltech corporate collaborators and startups. In 2019, AWS and Caltech also announced a collaboration around quantum computing, which will include the AWS Center for Quantum Computing, set to open later this year.
“Caltech prides itself as being an incubator for concepts like AI4Science and next-generation technologies like quantum computing,” said Caltech’s Kaushik Bhattacharya, vice provost for Research and Howell N. Tyson, Sr., Professor of Mechanics and Materials Science. “Our small size, our relentless focus on the most challenging scientific questions — along with our close-knit community that is interdisciplinary by design — encourage and enable us to always be pioneering in the application of tools and techniques from other fields to all areas of science and engineering. To help make sure our findings have impacts beyond academia, we greatly value our collaborations with partners like Amazon.”
