David E. Bernal Neira
David E. Bernal Neira is an Assistant Professor in the Davidson School of Chemical Engineering at Purdue University. His research focuses on the use of mathematical and computational methods to address scientific and engineering problems, particularly in process systems, energy, and chemical engineering. His core expertise lies in nonlinear discrete optimization, where he develops theory, algorithms, and software. He also conducts research in quantum computing and its intersection with optimization. He has co-authored several peer-reviewed publications, developed software tools, and delivered talks and seminars across academia, government, and industry. He has taught multiple courses, including one at the intersection of optimization, quantum computing, and machine learning, which he co-designed. He actively collaborates with researchers across academic institutions, national labs, government agencies, and industry.
Link to his profile at Purdue University.
Affiliations
- Principal Investigator of SECQUOIA, Purdue University, West Lafayette, IN, USA
- Assistant Professor in Chemical Engineering, Purdue University, West Lafayette, IN, USA
Former Positions
- Associate Scientist in Quantum Computing, USRA Research Institute for Advanced Computer Science, Mountain View, CA, USA
Supervisor: Dr. Davide Venturelli - Scientist in Quantum Computing, NASA Quantum Artificial Intelligence Laboratory, Mountain View, CA, USA
Supervisor: Dr. Eleanor Rieffel - Adjunct Professor in Quantum Computing, Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA
Education
- Ph.D. in Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA (2017–2021)
Advisor: Prof. Ignacio E. Grossmann - B.Sc. in Physics, Universidad de los Andes, Bogotá, Colombia (2011–2018)
Advisor: Prof. Jaime Forero - M.Sc. in Chemical Engineering, Universidad de los Andes, Bogotá, Colombia (2014–2016)
Advisor: Prof. Jorge Mario Gómez - B.Sc. in Chemical Engineering, Universidad de los Andes, Bogotá, Colombia (2010–2014)
Advisor: Prof. Jorge Mario Gómez
Research Interests
Our group works at the interface of nonlinear discrete optimization and advanced computing for applications in chemical engineering. Key research areas include:
- Algorithms, software, and theory for mixed-integer nonlinear programming
- Quantum computing for optimization and computational chemistry
- Non-conventional hardware for computing and optimization
- Federated and distributed (quantum) learning
- Process systems design, synthesis, operations, and control
- Applications to the pharmaceutical, chemical, oil and gas, and energy sectors
- Optimization-driven process engineering for sustainability
Teaching
See the teaching page for more on teaching experience and philosophy. Courses taught by Prof. Bernal include:
- Process Dynamics and Control — Purdue CHE456 (Fall 2023, Fall 2024)
- Quantum Integer Programming and Machine Learning — CMU 47-779 / 47-785, 18-819F
Fall 2021, Fall 2022, Fall 2023, Fall 2024 - Quantum Integer Programming — CMU 47-779 Fall 2020
Awards
- Fellow, Connections to Sustain Science in Latin America, National Academies of Sciences, Engineering, and Medicine (2025)
- Fellow, Arab-American Frontiers of Engineering, National Academies of Sciences, Engineering, and Medicine (2023)
- Best Talk Award, Quantum Computing Applications in Chemical and Biochemical Engineering Workshop (2022)
- Finalist, AIChE CAST Directors’ Student Presentation Awards (2020)
- Mark Dennis Karl Outstanding Teaching Assistant Award, Chemical Engineering Department, Carnegie Mellon University (2019)
- Cum Laude, Chemical Engineering, Universidad de los Andes (2014)
- Alberto Magno Scholarship, Universidad de los Andes (2010–2014)
- Valedictorian, Gimnasio Británico (2009)
- First Place, Colombian Physics Olympiad (Superior Level), Universidad Antonio Nariño (2007)
Publications
Please see the publications page.