Home AI News MIT-Pillar AI Collective Announces Inaugural Fellows for Fall 2023

MIT-Pillar AI Collective Announces Inaugural Fellows for Fall 2023

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MIT-Pillar AI Collective Announces Inaugural Fellows for Fall 2023

MIT-Pillar AI Collective Announces Inaugural Fellows for Fall 2023

The MIT-Pillar AI Collective has selected three graduate students as the inaugural fellows for the fall 2023 semester. These students, in their final year of a master’s or PhD program, will focus on research in areas of artificial intelligence, machine learning, and data science with the goal of commercializing their innovations.

Introduced in 2022 by MIT’s School of Engineering and Pillar VC, the MIT-Pillar AI Collective provides support for faculty, postdocs, and students conducting research in AI, machine learning, and data science. The program is funded by Pillar VC and managed by the MIT Deshpande Center for Technological Innovation, with the aim of advancing research towards commercialization.

The MIT-Pillar AI Collective Fall 2023 Fellows are:

Alexander Andonian, a PhD candidate in electrical engineering and computer science, focuses on developing a generalist, multimodal AI scientist driven by generative vision-language model agents capable of proposing scientific hypotheses. In addition to his research, Andonian is also the CEO and co-founder of Reelize, a startup that offers a generative AI video tool and a founding AI researcher at Poly AI.

Daniel Magley, a PhD candidate in the Harvard-MIT Program in Health Sciences and Technology, is working on a swallowable wireless thermal imaging capsule for treating and monitoring inflammatory bowel diseases. Magley leads a team of engineers in Mass General Brigham’s translational research lab, the Tearney Lab.

Madhumitha Ravichandra, a PhD candidate, aims to enhance the safety and performance of nuclear energy systems by integrating explainable AI with high-throughput autonomous experimentation to develop radiation-hardened sensors.

The MIT-Pillar AI Collective is paving the way for these students to make significant contributions to the fields of AI, machine learning, and data science, ultimately catalyzing the commercialization of innovative research.

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