Three MIT students chosen as inaugural MIT-Pillar AI Collective Fellows

MIT-Pillar AI Collective has announced three inaugural fellows for the autumn 2023 semester. With support from this system, the graduate students, who’re of their final yr of a master’s or PhD program, will conduct research within the areas of artificial intelligence, machine learning, and data science with the aim of commercializing their innovations.

Launched by MIT’s School of Engineering and Pillar VC in 2022, the MIT-Pillar AI Collective supports faculty, postdocs, and students conducting research on AI, machine learning, and data 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 research toward commercialization.

The autumn 2023 MIT-Pillar AI Collective Fellows are:

Alexander Andonian SM ’21 is a PhD candidate in electrical engineering and computer science whose research interests lie in computer vision, deep learning, and artificial intelligence. More specifically, he is concentrated on constructing a generalist, multimodal AI scientist driven by generative vision-language model agents able to proposing scientific hypotheses, running computational experiments, evaluating supporting evidence, and verifying conclusions in the identical way as a human researcher or reviewer. Such an agent might be trained to optimally distill and communicate its findings for human consumption and comprehension. Andonian’s work holds the promise of making a concrete foundation for rigorously constructing and holistically testing the next-generation autonomous AI agent for science. Along with his research, Andonian is the CEO and co-founder of Reelize, a startup that provides a generative AI video tool that effortlessly turns long videos into short clips — and originated from his business 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 tools. 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 keen about making a healthy, fully functioning mind and body a reality for all. His leading-edge research is concentrated on developing a swallowable wireless thermal imaging capsule that might be utilized in treating and monitoring inflammatory bowel diseases and their manifestations, akin to Crohn’s disease. Providing increased sensitivity and eliminating the necessity for bowel preparation, the capsule has the potential to vastly improve treatment efficacy and overall patient experience in routine monitoring. The capsule has accomplished animal studies and is entering human studies at Mass General Brigham, where Magley leads a team of engineers within the hospital’s largest translational research lab, the Tearney Lab. Following the human pilot studies, the biggest technological and regulatory risks will probably be cleared for translation. Magley will then begin specializing in a multi-site study to get the device into clinics, with the promise of benefiting patients across the country. Magley earned a BS in electrical engineering from Caltech.

Madhumitha Ravichandra is a PhD candidate eager about advancing heat transfer and surface engineering techniques to reinforce the protection and performance of nuclear energy systems and reduce their environmental impacts. Leveraging her deep knowledge of the combination of explainable AI with high-throughput autonomous experimentation, she seeks to remodel the event of radiation-hardened (rad-hard) sensors, which could potentially withstand and performance amidst radiation levels that may render conventional sensors useless. By integrating explainable AI with high-throughput autonomous experimentation, she goals to rapidly iterate designs, test under varied conditions, and be certain that the ultimate product is each robust and transparent in its operations. Her work on this space could shift the paradigm in rad-hard sensor development, addressing a glaring void available in the market and redefining standards, ensuring that nuclear and space applications are safer, more efficient, and on the leading edge of technological progress. Ravichandran earned a BTech in mechanical engineering from SASTRA University, India.