People
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.
Office
A207A Doherty Hall
Phone
412.268.9517
Fax
412.268.7139
Email
zulissi@andrew.cmu.edu
Google Scholar
Zachary Ulissi
Websites
Research Group

Designing New Molecules with Machine Learning

Education

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

Media mentions


Jayan and Ulissi named Scott Institute Fellows

MechE’s B. Reeja Jayan and ChemE’s Zack Ulissi have been named Wilton E. Scott Institute for Energy Innovation Energy Fellows.

Department of Energy

DOE awards Litster and partners $3.7M for fuel cell tech research

MechE’s Shawn Litster is involved in two new projects on fuel cells for heavy-duty vehicles, which are both funded by the Department of Energy (DOE).

CMU Engineering

CMU among first to pilot brand new supercomputer

In 2020, the National Energy Research Scientific Computing Center will celebrate the arrival of the Perlmutter supercomputer—and ChemE’s Zack Ulissi will be one of the first to use it.

College of Engineering’s Celebration of Education Awards announced

Congratulations to the College of Engineering’s 2019 recipients of the Celebration of Education Awards, which recognize individuals who exemplify excellence in teaching, advising, and mentoring.

Brown University

Ulissi group granted $500K for work on machine learning

ChemE’s Ulissi group was recently awarded $500K through the Department of Energy for their work on machine learning.

CMU Engineering

Accelerating electrocatalyst discovery

Chemical engineering researchers have developed a machine learning system to search through millions of intermetallics to discover new materials for electrocatalysis.