Kaylee receives a ChESS summer fellowship!

Congratulations to Kaylee for winning a ChESS fellowship to support her research in the group this summer. Her project is titled “Variational Autoencoders to Learn Efficient Representations of Catalyst Surfaces”.

Pari receives a PPG fellowship!

Pari received a departmental PPG fellowship for 2017-2018, courtesy of the PPG Foundation. Congratulations!

Talk at MRS "AI in Materials" Symposium

Great turnout (packed rooms) for a new AI in materials symposium at the MRS spring meeting in Phoenix. Prof. Ulissi talked about practical benefits and approaches to integrating these into the search for new catalyst materials.

Talk and session chair at ACS Machine Learning in Catalysis symposium

Prof Ulissi co-chaired a session on machine learning methods in catalysis, organized by Hongliang Xin, Andy Peterson and CMU’s John Kitchin. He also gave a talk on the group’s perspective of how ML can fit into a day-to-day computational catalysis workflow.

Group receives a DOE supercomputer allocation!

We received 4 million service unit allocation for 2018 on the Cori supercomputer at the Department of Energy National Energy Research Supercomputing Center (NERSC). This is a boost for our high throughput calculation and NERSC also supports our workflow, machine learning, and database tasks. This is roughly equivalent to about... [Read More]

Setting up the lab at PSC

We visited the Pittsburgh Supercomputing Center (PSC) co-location facility to do some hands-on maintenance with our machines hosted there. Luckily, this was the most labor intensive part of starting the group and building the ‘lab’! We share about 100 high performance CPU and GPU-accelerated nodes with other groups in the... [Read More]

F17 Group dinner

Group dinner for the 2017 holidays! We played with our dog Kepler, watched Kevin beat everyone in ping pong, and made and ate Osso Buco and homemade lemon/speculoos ice cream.

Welcome to new MS students Wen Zhong and Zong Qian Yu!

Wen and Zong Qian will be completing research projects from January through the end of next year. Zong Qian will be working on predictive methods for materials discovery, and Wen will be working on predictive and high-throughput methods for patterned surfaces!

ML for energy materials discovery commentary published in Nature!

A commentary that was written from the proceedings of a workshop we attended in May 2017 was published in Nature, with Zachary Ulissi as a co-signatory. See the article for a high-level description of challenges in applying predictive methods to the discovery of new energy materials: Use machine learning to... [Read More]

Kevin passes his quals!

The group’s first PhD student, Kevin Tran, passed his quals with a presentation on his first project “Automated materials simulation: DFT-calculated adsorption energies”. [Read More]

Actively recruiting!

We have positions at the undergrad (CMU-preferred) and PhD level. If you’re excited about this work, get in touch by email with your background, CV, and what interests you.

Ulissi Group welcomes the first student!

Kevin Tran joined in December 2016, and will be working on systems engineering approaches applied to materials discovery. Welcome to the group!