Six MIT students chosen for MIT-Pillar AI Collective Fellowship in spring 2024

The MIT-Pillar AI Collective has announced a group of six fellows for the spring 2024 semester. These graduate students, who are in the final year of their master’s or PhD programs, will be conducting research in the fields of AI, machine learning, and data science with the goal of commercializing their innovations.

The MIT-Pillar AI Collective was launched in 2022 by MIT’s School of Engineering and Pillar VC. This program provides support to faculty, postdocs, and students who are engaged in research related to AI, machine learning, and data science. The mission of the program, which is administered by the MIT Deshpande Center for Technological Innovation and made possible by a gift from Pillar VC, is to advance research that can be commercialized.

The spring 2024 MIT-Pillar AI Collective Fellows are as follows:

Yasmeen AlFaraj

Yasmeen AlFaraj is a chemistry PhD candidate who is focused on the application of data science and machine learning to the design of soft materials. Her research aims to enable the development of sustainable plastics, rubber, and composite materials. AlFaraj’s work has led to the discovery of new materials that could help address plastic waste. As a Pillar Fellow, she will work on bringing this technology to market, starting with wind turbine blade manufacturing and conformal coatings. AlFaraj earned a BS in chemistry from the University of California at Berkeley.

Ruben Castro Ornelas

Ruben Castro Ornelas is a mechanical engineering PhD student who is passionate about multipurpose robots and designing AI-controlled hardware for them. He has designed a dexterous robotic hand that can perform various tasks without sacrificing size or durability. This design has potential applications in domestic, industrial, and health-care settings. As a Pillar Fellow, Castro Ornelas will focus on identifying commercial markets and developing business-to-business sales strategies. He previously co-directed StartLabs, an undergraduate entrepreneurship club at MIT, where he earned a BS in mechanical engineering.

Keeley Erhardt

Keeley Erhardt is a media arts and sciences PhD candidate who is interested in the transformative potential of AI in network analysis. Her research involves using machine learning algorithms to uncover hidden signals and correlations in large-scale networks. Erhardt’s work has applications in detecting fraud, propaganda, and other covert activities. As a Pillar Fellow, she will explore the commercial potential of her research in sectors such as finance, energy, and national security. Erhardt has interned at Google, Facebook, and Apple and holds software engineering roles at multiple tech unicorns. She earned an MEng in electrical engineering and computer science and a BS in computer science, both from MIT.

Vineet Jagadeesan Nair

Vineet Jagadeesan Nair is a mechanical engineering PhD candidate who focuses on modeling power grids and designing electricity markets to integrate renewables and electric vehicles. He is interested in using machine learning and data science to improve the accuracy of electricity demand and supply forecasting. Nair’s work could contribute to the development of grids with high penetrations of renewable energy sources. He is also collaborating with Project Tapestry @ Google X to improve the speed and accuracy of high-fidelity simulations. Nair is active in entrepreneurship and helped organize the 2023 MIT Global Startup Workshop. He earned an MS in computational science and engineering from MIT, an MPhil in energy technologies from Cambridge University, and a BS in mechanical engineering and a BA in economics from the University of California at Berkeley.

Mahdi Ramadan

Mahdi Ramadan is a brain and cognitive sciences PhD candidate who is interested in the intersection of cognitive science, computational modeling, and neural technologies. His research utilizes AI techniques to uncover patterns in neural dynamics and develop better understanding of motor control. Ramadan’s work has applications in the development of neuroprosthetics. As a Pillar Fellow, he aims to build commercial neuroprosthetics that can enhance motor control in real time. He has entrepreneurial experience as the co-founder of UltraNeuro and Presizely. Ramadan earned a BS in neurobiology from the University of Washington.

Rui (Raymond) Zhou

Rui (Raymond) Zhou is a mechanical engineering PhD candidate who focuses on multimodal AI for engineering design. He is working on models that can translate information from various modalities into comprehensive designs. These models could optimize existing designs and redefine the product design process across sectors. Zhou has entrepreneurial experience as the founder of UrsaTech. He earned a BS in electrical engineering and computer sciences from the University of California at Berkeley.

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