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recordings, developing and prototyping sensing hardware, and executing structured data collection protocols. The candidate will contribute to experiments involving nerve interfacing, signal acquisition, and
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for understanding how AI-enabled control, optimization, and market design can support large-scale decarbonization, grid modernization, and the integration of distributed and flexible energy resources. Research topics
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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include conducting survival surgeries in rodents, performing electrophysiological recordings, developing and prototyping sensing hardware, and executing structured data collection protocols. The candidate
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magnetic response. Development of machine learning methods for exchange-correlation functionals. Current work in the group is focused on improvements and performance optimizations for the recently developed
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. Responsibilities include conceptualizing and implementing statistical and structural models, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis
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, computer science, architecture, and engineering to develop scalable, data-informed solutions in sustainable design, construction, and energy management. The Cluster aims to modernize—and ultimately revolutionize