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 machine learning and 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.

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

  • Wimmer Faculty Fellow for the Development of Teaching, 2018
  • Team Science Award, DOE EFRC Hub PI Meeting, 2017
  • Department of Energy Computational Science Graduate Fellow (DOE CSGF), 2010-2014
  • National Science Foundation Graduate Research Fellowship, 2009-2010


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

Seoin Back

Post-Doc (2018-)

My research interest is a novel catalyst design from density functional theory calculations and machine learning. During my PhD at KAIST, I worked on nanoparticle and single atom catalysts for CO2 reduction. After my PhD, I joined Stanford as a postdoctoral researcher where I focused on the design of active and selective catalysts for O2 reduction and H2O oxidation. My research goal at Prof. Ulissi’s group is to apply machine learning techniques to exhaustively search a broad chemical space to develop groundbreaking catalysts.


  • Postdoc, Chemical Engineering, Stanford University, 2017-2018
  • PhD, Energy, Environment, Water and Sustainability (EEWS), KAIST, 2013-2017
  • MS, Energy, Environment, Water and Sustainability (EEWS), KAIST, 2012-2013
  • BS, Chemical Engineering, Hanyang University, 2008-2011

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.


  • 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)

Muhammed Shuaibi

PhD Student (2022)

I completed my bachelor’s and master’s degree at Illinois Institute of Technology. During my time there I took part in various interprofessional projects. Motivated by the global crisis of malnutrition, I was involved in the development of a pilot scale, three-phase reactor to accelerate the growth of microgreens with Dr. Fouad Teymour. Upon graduation, I joined the US EPA and spent much of my time conducting various facility inspections and researching and modeling particulate matter emissions from the metallurgical industry. Hoping to contribute to solving some of society’s energy and environmental problems, I joined CMU’s PhD program to gain the skills and mindset necessary to accomplish such feats.

Outside of work I enjoy spending time with family and friends. I am extremely competitive when it comes to sports and board games – my favorites being volleyball and Settlers of Catan. My wife and I love exploring cities, parks, and new food places.


  • Master of Chemical Engineering, Illinois Institute of Technology, May 2017
  • B.S. in Chemical Engineering, Illinois Institute of Technology, May 2017
  • Environmental Engineer, U.S. Environmental Protection Agency, Jan. 2017 – Aug. 2018

Email mshuaibi (at)

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! 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.


  • 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)

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 functional 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.


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

Email junwoony (at)

Shiv Rekhi

MS Student (2019)

I completed my Bachelors degree in Chemical Engineering from the coastal city of Chennai in India. During my undergrad my field of interest gradually shifted from environmental Chemical Engineering to Pharmaceuticals and development of drug delivery materials. Currently I amworking on Molecular Modelling of Lipid Nanoparticles. Though a Chemical Engineer by profession, I am a performer at heart, enjoying performing everything from comedy routines to gigs with bands as a bass guitarist. In my time away from books (or in this case computers), Ican be found listening to extremely loud music, playing his guitar at home or on a boat for a peaceful sail.

Katsuyuki Tomita

MS Student (2019)

I completed my bachelor’s and master’s at The University of Tokyo. My research was experimental study into interaction between low dimensional semiconductor materials and photon. After graduation, I joined Nippon Steel & Sumitomo Metal Corporation and worked in R&D division for 7 years. I worked on variety of heat and energy related projects both experimentally and computationally. My goal here is to discover efficient material to reduce carbon dioxide using machine learning technique.

Outside of school, I enjoy snowboarding, hiking and reading books. I also like to travel and enjoy new foods, culture and scenery.


  • Nippon Steel & Sumitomo Metal Corporation, 2011~
  • M.E in Applied physics from The University of Tokyo, 2011
  • B.E in Applied physics from The University of Tokyo, 2009

Email katsuyut (at)

Qingyang(Ernest) Zhang

MS Student (2019)

I graduated in May 2018 from Haverford College as a Chemistry major. Haverford College is a small liberal arts college in Philadelphia which produced few engineers, but I never deviated far from the engineering path ever since my high school years in Beijing. Mentored by Prof. Joshua Schrier, I built my thesis by quantifying the improvements that new algorithms and failed reactions (on top of successful ones) can bring to machine learning predictions of untested reactions; I also explored the scalability of each algorithm.

I can be called upon to balance the team numbers in a basketball game, though you might see me taking advantage of the college swimming pool more often. I often spend my vacations hiking or diving. I like to divide the rest of my time studying and practicing both computational and natural languages.


  • B.S. in Chemistry with minor in Mathematics, Haverford College, 2018.
  • Summer research at Tsinghua University, 2017
  • Intern at Roche Shanghai, 2016

Email qingyanz (at)

Amish Chovatiya

MS Student (2019)

I completed my bachelors in Chemical Engineering from Ahmedabad University in May 2018 as a part of first Chemical Engineering batch of the university. I worked on Aspen Plus simulation of catalytic methane decomposition reaction during my final year there. Modern computational techniques used in chemical engineering fascinate me. Catalysis in energy applications is something that always interests me and same are the reason for me to join Ulissi Lab.

Music is something that keeps me going. Apart from this, I enjoy reading and playing badminton and volleyball (does not mean I’m very good at sports!).


  • B.Tech in Chemical Engineering,Ahmedabad University, India, May 2018

Email achovati (at)

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)

Hyukjae (Alex) Kwark

Undergraduate Student (2020)

Hyukjae (Alex) Kwark

I am currently a undergraduate student in CMU chemical engineering. My current interest is in Machine Learning and catalysts. I’ve been currently working on interaction energy calculations with DNA strands and MoS2 surfaces through MD simulations. I joined the Ulissi lab to see how machine learning techniques can be applied to solve chemistry and engineering problems. I am hoping to learn more about the actual applications of coding to accelerate engineering problem solving. Outside of academics, I like play league, play and watch basketball. I also enjoy dancing, and was a member CMU KPDC until last year.

Qi (Rui) Chen

Undergraduate Student (2021)

I am an undergraduate student in Chemical Engineering at Carnegie Mellon University. In addition, I am also pursuing a minor in computer science. I joined Professor Ulissi’s Group because I was interested in using machine learning to do research in chemical engineering. Currently, I am working with Kevin on using machine learning to predict weather or not density functional theory calculations will fail prior to running them. Outside of school, I enjoy playing music and spending time with my friends.

Email ruiqic (at)

Ketong Chen

Undergraduate Student (2022)

I am an upcoming sophomore in Chemical Engineering Department. I am passionate about my major, and currently trying to explore more about the numerous fields under chemical engineering. I appreciate the opportunity to join the Ulissi Lab and get some hands-on experience to combine machine learning and catalysis. Through this experience, I hope to do some useful calculations and help decide the ideal metal catalyst for future use. During my high school, I also had previous chemistry research experience on synthesis and characterization of ferrocene coumarin-chalcone hybrid.

Beyond research, I joined CMU chemE car, and ARCC a cappella. Music is a necessity in my life. I love spending a sunny Sunday morning singing, playing musical instruments such as the piano, guitar, ukulele, drums, or just simply listening to music. I love expressing emotions through music. I enjoyed creating music with friends in my band as well in my high school, and really hope I can join a band here in CMU.

Email ketongc (at)

Group Alumni

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.


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

Email zongqiay (at)

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.


  • 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)