Ulissi joined Carnegie Mellon University in 2016. He received his B.S. in physics and B.E. in chemical engineering from the University of Delaware in 2009, a master's of advanced studies in mathematics from the University of Cambridge in 2010, and a Ph.D. in chemical engineering from MIT in 2015. His thesis research at MIT focused on the the applications of systems engineering methods to understanding selective nanoscale carbon nanotube devices and sensors under the supervision of Michael S. Strano and Richard Braatz. Ulissi was then a postdoctoral fellow at Stanford with Jens K. Nørskov where he worked on machine learning techniques to simplify complex catalyst reaction networks, applied to the electrochemical reduction of N2 and CO2 to fuels.
Designing New Molecules with Machine Learning
2015 Ph.D., Chemical Engineering, Massachusetts Institute of Technology
2010 MA, Applied Mathematics, Cambridge University
2009 BE, Chemical Engineering, University of Delaware
2009 BS, Physics, University of Delaware
Scott Institute announces 2022 seed grants for five projects
The Scott Institute has announced its latest seed grant awards worth $1.42 million to five research projects led by CMU Engineering faculty.
Engineering & Technology Magazine
Ulissi quoted on importance of reaction kinetics
ChemE’s Zachary Ulissi spoke with Engineering & Technology Magazine about how reaction kinetics factor in the search for a catalyst to replace platinum in experiments.
New data set accelerates search for renewable energy sources
As part of the Open Catalyst Project collaboration, Meta AI and Carnegie Mellon University’s (CMU) Department of Chemical Engineering have announced an entirely new data set focused on oxide catalysts for the Oxygen Evolution Reaction (OER), a critical chemical reaction used in green hydrogen fuel production via wind and solar energy.
Ulissi featured in Physics World
A feature in Physics World explains how Assistant Professor Zachary Ulissi and his group have developed a deep reinforcement learning (DRL) program, dubbed CatGym, used to find the best surface atom configurations for a given chemical reaction.
Berg Scholars, Chen and Pavlat will present posters at AIChE Conference
ChemE’s 6th Annual John Berg Undergraduate Research Symposium Poster Session winners, Ketong Chen and Benjamin Pavlat, earned the designation of Berg Scholars. They will travel on an all-expenses-paid trip to Boston for the AIChE Annual Student Conference and participate in its Undergraduate Student Poster Competition.
2021 Engineering faculty award winners selected
Congratulations to the 2021 CMU Engineering Faculty Awards winners.
Ulissi quoted on AI research
ChemE’s Zack Ulissi was quoted on his AI research with Facebook in multiple outlets, including CNBC, CNET, Engadget, Yahoo, Fortune, VentureBeat, and more.
Ulissi and Facebook AI create world’s largest catalysis dataset
Zack Ulissi and Facebook AI Research (FAIR) have created the Open Catalyst Project, the largest dataset of its kind, to accelerate the discovery of new catalysts for use in renewable energy storage.
American Institute of Chemical Engineers (AIChE)
Ulissi recognized for outstanding research
ChemE’s Zachary Ulissi was named one of AIChE’s 35 Under 35 for his work on the development and application of high-throughput simulation methods, active learning methods, and machine learning models for surface science and catalysis.
Ulissi receives 3M award
ChemE’s Zack Ulissi received a 3M Non-tenured Faculty Award.
Ulissi quoted on material design
ChemE’s Zach Ulissi was quoted in Wired on material design.
AI helps researchers up-cycle waste carbon
A collaboration between CMU ChemE and the University of Toronto has produced a record-setting catalyst for CO2-to-ethylene conversion.