Burcu Beykal

Assistant Professor

Department of Chemical and Biomolecular Engineering


Education

  • Postdoc, Data Analytics/Optimization, Texas A&M University (2021)
  • Ph.D., Chemical Engineering, Texas A&M University (2020)
  • M.S., Chemical Engineering, Carnegie Mellon University (2014)
  • B.S., Chemical & Biological Engineering, Koc University (2013)

Research Focus

  • Process Systems Engineering
  • Machine Learning/AI
  • Data-driven Optimization
  • Supply Chain Optimization
  • Energy Systems Design
  • Data-driven Modeling of Environmental & Biological Systems
  • TEA/LCA

Awards and Honors

  • 2023 ACS Petroleum Research Fund Doctoral New Investigator Award
  • 2020 AIChE CAST Directors’ Award
  • Outstanding Graduate Student Award, Artie McFerrin Department of Chemical Engineering, Texas A&M University
  • MIT Rising Stars in Chemical Engineering

Publications

  1. H Nikkhah, Z Aghayev, A Shahbazi, VM Charitopoulos, S Avraamidou, B Beykal. Bi-level data-driven enterprise-wide optimization with mixed-integer nonlinear scheduling problems, Digital Chemical Engineering, 2025, 100218.
  2. H Nikkhah, A Di Maria, G Granata, B Beykal. Sustainable process design for lithium recovery from geothermal brines using chemical precipitation, Resources, Conservation and Recycling, 2025, 212, 107980.
  3. H Nikkhah, D Ipekci, W Xiang, Z Stoll, P Xu, B Li, JR McCutcheon, B Beykal. Challenges and opportunities of recovering lithium from seawater, produced water, geothermal brines, and salt lakes using conventional and emerging technologies, Chemical Engineering Journal, 2024, 498, 155349.
  4. BG Cohen, B Beykal, GM Bollas. Physics-informed genetic programming for discovery of partial differential equations from scarce and noisy data, Journal of Computational Physics, 2024, 514, 113261.
  5. H Nikkhah, B Beykal, MD Stuber. Comparative life cycle assessment of single-use cardiopulmonary bypass devices. Journal of Cleaner Production, 2023, 425, 138815.
  6. Z Aghayev, AT Szafran, A Tran, HS Ganesh, F Stossi, L Zhou, MA Mancini, EN Pistikopoulos, B Beykal. Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data. Chemical Engineering Science, 2023, 119086.
  7. H Nikkhah, B Beykal. Process Design and Technoeconomic Analysis for Zero Liquid Discharge Desalination via LiBr Absorption Chiller Integrated HDH-MEE-MVR System, Desalination, 2023, 116643.

 

 

 

Prof. Burcu Beykal, Ph.D.
Contact Information
Emailbeykal@uconn.edu
Phone860-486-2756
Office LocationPWEB-282
CampusStorrs
Linkhttps://beykal.engr.uconn.edu/