معرفی
Zachary Ulissi is an Adjunct Professor in the Department of Chemical Engineering at Carnegie Mellon University. He holds a B.S. in Physics and B.E. in Chemical Engineering from the University of Delaware (2009), an M.A.S. in Mathematics from the University of Cambridge (2010), and a Ph.D. in Chemical Engineering from MIT (2015). His research applies systems engineering and machine learning to nanoscale carbon nanotube devices, catalyst networks, and electrochemical reduction processes.
His core research focuses on catalysis, surface science, energy systems, and machine learning applications in chemical engineering. Key areas include developing computational methods to optimize catalyst reactions for sustainable fuel production and designing nanoscale sensors.
Dr. Ulissi has contributed to projects funded by the Scott Institute for Energy Innovation, including green chemistry initiatives aimed at reducing industrial emissions. He actively engages in academic discourse on energy innovation and reaction kinetics, as noted in Engineering & Technology Magazine.
His work emphasizes cross-disciplinary collaboration, particularly in integrating machine learning with chemical engineering to address energy challenges.
