The MIT-Pillar AI Collective has announced its first six grant recipients. Students, alumni, and postdocs working on a wide range of AI, machine learning, and data science topics will receive funding and support for research projects that could result in commercially viable products or companies. These grants are intended to help students explore commercial applications for their research and ultimately further that commercialization through the creation of a new company.
“These tremendous students and postdocs are working on projects that have the potential to be truly transformative across a wide range of industries. It’s exciting to think that the groundbreaking research these teams are doing could lead to the founding of startups that would revolutionize everything from drug delivery to video conferencing,” says Anantha Chandrakasan, dean of the School of Engineering and Vannevar Bush Professor of Engineering. Electrical and Computer Science. Science.
Released in September 2022, the MIT-Pillar AI Collective is a pilot program funded by a $1 million grant from Pillar CV which aims to cultivate potential entrepreneurs and drive innovation in AI-related areas. Administered by the MIT Deshpande Center for Technological Innovation, AI Collective focuses on the market discovery process, driving projects forward through market research, customer discovery, and prototyping. Graduate students and postdocs supported by the program work toward the development of minimum viable products.
“In addition to funding, the MIT-Pillar AI Collective provides mentoring and mentoring to grant recipients. With the rapid advancement of AI technologies, this type of support is critical to ensure that students and postdocs can access the resources needed to move quickly in this fast-paced environment,” says Jinane Abounadi, CEO of MIT-Pillar. AI Collective. .
The six inaugural winners will receive support in identifying key milestones and advice from experienced entrepreneurs. AI Collective helps seed grant recipients gather feedback from potential end-users, as well as obtain input from early-stage investors. The program also hosts community events, including a “Founder Talks” speaker series and other team-building activities.
“Every one of these grant recipients exhibits an entrepreneurial spirit. It’s exciting to provide support and guidance as they begin a journey that could one day make them founders and leaders of successful companies,” adds Jamie Goldstein ’89, founder of Pillar VC.
The first cohort of grant recipients includes the following projects:
predictive query interface
Abdullah Alomar SM ’21, a PhD candidate studying electrical engineering and computer science, is building a predictive query interface for time series databases to better forecast demand and financial data. This easy-to-use interface can help alleviate some of the bottlenecks and issues associated with unwieldy data engineering processes while providing state-of-the-art statistical precision. Alomar is advised by Devavrat Shah, Professor Andrew (1956) and Erna Viterbi at MIT.
Design of photoactivated drugs
Simon Axelrod, a doctoral candidate studying chemical physics at Harvard University, is combining AI with physical simulations to design light-activated drugs that could reduce side effects and improve efficacy. Patients would receive an inactive form of a drug, which is then activated by light in a specific area of the body containing diseased tissue. This localized use of photoactive drugs would minimize the side effects of drugs that target healthy cells. Axelrod is developing new computational models that predict the properties of photoactive drugs with high speed and accuracy, allowing researchers to focus only on the highest quality drug candidates. He is advised by Rafael Gomez-Bombarelli, chair of the Jeffrey Cheah Career Development in Engineering in MIT’s Department of Materials Science and Engineering.
Low cost 3D perception
Arjun Balasingam, a PhD student in electrical and computer engineering and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) Mobile Systems and Networks group, is developing a technology, called MobiSee, that enables real-time 3D reconstruction in challenging dynamics. environments. MobiSee uses self-monitoring AI methods in conjunction with video and lidar to provide low-cost, next-generation 3D perception on consumer mobile devices such as smartphones. This technology could have far-reaching applications in mixed reality, navigation, security and sports streaming, as well as unlock opportunities for new immersive and real-time experiences. He is advised by Hari Balakrishnan, Fujitsu Professor of Computer Science and Artificial Intelligence at MIT and a CSAIL member.
sleep therapy
Guillermo Bernal SM ’14, PhD ’23, a recent PhD graduate in media arts and sciences, is developing a therapeutic sleep platform that would enable sleep specialists and researchers to conduct robust sleep studies and develop sleep therapy plans. remotely, while the patient feels comfortable at home. Called Fascia, the three-part system consists of a polysomnogram in a sleep mask form factor that collects data, a hub that allows researchers to provide stimulation and feedback through olfactory, auditory, and visual stimuli, and a web portal. that allows researchers to read a patient’s signals in real time with machine learning analytics. Bernal was mentored by Pattie Maes, a professor of media arts and sciences at the MIT Media Lab.
Autonomous manufacturing assembly with human-like tactile perception
Michael Foshey, a mechanical engineer and project manager in MIT CSAIL’s Computational Design and Manufacturing Group, is developing an AI-enabled tactile perception system that can be used to give robots human-like dexterity. With this new technology platform, Foshey and his team hope to enable industry-changing manufacturing applications. Today, assembly tasks in manufacturing are largely done by hand and are often repetitive and tedious. As a result, these jobs go largely unfilled. This labor shortage can cause shortages in the supply chain and increases in the cost of production. Foshey’s new technology platform aims to address this by automating assembly tasks to reduce reliance on manual labor. Foshey is supervised by Wojciech Matusik, an MIT professor of electrical and computer engineering and a CSAIL member.
Generative AI for video conferencing
Vibhaalakshmi Sivaraman SM ’19, a PhD candidate in electrical engineering and computer science and a member of CSAIL’s Mobile Systems and Networks Group, is developing a generative technology, Gemino, to facilitate video conferencing in low-latency, high-latency network environments. bandwidth. Gemino is a neural compression system for video conferencing that overcomes robustness concerns and computational complexity challenges that limit current facial image synthesis models. This technology could enable sustained video conference calls in regions and scenarios that cannot reliably support video calls today. Sivaraman is advised by Mohammad Alizadeh, an associate professor of electrical and computer engineering at MIT and a CSAIL member.
