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The MIT-Pillar AI Collective has announced its first six grantees. Students, graduates and postdocs working on a wide range of artificial intelligence, machine learning and data science topics will receive funding and support for research projects that can be developed into commercially viable products or companies. These grants aim to help students explore commercial applications for their research and ultimately lead that commercialization through the creation of a startup.
“These tremendous students and postdocs are working on projects that have the potential to be truly transformative across a diverse range of industries. It’s exciting to think that new research from these teams could lead to startups that revolutionize everything from drug delivery to video conferencing,” said Ananta Chandrakasan, dean of the School of Engineering and Vannevari Bush Professor of Electrical and Computer Engineering. Science.
Launched in September 2022, the MIT-Pillar AI Collective is a pilot program funded by a $1 million gift from Pillar VC that aims to develop promising entrepreneurs and spark innovation in AI-related fields. Administered by the MIT Deshpande Center for Technological Innovation, the AI Collective is focused on the market discovery process, advancing projects through market research, customer discovery, and prototyping. Graduate students and postdoctoral fellows supported by the program are working to develop minimum viable products.
“In addition to funding, the MIT-Pillar AI Collective provides mentorship and guidance to grantees. With the rapid advancement of AI technologies, this type of support is critical to ensure that students and postdocs can access the resources they need to move quickly in this fast-paced environment,” said Jeanne 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. AI Collective helps seed grantees gather feedback from potential end users as well as get input from early stage investors. The program also hosts community events, including Founder Talks speaker series and other team building activities.
“Each of these grantees demonstrates an entrepreneurial spirit. It’s exciting to support and guide them as they embark on the journey that will one day see them as founders and leaders of successful companies,” adds Jamie Goldstein ’89, founder of Pillar VC.
The first group 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 interface for time series databases to better forecast demand and financial data. This user-friendly interface can help alleviate some of the delays and problems associated with data engineering processes while maintaining state-of-the-art statistical accuracy. Alomar is advised by the Devavrat Shah, Andrew (1956) and Erna Viterbi Professor at MIT.
Design of light-activated drugs
Simon Axelrod, a PhD candidate studying chemical physics at Harvard University, combines artificial intelligence with physical simulations to develop light-activated drugs that can reduce side effects and improve efficacy. Patients will receive an inactive form of the drug, which is then activated by light in a specific area of the body that contains the diseased tissue. This localized application of photoactive drugs will minimize the side effects of drugs targeting healthy cells. Axelrod is developing new computational models that predict the properties of photoactive drugs with high speed and accuracy, allowing researchers to focus on only the highest quality drug candidates. He is advised by Rafael Gómez-Bombarelli, the Jeffrey Chia Career Development Chair in Engineering in MIT’s Department of Materials Science and Engineering.
Inexpensive 3D perception
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), is developing a technology called MobiSee that enables real-time 3D reconstruction of complex dynamic conditions. environment. MobiSee uses self-supervised AI methods along with video and lidar to provide low-cost, state-of-the-art 3D sensing on consumer mobile devices such as smartphones. This technology could have far-reaching applications across mixed reality, navigation, security and sports streaming, in addition to unlocking new real-time and immersive experiences. He is advised by Hari Balakrishnan, the Fujitsu Professor of Computer Science and Artificial Intelligence at MIT and a member of CSAIL.
Sleep therapy
Guillermo Bernal SM ’14, PhD ’23, who recently completed his PhD in media arts and sciences, is developing a sleep therapy platform that will enable sleep specialists and researchers to conduct powerful sleep studies and develop therapy plans remotely while the patient is comfortable. Their house. 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 through olfactory, auditory, and visual stimuli, and a web portal that allows researchers to read. Real-time machine learning analysis of patient signals. Bernal was advised by Patti Mace, a professor of media arts and sciences at the MIT Media Lab.
Autonomous manufacturing assembly with human-like tactile perception
Michael Foschi, 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 applications in manufacturing. Currently, assembly tasks in manufacturing are mostly done manually and are usually repetitive and tedious. As a result, these jobs remain largely unfilled. This labor shortage can lead to supply chain shortages and increased production costs. Foshey’s new technology platform aims to solve this problem by automating assembly tasks to reduce reliance on manual labor. Foshi is led by Wojciech Matusik, MIT professor of electrical engineering and computer science and a member of CSAIL.
Generative AI for video conferencing
Vibhaalakshmi Sivaraman SM ’19, a PhD candidate in electrical engineering and computer science who is a member of CSAIL’s Network and Mobile Systems Group, is developing a generative technology, Gemino, to facilitate video conferencing in high-latency, low-speed network environments. Gemino is a neural compression system for video conferencing that overcomes robustness issues and computational complexity challenges that limit current face-image synthesis models. This technology can enable sustainable video conference calls in regions and scenarios that cannot reliably support video calls today. Sivaraman is advised by Mohamed Alizadeh, an associate professor of electrical engineering and computer science at MIT and a member of CSAIL.
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