The MIT-Pillar AI Collective has announced the first six grant recipients. Students, graduates and postdocs working on a wide range of subjects in artificial intelligence, machine learning and data science will receive funding and support for research projects that may lead to commercially viable products and companies. These grants are intended to help students explore commercial applications for their research and ultimately promote their commercialization through the formation of start-ups.
“These talented students and postdocs are working on potentially truly transformative projects across a variety of industries. It’s exciting to think that it could lead to the creation of a start-up company that will revolutionize the world,” said Anantha Chandrakasan, Dean of the School of Engineering and Professor of Electrical Engineering and Computers at Vannevar Bush. Chemistry.
Launched in September 2022, the MIT-Pillar AI Collective is a pilot program funded by a $1 million donation from Pillar VC to nurture future entrepreneurs and drive innovation in AI-related fields. is intended for Managed by the MIT Deshpande Technology and Innovation Center, the AI Collective focuses on the market research process, driving projects through market research, customer discovery, and prototyping. Graduate students and postdocs supported by this program work to develop a minimally viable product.
“In addition to funding, the MIT-Pillar AI Collective will provide mentorship and guidance to grant recipients. This kind of support is essential to ensure that we have access to the resources we need,” said Jinan Abnadi, managing director of the MIT-Pillar AI Collective. .
The first six winners will receive support in identifying key milestones and advice from seasoned entrepreneurs. The AI Collective helps seed grant recipients gather feedback from potential end-users and gain insights from early-stage investors. The program also organizes community events such as “Founder Talks” speaker series and other team building activities.
“All of these grantees demonstrate an entrepreneurial spirit. It is a great pleasure to provide support and guidance as they begin their journey where they will one day be seen as founders and leaders of successful companies.” That’s it,” added Jamie Goldstein ’89, founder of Pillar VC.
The first group of grantees includes the following projects:
prediction query interface
Abdullah Alomar SM ’21 is a PhD candidate studying electrical engineering and computer science, building forecast query interfaces for time series databases to more accurately forecast demand and financial data. This user-friendly interface helps alleviate some of the bottlenecks and problems associated with cumbersome data engineering processes while providing state-of-the-art statistical accuracy. Alomar is advised by Andrew (1956) at MIT and Devabrat Shah, Professor Erna Vitavi.
Design of photoactivated drugs
Simon Axelrod, a Ph.D. student in chemical physics at Harvard University, combines AI and physics simulations to design photoactive drugs that can reduce side effects and increase efficacy. Patients receive the drug in its inactive form, which is then activated by light in specific areas of the body, including the affected tissue. The topical use of this photoactive agent minimizes side effects from agents that target healthy cells. Axelrod is developing new computational models that rapidly and accurately predict photoactive drug properties, enabling researchers to focus on only the highest quality drug candidates. He is advised by Rafael Gomez Bombarelli, Chair of the Jeffrey Chia Career Development Committee in the Engineering Division of the Massachusetts Institute of Technology’s School of Materials Science and Engineering.
Low cost 3D recognition
Arjun Balasingam, a PhD student in electrical engineering and computer science and a member of the Networks and Mobile Systems group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), has developed real-time 3D reconstructions in challenging dynamic environments. We are developing a technology called MobiSee that allows us to do that. environment. MobiSee uses self-supervised AI techniques along with video and his LIDAR to provide low-cost, state-of-the-art his 3D recognition on consumer mobile his devices such as smartphones. Not only does this technology open up opportunities for new real-time, immersive experiences, but it also has the potential for widespread applications across mixed reality, navigation, safety, and sports streaming. He is advised by Mr. Hari Balakrishnan, Fujitsu Professor of Computer Science and Artificial Intelligence at MIT and a member of CSAIL.
sleep therapy
Guillermo Bernal SM ’14, Ph.D. ’23 is a recent Ph.D. in Media Arts and Sciences that allows sleep professionals and researchers to conduct remote and robust sleep research while the patient remains comfortable. , is developing a sleep therapy platform that allows you to create treatment plans. their home. Called Fascia, the three-part system consists of a polysomnogram with a sleep mask form factor that collects data, a hub that allows researchers to provide stimulation and feedback via olfactory, auditory and visual stimuli; It consists of a web portal where researchers can read the information. Collect patient signals in real time with machine learning analytics. Bernal was advised by Patti Mays, professor of media arts and sciences at the MIT Media Lab.
Autonomous manufacturing assembly with human-like haptics
Michael Foshey, a mechanical engineer and project manager in the Computational Design and Manufacturing group at MIT CSAIL, is developing an AI-enabled haptic perception system that can be used to give robots human-like dexterity. Foshey and his team hope to use this new technology platform to enable industry-changing applications in manufacturing. Today, assembly operations in manufacturing are largely manual and are usually repetitive and tedious. As a result, these jobs are almost filled. Such labor shortages can lead to supply chain shortages and higher production costs. Foshey’s new technology platform aims to address this problem by automating assembly tasks and reducing reliance on manual labor. Foshey is a professor of electrical engineering and computer science at MIT and a member of CSAIL, where he is supervised by Wojciech Matusik.
Generative AI for Video Conferencing
Vibhaalakshmi Sivaraman SM ’19, a PhD Candidate in Electrical Engineering and Computer Science, member of CSAIL’s Networking and Mobile Systems Group, has developed a program to facilitate video conferencing in high-latency and low-bandwidth network environments. We are developing Gemino, a technology. Gemino is a neural compression system for videoconferencing that overcomes the challenges of robustness concerns and computational complexity that limit current facial image synthesis models. This technology has the potential to enable continuous video conferencing calls in regions and scenarios where video calling cannot be reliably supported today. Mr. Shivaraman is an associate professor of electrical engineering and computer science at MIT and is advised by CSAIL member Mohammad Alizadeh.
