Program Overview

This unique training program is designed to foster collaboration between computer scientists, chemists, and chemical engineers. By learning how to harness data, we will be able to ask and answer new questions in catalysis. We train students how to be interdisciplinary scholars, highly skilled communicators and leaders capable of excelling a wide array of careers.

Curriculum and Programming

Required Courses

C&PE 715 | Topics in Chemical and Petroleum Engineering: Applied Machine Learning for Scientists and Engineers - 3 credit hours, even Springs only

C&PE 802 | CEBC Colloquium- 1 credit hour (2 semesters at 0.5 credit hours each, they do not need to be successive semesters)



& Choose One (at least 3 credit hours) Research Course:

C&PE Students: C&PE 803 or C&PE 904 | Research - 3-6 credit hour(s)

CHEM Students: CHEM 800 or CHEM 899 or CHEM 900 or CHEM 999 | Research - 3-10 credit hour(s)

EECS Students: EECS 891 or EECS 899 or EECS 998 or EECS 999 | Research - 3-5 credit hour(s)

BIOE Students: BIOE 899, or BIOE 999 | Research - 3-6 credit hour(s) (added as of Fall 2025)

ME Students: ME 899, or ME 999 | Research - 3-6 credit hour(s) (added as of Fall 2025)

CE Students: CE 899, or CE 999 | Research - 3-10 credit hour(s) (added as of Fall 2025)



& Choose One (3 credit hour) Data Science Course:

C&PE 778 | Applied Optimization Methods - 3 credit hours

CHEM 914 | Computational Methods in Physical Sciences - 3 credit hours

EECS 649 | Introduction to Artificial Intelligence - 3 credit hours

EECS 767 | Information Retrieval - 3 credit hours

EECS 835 | Advanced Data Science - 3 credit hours

EECS 836 | Machine Learning - 3 credit hours

CEBC-affiliated students and those enrolled in the Graduate Certificate for Machine Learning for Scientists and Engineering are expected to attend the bi-annual CEBC Industry Advisory Board (IAB) meetings (October and April). 

At these meetings, trainees will have the chance to present their research and network with representatives from our science and industry advisors. They will also gain insights on how research is conducted in the private sector and how discoveries are commercialized.

The Internet of Catalysis includes faculty from the Center for Environmentally Beneficial Catalysis.

Former NSF Grant Information

The NRT is an educational experiment intended to enhance graduate training while transforming research and education at the University of Kansas. Our NRT program is funded by the National Science Foundation by grant number 1922649. The program was funded from September 1, 2019 to August 31, 2025.