The MIT-Pillar AI Collective has announced six fellows for the spring 2024 semester. With the support of this system, the doctoral students, who’re in the ultimate 12 months of a master’s or PhD program, will conduct research within the areas of AI, machine learning and data science with the aim of commercializing their innovations.

Launched in 2022 by MIT’s School of Engineering and Pillar VC, the MIT-Pillar AI Collective supports faculty, postdocs, and students conducting research in AI, machine learning, and data science. Supported by a present from Column VC and managed by the MIT Deshpande Center for Technological InnovationThe mission of this system is to advance research toward commercialization.

The Spring 2024 MIT Pillar AI Collective Fellows are:

Yasmeen AlFaraj

Yasmeen AlFaraj is a PhD candidate in chemistry considering applying data science and machine learning to the design of soppy materials to enable next-generation sustainable plastics, rubber and composites. In particular, she applies machine learning to the event of novel molecular additives to enable the cost-effective production of chemically deconstructable thermosets and composites. AlFaraj’s work has led to the invention of scalable, translatable latest materials that might address thermoset plastic waste. As a Pillar Fellow, she’s going to drive the market launch of this technology, initially specializing in wind turbine blade manufacturing and conformal coatings. Through the Deshpande Center for Technological Innovation, AlFaraj is leading a team developing a spinout focused on recyclable versions of existing high-performance thermosets by incorporating small amounts of a degradable comonomer. Additionally, she participated within the National Science Foundation Innovation Corps program and recently accomplished the Clean Tech Open, where she focused on improving her marketing strategy, analyzing potential markets, securing an entire IP portfolio, and contacting potential funders . AlFaraj earned a BS in chemistry from the University of California, Berkeley.

Ruben Castro Ornelas ’22

Ruben Castro Ornelas is a PhD student in mechanical engineering who’s keen about the long run of multi-purpose robots and the event of the hardware to make use of them with AI control solutions. Combining his expertise in programming, embedded systems, machine design, reinforcement learning, and AI, he designed a dexterous robotic hand able to performing useful on a regular basis tasks without sacrificing size, durability, complexity, or simulability. Ornelas’ modern design holds significant business potential for domestic, industrial and healthcare applications as it might be customized to accommodate all the pieces from kitchenware to delicate items. As a Pillar Fellow, he’ll give attention to identifying potential business markets, determining the optimal approach to business-to-business sales, and identifying key advisors. Ornelas was co-director of StartLabs, a student entrepreneurship club at MIT, where he earned a bachelor’s degree in mechanical engineering.

Keeley Erhardt ’17, MNG ’17

Keeley Erhardt is a doctoral candidate in media studies and studies whose research interests lie within the transformative potential of AI in network evaluation, particularly for entity correlation and hidden link detection inside and between domains. She has developed machine learning algorithms to discover and track temporal relationships and hidden signals across large networks, uncovering online influence campaigns from multiple countries. She has similarly demonstrated the usage of graph neural networks to discover coordinated cryptocurrency accounts by analyzing financial time series data and transaction dynamics. As a Pillar Fellow, Erhardt will pursue the potential business applications of her work, equivalent to uncovering fraud, propaganda, money laundering and other covert activities in finance, energy and national security. She has accomplished internships at Google, Facebook and Apple and worked in software development at several tech unicorns. Erhardt earned an MEng in electrical engineering and computer science and a BS in computer science, each from MIT.

Vineet Jagadeesan Nair SM ’21

Vineet Jagadeesan Nair is a PhD student in mechanical engineering. The focus of his research is on modeling power grids and designing power markets to integrate renewable energy, batteries and electric vehicles. He could be very considering developing computational tools to combat climate change. As a Pillar Fellow, Nair will research the appliance of machine learning and data science to energy systems. Specifically, he’ll experiment with approaches to enhance the accuracy of forecasting electricity demand and provide with high spatiotemporal resolution. In collaboration with Project Tapestry @ Google Nair’s work could help realize future grids with high penetration of renewable energy and other clean, distributed energy resources. Outside of academia, Nair is energetic in entrepreneurship and most recently helped organize the MIT Global Startup Workshop 2023 in Greece. He earned an MS in Computer Science and Engineering from MIT, an MPhil in Energy Technologies from the University of Cambridge as a Gates Scholar, and a BS in Mechanical Engineering and a BA in Economics from the University of California, Berkeley.

Mahdi Ramadan

Mahdi Ramadan is a doctoral candidate in brain and cognitive sciences whose research interests lie on the intersection of cognitive science, computational modeling, and neural technologies. His work uses novel unsupervised methods to learn and generate interpretable representations of neural dynamics, leveraging recent advances in AI, particularly contrastive and geometric deep learning techniques able to understanding the latent dynamics underlying neural processes. uncover with high accuracy. As a Pillar Fellow, he’ll use these methods to higher understand dynamic models of muscle signals for generative motor control. By complementing current spinal prostheses with generative AI motor models that may streamline, speed up and proper limb muscle activations in real time, and potentially using multimodal vision-language models to infer patients’ higher-level intentions, Ramadan goals to realize one Building truly scalable, accessible and powerful business neuroprosthetics. Ramadan’s entrepreneurial experience includes serving as co-founder of UltraNeuro, a neurotechnology startup, and co-founder of Presizely, a pc vision startup. He earned a BS in neurobiology from the University of Washington.

Rui (Raymond) Zhou

Rui (Raymond) Zhou is a PhD student in mechanical engineering whose research focus is on multimodal AI for engineering design. As a Pillar Fellow, he’ll further develop models that might enable designers to translate information in any modality or combination of modalities into comprehensive 2D and 3D designs, including parametric data, component visualizations, assembly diagrams and sketches. These models could also optimize existing human designs to realize goals equivalent to improving ergonomics or reducing the drag coefficient. Ultimately, Zhou desires to translate his work right into a software-as-a-service platform that redefines product design across sectors, from automotive to consumer electronics. His efforts have the potential to not only speed up the design process but in addition reduce costs, opening the door to unprecedented levels of customization, idea generation and rapid prototyping. Beyond his academic pursuits, Zhou founded UrsaTech, a startup that integrates AI into education and technical design. He earned a BS in electrical engineering and computer science from the University of California, Berkeley.

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