Philip Harris

Philip Harris is an Associate Professor of Physics at the Massachusetts Institute of Technology (MIT), specializing in particle and nuclear physics experiments. He leads research on dark matter detection and Higgs boson properties, leveraging machine learning and deep learning techniques. His affiliations include the Laboratory for Nuclear Science and Particle Physics Collaboration (PPC). He also serves as experimental coordinator of the Institute for AI and Fundamental Interactions (IAIFI) and deputy director of the A3D3 Institute.

Education: B.S. in Physics from Caltech (2005), Ph.D. from MIT (2011). Research focuses on real-time FPGA-based systems, jet substructure in heavy ion collisions, and AI-driven analysis of LHC data. He co-founded the Fast Machine Learning Organization and pioneered AI strategies for Higgs measurements.

Awards include the 2023 MIT Teaching with Digital Technology Award and 2021 DOE Early Career Award. His work bridges particle physics with cutting-edge AI, emphasizing open data and collaborative tools like Jupyter notebooks.

Key initiatives include the Fast Machine Learning Lab and multi-messenger astronomy projects integrating gravitational wave detection with particle physics. He advocates for advancing AI in fundamental physics through interdisciplinary collaboration.