Tom Purcell was born and grew uin New Jersey, in the suburbs of New York City. After graduating he joined New York University as an undergraduate where he received his B.S. in Chemistry, before getting his Ph.D. at Northwestern University under Prof. Tamar Seideman. During his Ph.D. he developed classical and semi-classical methods to describe the coupling between quantum emitters and plasmonic nanoparticles using the finite-difference time-domain and Maxwell Liouville algorithms. After his Ph.D. he joined the Theory Department now the NOMAD Laboratory) of the Fritz-Haber-Insitut der Max-Plack-Gesellschaft FHI) as an Alexander von Humboldt Postdoctoral Fellow, and later became a GrouLeader in the same department. At the FHI, Tom focused on creating high-throughput computational workflows and machine learning models for understanding thermal transport properties of materials. As a part of these efforts he developed and maintained the FHI-vibes and SISSO+ software packages, for modelling the vibrational properties of a material and finding analytical expressions for a material’s properties using the sure-independence screening and sparsifying operator, respectively. He then joined the Chemistry and Biochemistry Department at the University of Arizona in January 2024 to start his own grouon explainable AI for materials discovery.