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HomeArtificial IntelligenceMIT-Pillar AI Collective pronounces first seed grant recipients | MIT Information

MIT-Pillar AI Collective pronounces first seed grant recipients | MIT Information



The MIT-Pillar AI Collective has introduced its first six grant recipients. College students, alumni, and postdocs engaged on a broad vary of matters in synthetic intelligence, machine studying, and knowledge science will obtain funding and help for analysis tasks that might translate into commercially viable merchandise or corporations. These grants are meant to assist college students discover business purposes for his or her analysis, and ultimately drive that commercialization via the creation of a startup.

“These great college students and postdocs are engaged on tasks which have the potential to be actually transformative throughout a various vary of industries. It’s thrilling to suppose that the novel analysis these groups are conducting may result in the founding of startups that revolutionize all the things from drug supply to video conferencing,” says Anantha Chandrakasan, dean of the College of Engineering and the Vannevar Bush Professor of Electrical Engineering and Laptop Science.

Launched in September 2022, the MIT-Pillar AI Collective is a pilot program funded by a $1 million present from Pillar VC that goals to domesticate potential entrepreneurs and drive innovation in areas associated to AI. Administered by the MIT Deshpande Heart for Technological Innovation, the AI Collective facilities in the marketplace discovery course of, advancing tasks via market analysis, buyer discovery, and prototyping. Graduate college students and postdocs supported by this system work towards the event of minimal viable merchandise.

“Along with funding, the MIT-Pillar AI Collective gives grant recipients with mentorship and steering. With the fast development of AI applied sciences, this sort of help is essential to make sure college students and postdocs are in a position to entry the sources required to maneuver rapidly on this fast-pace setting,” says Jinane Abounadi, managing director of the MIT-Pillar AI Collective.

The six inaugural recipients will obtain help in figuring out key milestones and recommendation from skilled entrepreneurs. The AI Collective assists seed grant recipients in gathering suggestions from potential end-users, in addition to getting insights from early-stage traders. This system additionally organizes group occasions, together with a “Founder Talks” speaker collection, and different team-building actions.   

“Every considered one of these grant recipients reveals an entrepreneurial spirit. It’s thrilling to offer help and steering as they begin a journey that might at some point see them as founders and leaders of profitable corporations,” provides Jamie Goldstein ’89, founding father of Pillar VC.

The primary cohort of grant recipients embrace the next tasks:

Predictive question interface

Abdullah Alomar SM ’21, a PhD candidate learning electrical engineering and laptop science, is constructing a predictive question interface for time collection databases to higher forecast demand and monetary knowledge. This user-friendly interface can assist alleviate a few of the bottlenecks and points associated to unwieldy knowledge engineering processes whereas offering 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 medication

Simon Axelrod, a PhD candidate learning chemical physics at Harvard College, is combining AI with physics simulations to design light-activated medication that might scale back unintended effects and enhance effectiveness. Sufferers would obtain an inactive type of a drug, which is then activated by mild in a particular space of the physique containing diseased tissue. This localized use of photoactive medication would decrease the unintended effects from medication concentrating on wholesome cells. Axelrod is growing novel computational fashions that predict properties of photoactive medication with excessive velocity and accuracy, permitting researchers to concentrate on solely the highest-quality drug candidates. He’s suggested by Rafael Gomez-Bombarelli, the Jeffrey Cheah Profession Growth Chair in Engineering within the MIT Division of Supplies Science and Engineering. 

Low-cost 3D notion

Arjun Balasingam, a PhD scholar in electrical engineering and laptop science and a member of the Laptop Science and Synthetic Intelligence Laboratory’s (CSAIL) Networks and Cellular Methods group, is growing a know-how, referred to as MobiSee, that permits real-time 3D reconstruction in difficult dynamic environments. MobiSee makes use of self-supervised AI strategies together with video and lidar to offer low-cost, state-of-the-art 3D notion on client cell units like smartphones. This know-how may have far-reaching purposes throughout blended actuality, navigation, security, and sports activities streaming, along with unlocking alternatives for brand spanking new real-time and immersive experiences. He’s suggested by Hari Balakrishnan, the Fujitsu Professor of Laptop Science and Synthetic Intelligence at MIT and member of CSAIL.

Sleep therapeutics

Guillermo Bernal SM ’14, PhD ’23, a latest PhD graduate in media arts and sciences, is growing a sleep therapeutic platform that will allow sleep specialists and researchers to conduct sturdy sleep research and develop remedy plans remotely, whereas the affected person is comfy of their house. Referred to as Fascia, the three-part system consists of a polysomnogram with a sleep masks type issue that collects knowledge, a hub that permits researchers to offer stimulation and suggestions by way of olfactory, auditory, and visible stimuli, and an internet portal that permits researchers to learn a affected person’s alerts in actual time with machine studying evaluation. Bernal was suggested by Pattie Maes, professor of media arts and sciences on the MIT Media Lab.

Autonomous manufacturing meeting with human-like tactile notion

Michael Foshey, a mechanical engineer and challenge supervisor with MIT CSAIL’s Computational Design and Fabrication Group, is growing an AI-enabled tactile notion system that can be utilized to provide robots human-like dexterity. With this new know-how platform, Foshey and his staff hope to allow industry-changing purposes in manufacturing. At the moment, meeting duties in manufacturing are largely executed by hand and are usually repetitive and tedious. Consequently, these jobs are being largely left unfilled. These labor shortages could cause provide chain shortages and will increase in the price of manufacturing. Foshey’s new know-how platform goals to deal with this by automating meeting duties to cut back reliance on guide labor. Foshey is supervised by Wojciech Matusik, MIT professor {of electrical} engineering and laptop science and member of CSAIL.  

Generative AI for video conferencing

Vibhaalakshmi Sivaraman SM ’19, a PhD candidate in electrical engineering and laptop science who’s a member of CSAIL’s Networking and Cellular Methods Group, is growing a generative know-how, Gemino, to facilitate video conferencing in high-latency and low-bandwidth community environments. Gemino is a neural compression system for video conferencing that overcomes the robustness issues and compute complexity challenges that restrict present face-image-synthesis fashions. This know-how may allow sustained video conferencing calls in areas and eventualities that can’t reliably help video calls right this moment. Sivaraman is suggested by Mohammad Alizadeh, MIT affiliate professor {of electrical} engineering and laptop science and member of CSAIL. 

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