Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows | MIT News

MIT-Pillar AI Collective has introduced three inaugural fellows for the autumn 2023 semester. With assist from this system, the graduate college students, who’re of their remaining yr of a grasp’s or PhD program, will conduct analysis within the areas of synthetic intelligence, machine studying, and knowledge science with the goal of commercializing their improvements.

Launched by MIT’s College of Engineering and Pillar VC in 2022, the MIT-Pillar AI Collective helps school, postdocs, and college students conducting analysis on AI, machine studying, and knowledge science. Supported by a present from Pillar VC and administered by the MIT Deshpande Heart for Technological Innovation, the mission of this system is to advance analysis towards commercialization.

The autumn 2023 MIT-Pillar AI Collective Fellows are:

Alexander Andonian SM ’21 is a PhD candidate in electrical engineering and laptop science whose analysis pursuits lie in laptop imaginative and prescient, deep studying, and synthetic intelligence. Extra particularly, he’s centered on constructing a generalist, multimodal AI scientist pushed by generative vision-language mannequin brokers able to proposing scientific hypotheses, working computational experiments, evaluating supporting proof, and verifying conclusions in the identical means as a human researcher or reviewer. Such an agent could possibly be educated to optimally distill and talk its findings for human consumption and comprehension. Andonian’s work holds the promise of making a concrete basis for rigorously constructing and holistically testing the next-generation autonomous AI agent for science. Along with his analysis, Andonian is the CEO and co-founder of Reelize, a startup that gives a generative AI video device that effortlessly turns lengthy movies into brief clips — and originated from his enterprise coursework and was supported by MIT Sandbox. Andonian can also be a founding AI researcher at Poly AI, an early-stage YC-backed startup constructing AI design instruments. Andonian earned an SM from MIT and a BS in neuroscience, physics, and arithmetic from Bates Faculty.

Daniel Magley is a PhD candidate within the Harvard-MIT Program in Well being Sciences and Know-how who’s enthusiastic about making a wholesome, absolutely functioning thoughts and physique a actuality for all. His modern analysis is targeted on creating a swallowable wi-fi thermal imaging capsule that could possibly be utilized in treating and monitoring inflammatory bowel ailments and their manifestations, comparable to Crohn’s illness. Offering elevated sensitivity and eliminating the necessity for bowel preparation, the capsule has the potential to vastly enhance remedy efficacy and total affected person expertise in routine monitoring. The capsule has accomplished animal research and is getting into human research at Mass Normal Brigham, the place Magley leads a staff of engineers within the hospital’s largest translational analysis lab, the Tearney Lab. Following the human pilot research, the biggest technological and regulatory dangers will probably be cleared for translation. Magley will then start specializing in a multi-site examine to get the system into clinics, with the promise of benefiting sufferers throughout the nation. Magley earned a BS in electrical engineering from Caltech.

Madhumitha Ravichandra is a PhD candidate focused on advancing warmth switch and floor engineering strategies to boost the security and efficiency of nuclear vitality methods and cut back their environmental impacts. Leveraging her deep information of the mixing of explainable AI with high-throughput autonomous experimentation, she seeks to remodel the event of radiation-hardened (rad-hard) sensors, which may doubtlessly stand up to and performance amidst radiation ranges that may render standard sensors ineffective. By integrating explainable AI with high-throughput autonomous experimentation, she goals to quickly iterate designs, check below assorted situations, and make sure that the ultimate product is each sturdy and clear in its operations. Her work on this area may shift the paradigm in rad-hard sensor growth, addressing a obvious void out there and redefining requirements, making certain that nuclear and area purposes are safer, extra environment friendly, and on the slicing fringe of technological progress. Ravichandran earned a BTech in mechanical engineering from SASTRA College, India.

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