Zachary Ulissi

Assistant Professor of Chemical Engineering

Professor Ulissi joined Carnegie Mellon University in 2017, after doing his PhD at MIT and post-doc at Stanford. His 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 Strano and Richard Braatz. Prof. Ulissi did his postdoctoral work at Stanford with Jens 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. The Ulissi group builds on this foundation to model, understand, and design nanoscale interfaces using modern predictive methods to guide detailed molecular simulations.

In his free time, Prof. Ulissi enjoys the outdoors and is a competitive cyclist, mostly with results at the collegiate cycling level. He also enjoys cooking and traveling.

Education
Ph.D. in Chemical Engineering from the Massachusetts Institute of Technology in 2015
M.A.St. in Applied Mathematics from Churchill College, University of Cambridge 2010
B.E. in Chemical Engineering, B.S. in Physics from the University of Delaware, 2009

Honors and Awards

  • Department of Energy Computational Science Graduate Fellow (DOE CSGF), 2010-2014
  • National Science Foundation Graduate Research Fellowship, 2009-2010

Contact

Room A207A
Doherty Hall
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213
Email: zulissi (at) andrew.cmu.edu
Tel: +1 412-268-9517

Kevin Tran

PhD Student (2021)

I create and use automated, active machine learning workflows to perform density functional theory (DFT) simulations. I then use these DFT simulations to screen for new catalysts for various applications, such as carbon dioxide reduction or hydrogen evolution. My goal is to discover catalysts that are active, efficient, selective, stable, and cheap so that we can ultimately enable large-scale production of solar fuels.

But more importantly, I enjoy being with family, playing with my baby nieces, cooking/eating, shooting pool, playing ultimate frisbee, doing yoga, rock climbing, and playing racquetball.

Background:

  • Graduated from University of Delaware, 2011 (Advisor: Babatunde Ogunnaike)
  • Process Engineer (PTFE Paste Processing) from 2011-2014 at W.L. Gore & Associates
  • Process Engineer (Bioresorbable Polymer Synthesis) from 2014-2016 at W.L. Gore & Associates

Email ktran (at) andrew.cmu.edu

Pari (Aini) Palizhati

PhD Student (2022)

I completed my B.S. in Chemical Engineering at North Carolina State University (Go Pack!). When I was an undergraduate there, I was heavily involved in AIChE and conducted research in Dr. Chase Beisel’s lab for two years. In addition, I was also given opportunities to spend all my summers in the industry. All of these experiences provided me with the privilege to learn from many incredible mentors and inspired me to get into graduate school. CMU was the perfect next step for me (fun fact! My undergraduate academic advisor Dr. Lisa Bullard also graduated from here).

Outside of school and research, I am part of the CMU Ballroom Dance Competition Team, and I love it! It has become a great way for me to de-stress, learn something new, and meet some of the most interesting and unique people outside of my daily routine. Other than that, I love crafting and spending time in nature (my favorite activity is hiking in the mountains). Coffee, cupcakes, and TV Show “Friends” are always my guilty pleasures.

Background:

  • Graduated from North Carolina State University, May 2017 (Advisor: Dr. Chase Beisel)
  • Process Optimization Intern (Fujifilm Diosynth, Summer 2017)
  • Project Management Intern (Merck, Summer 2016)
  • Process Development Intern (PotashCorp, summer 2015)
  • REU (Iowa State University, Summer 2014)

Email apalizha (at) andrew.cmu.edu

Junwoong Yoon

PhD Student (2022)

During my undergraduate at UC Berkeley, I worked on synthesizing metal nanoparticle catalysts that enhance catalytic performance of various chemical reactions under the supervision of Prof. Somorjai. After graduating from UC Berkeley, I became a retail trader and studied stock trading strategies which drew my attention to machine learning. Therefore my experience in catalysis research and interest in machine learning led me to pursue a PhD program at CMU.

I joined Prof. Ulissi’s group with a deep interest in machine learning and its applications in chemical engineering field. My research interest is to study machine learning techniques to increase the speed and efficiency of density function theory (DFT) calculations. I believe this work will enable us to study more complex chemical problems that require high-throughput calculations and large databases.

I spend my leisure time on watching documentaries. I also love to travel around and take pictures of places and landscapes.

Background:

  • B.S in Chemical Engineering from University of California, Berkeley 2015

Email junwoony (at) andrew.cmu.edu

Zong Qian (Max) Yu

MS Student (2018)

I completed my B.S. chemical engineering in University of Alberta in 2017. During my undergraduate study, I have worked on studies related to halides affecting coking formation during hydrocarbon cracking process as well as surface tensions on oil/potash interface. I came to CMU hoping to approach the field of engineering from coding. Based on my past experience, I entered professor Ulissi group hoping to further study catalysis through modeling and calculations.

I enjoy outdoor activities such as Frisbee, kayaking, and snowboarding. I have played violin for a very long time and recently picked up the ukulele.

Background:

  • B.S. in Chemical Engineering, University of Alberta, 2017

Email zongqiay (at) andrew.cmu.edu

Wen (Amber) Zhong

MS Student (2018)

During my undergraduate research at Purdue University, I worked on simulated moving bed which implanted chromatography separation. The summer after graduating, I joined Novartis as a R&D intern studying gene modification using CRISPR Cas9. Both experience heavily relied on built up software, which inspired me to explore the field in computational modeling and process system engineering. This inspiration led me joining the MS program at CMU.

For relaxation, I enjoy listening to Broadway musicals and watching late night shows. I am also a big fun of detective stories. Most important, I enjoy spending time with my friend.

Background:

  • B.S. in Chemical Engineering, Purdue University, May 2017
  • R&D Intern (Novartis, Summer 2017)
  • R&D Intern (Novozymes Biotechnology, Summer 2016)

Email wzhong1 (at) andrew.cmu.edu

Nianhan (Kaylee) Tian

Undergraduate Student (2019)

I joined the Ulissi Lab being interested in utilizing Machine-learning approaches to accelerate materials discovery. My research builds on a dataset of adsorption energies to discover and predict new catalyst. I use variational autoencoders to learn efficient representations of catalyst surfaces and make more accurate predictions about target properties given structural information. My goal is to make more accurate predictions on catalysts’ performance than existing variational autoencoders, by reducing the mean absolute error.

Outside of school, I am a member of CMU ChemE Car, a food lover and a passionate baker. I really enjoy spending time in the kitchen, creating and testing my own dessert recipes. Other than that, I’m obsessed with doing CrossFit and taking photos.

Email nianhant (at) andrew.cmu.edu