The MIT-Pillar AI Collective has announced its first six grant recipients. Students, alumni, and postdocs working on a broad range of topics in artificial intelligence, machine learning, and data science will receive funding and support for research projects that might translate into commercially viable products or corporations. These grants are intended to assist students explore business applications for his or her research, and eventually drive that commercialization through the creation of a startup.

“These tremendous students and postdocs are working on projects which have the potential to be truly transformative across a various range of industries. It’s thrilling to think that the novel research these teams are conducting could lead on to the founding of startups that revolutionize all the pieces from drug delivery to video conferencing,” says Anantha Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science.

Launched in September 2022, the MIT-Pillar AI Collective is a pilot program funded by a $1 million gift from Pillar VC that goals to cultivate prospective entrepreneurs and drive innovation in areas related to AI. Administered by the MIT Deshpande Center for Technological Innovation, the AI Collective centers available on the market discovery process, advancing projects through market research, customer discovery, and prototyping. Graduate students and postdocs supported by this system work toward the event of minimum viable products.

“Along with funding, the MIT-Pillar AI Collective provides grant recipients with mentorship and guidance. With the rapid advancement of AI technologies, the sort of support is critical to make sure students and postdocs are capable of access the resources required to maneuver quickly on this fast-pace environment,” says Jinane Abounadi, managing director of the MIT-Pillar AI Collective.

The six inaugural recipients will receive support in identifying key milestones and advice from experienced entrepreneurs. The AI Collective assists seed grant recipients in gathering feedback from potential end-users, in addition to getting insights from early-stage investors. This system also organizes community events, including a “Founder Talks” speaker series, and other team-building activities.   

“Each considered one of these grant recipients exhibits an entrepreneurial spirit. It’s exciting to offer support and guidance as they begin a journey that might in the future see them as founders and leaders of successful corporations,” adds Jamie Goldstein ’89, founding father of Pillar VC.

The primary cohort of grant recipients include the next projects:

Predictive query interface

Abdullah Alomar SM ’21, a PhD candidate studying electrical engineering and computer science, is constructing a predictive query interface for time series databases to higher forecast demand and financial data. This user-friendly interface will help alleviate a few of the bottlenecks and issues related to unwieldy data engineering processes while providing state-of-the-art statistical accuracy. Alomar is suggested by Devavrat Shah, the Andrew (1956) and Erna Viterbi Professor at MIT.

Design of light-activated drugs

Simon Axelrod, a PhD candidate studying chemical physics at Harvard University, is combining AI with physics simulations to design light-activated drugs that might reduce uncomfortable side effects and improve effectiveness. Patients would receive an inactive type of a drug, which is then activated by light in a particular area of the body containing diseased tissue. This localized use of photoactive drugs would minimize the uncomfortable side effects from drugs targeting healthy cells. Axelrod is developing novel computational models that predict properties of photoactive drugs with high speed and accuracy, allowing researchers to concentrate on only the highest-quality drug candidates. He is suggested by Rafael Gomez-Bombarelli, the Jeffrey Cheah Profession Development Chair in Engineering within the MIT Department of Materials Science and Engineering. 

Low-cost 3D perception

Arjun Balasingam, a PhD student in electrical engineering and computer science and a member of the Computer Science and Artificial Intelligence Laboratory’s (CSAIL) Networks and Mobile Systems group, is developing a technology, called MobiSee, that allows real-time 3D reconstruction in difficult dynamic environments. MobiSee uses self-supervised AI methods together with video and lidar to offer low-cost, state-of-the-art 3D perception on consumer mobile devices like smartphones. This technology could have far-reaching applications across mixed reality, navigation, safety, and sports streaming, along with unlocking opportunities for brand new real-time and immersive experiences. He is suggested by Hari Balakrishnan, the Fujitsu Professor of Computer Science and Artificial Intelligence at MIT and member of CSAIL.

Sleep therapeutics

Guillermo Bernal SM ’14, PhD ’23, a recent PhD graduate in media arts and sciences, is developing a sleep therapeutic platform that might enable sleep specialists and researchers to conduct robust sleep studies and develop therapy plans remotely, while the patient is comfortable of 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 offer stimulation and feedback via olfactory, auditory, and visual stimuli, and an internet portal that allows researchers to read a patient’s signals in real time with machine learning evaluation. Bernal was advised by Pattie Maes, professor of media arts and sciences on the MIT Media Lab.

Autonomous manufacturing assembly with human-like tactile perception

Michael Foshey, a mechanical engineer and project manager with MIT CSAIL’s Computational Design and Fabrication Group, is developing an AI-enabled tactile perception system that will be used to offer robots human-like dexterity. With this latest technology platform, Foshey and his team hope to enable industry-changing applications in manufacturing. Currently, assembly tasks in manufacturing are largely done by hand and are typically repetitive and tedious. In consequence, these jobs are being largely left unfilled. These labor shortages could cause supply chain shortages and increases in the fee of production. Foshey’s latest technology platform goals to deal with this by automating assembly tasks to scale back reliance on manual labor. Foshey is supervised by Wojciech Matusik, MIT professor of electrical engineering and computer science and member of CSAIL.  

Generative AI for video conferencing

Vibhaalakshmi Sivaraman SM ’19, a PhD candidate in electrical engineering and computer science who’s a member of CSAIL’s Networking and Mobile Systems Group, is developing a generative technology, Gemino, to facilitate video conferencing in high-latency and low-bandwidth network environments. Gemino is a neural compression system for video conferencing that overcomes the robustness concerns and compute complexity challenges that limit current face-image-synthesis models. This technology could enable sustained video conferencing calls in regions and scenarios that can’t reliably support video calls today. Sivaraman is suggested by Mohammad Alizadeh, MIT associate professor of electrical engineering and computer science and member of CSAIL.