معرفی
David Bernal Neira is an Assistant Professor in the Davidson School of Chemical Engineering at Purdue University, joined in August 2023. His research focuses on optimization algorithms, quantum computing, and computational methods applied to chemical and energy systems. He holds a PhD in Chemical Engineering from Carnegie Mellon University and degrees from Universidad de Los Andes, Colombia.
Education:
- PhD in Chemical Engineering, Carnegie Mellon University (2017–2021)
- M.Sc. in Chemical Engineering, Universidad de Los Andes (2014–2016)
- B.A.Sc. in Chemical Engineering, Universidad de Los Andes (2010–2014)
- B.A.Sc. in Physics, Universidad de Los Andes (2011–2018)
Research Interests: His work bridges classical and quantum optimization, with applications in process systems, energy, and chemical engineering. Key areas include mathematical modeling, quantum annealing, and federated learning. He develops algorithms and software tools, such as GDP and QUBO frameworks, and explores quantum computing for chemistry and combinatorial problems.
Publications: Over 30 peer-reviewed articles since 2020, focusing on quantum optimization, federated learning, and algorithm design. Recent work emphasizes benchmarking quantum hardware and hybrid quantum-classical methods.
Awards:
- Fellow, National Academies (2025, 2023)
- Best Talk Award (2022)
- Outstanding Teaching Assistant (2019)
Advising & Grants: Supervises graduate students in quantum computing and optimization. Collaborates with NASA, USRA, and industry on quantum projects. Formerly an Associate Scientist at NASA QuAIL and Adjunct Professor at Carnegie Mellon.
Labs & Teams: Leads the SECQUOIA Research Group at Purdue, focusing on systems engineering via quantum and classical optimization. Active in federally funded initiatives and industry partnerships.
