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

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 help from this system, the graduate students, who’re of their last 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 School of Engineering and Pillar VC in 2022, the MIT-Pillar AI Collective helps school, postdocs, and students conducting analysis on AI, machine studying, and knowledge science. Supported by a present from Pillar VC and administered by the MIT Deshpande Center for Technological Innovation, the mission of this system is to advance analysis towards commercialization.

The fall 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. More particularly, he’s centered on constructing a generalist, multimodal AI scientist pushed by generative vision-language mannequin brokers able to proposing scientific hypotheses, operating computational experiments, evaluating supporting proof, and verifying conclusions in the identical manner as a human researcher or reviewer. Such an agent might be skilled 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. In addition to his analysis, Andonian is the CEO and co-founder of Reelize, a startup that gives a generative AI video software that effortlessly turns lengthy movies into brief clips — and originated from his enterprise coursework and was supported by MIT Sandbox. Andonian can 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 College.

Daniel Magley is a PhD candidate within the Harvard-MIT Program in Health Sciences and Technology who’s enthusiastic about making a wholesome, totally functioning thoughts and physique a actuality for all. His modern analysis is concentrated on creating a swallowable wi-fi thermal imaging capsule that might be utilized in treating and monitoring inflammatory bowel ailments and their manifestations, such as Crohn’s illness. Providing elevated sensitivity and eliminating the necessity for bowel preparation, the capsule has the potential to vastly enhance therapy efficacy and general affected person expertise in routine monitoring. The capsule has accomplished animal research and is getting into human research at Mass General Brigham, the place Magley leads a crew of engineers within the hospital’s largest translational analysis lab, the Tearney Lab. Following the human pilot research, the most important technological and regulatory dangers can be cleared for translation. Magley will then start specializing in a multi-site research 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 fascinated with advancing warmth switch and floor engineering strategies to reinforce the security and efficiency of nuclear vitality methods and scale back their environmental impacts. Leveraging her deep data of the mixing of explainable AI with high-throughput autonomous experimentation, she seeks to rework the event of radiation-hardened (rad-hard) sensors, which may probably face up to and performance amidst radiation ranges that will render standard sensors ineffective. By integrating explainable AI with high-throughput autonomous experimentation, she goals to quickly iterate designs, check beneath assorted circumstances, and be certain that the ultimate product is each strong and clear in its operations. Her work on this house may shift the paradigm in rad-hard sensor improvement, addressing a obvious void available in the market and redefining requirements, guaranteeing that nuclear and house purposes are safer, extra environment friendly, and on the slicing fringe of technological progress. Ravichandran earned a BTech in mechanical engineering from SASTRA University, India.

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