Beykal, Burcu

Burcu Beykal

Assistant Professor, Chemical and Biomolecular Engineering

Email beykal@uconn.edu
Phone (860) 486-2756
Mailing Address Department of Chemical &
Biomolecular Engineering Engineering II, Room 204 191 Auditorium Road, Unit 3222 University of Connecticut Storrs, CT 06269-3222
Link Research Website
Google Scholar Link

Brief Bio

  • Process Design for Energy, Water, & Critical Minerals Recovery
  • Artificial Intelligence & Machine Learning for Process Systems Engineering
  • Process Operations & Supply Chain Management
  • Data-Driven Optimization & Algorithms

2025

  1. Y Zhang, A Purohit, Z Aghayev, Y Wang, J Liang, B Beykal, Y Luo, M Qiao. Optimization and evaluation of a simplified green biorefinery for alginate extraction from sugar kelp (Saccharina latissima), International Journal of Biological Macromolecules, 2025, 309(4), 143147.
  2. Z Aghayev, D Voulanas, E Gildin, B Beykal. Surrogate-Assisted Optimization of Highly Constrained Oil Recovery Processes Using Classification-Based Constraint Modeling, Industrial & Engineering Chemistry Research, 2025, 64, 15, 7751–7766.
  3. S Kivanc, B Beykal, O Deliismail, H Sildir. Dynamic and Stochastic Optimization of Algae Cultivation Process, Computers & Chemical Engineering, 2025, 198, 109087.
  4. 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, 14, 100218.
  5. 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.

2024

  1. 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.
  2. 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.
  3. Y Feng, Y Wang, B Beykal, Z Xiao, Y Luo. Machine learning supported ground beef freshness monitoring based on near-infrared and paper chromogenic array, Food Frontiers, 2024, 5(5), 2199-2210.
  4. KJ Rivenbark, LS Fawkes, H Nikkhah, M Wang, GT Sansom, B Beykal, TL Wade, TD Phillips. Using L. minor and C. elegans to assess the ecotoxicity of real-life contaminated soil samples and their remediation by clay- and carbon-based sorbents, Environmental Pollution, 2024, 347, 123762.
  5. KJ Rivenbark, H Nikkhah, M Wang, B Beykal, TD Phillips. Toxicity of representative organophosphate, organochlorine, phenylurea, dinitroaniline, carbamate, and viologen pesticides to the growth and survival of H. vulgaris, L. minor, and C. elegans, Environmental Science and Pollution Research, 2024, 31, 21781–21796.
  6. M Wang, KJ Rivenbark, H Nikkhah, B Beykal, TD Phillips. In vitro and in vivo remediation of per- and polyfluoroalkyl substances by processed and amended clays and activated carbon in soil, Applied Soil Ecology, 2024, 196, 105285.
  7. Y Feng, Y Wang, B Beykal, M Qiao, Z Xiao, Y Luo. A mechanistic review on machine learning-supported detection and analysis of volatile organic compounds for food quality and safety, Trends in Food Science & Technology, 2024, 143, 104297.
  8. A Nikkhah, H Nikkhah, A Shahbazi, MKZ Zarin, D Beykal Iz, MT Ebadi, M Fakhroleslam, B Beykal. Cumin and eucalyptus essential oil standardization using fractional distillation: Data-driven optimization and techno-economic analysis, Food and Bioproducts Processing, 2024, 143, 90-101.

2023

  1. H Nikkhah, B Beykal, MD Stuber. Comparative life cycle assessment of single-use cardiopulmonary bypass devices. Journal of Cleaner Production, 2023, 425, 138815.
  2. 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, 281, 119086.
  3. 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, 558, 116643.

2022

  1. D Kenefake, I Pappas, S Avraamidou, B Beykal, HS Ganesh, Y Cao, Y Wang, J Otashu, S Leyland, J Flores-Cerrillo, EN Pistikopoulos. A Smart Manufacturing Strategy for Multi-Parametric Model Predictive Control in Air Separation Systems, Journal of Advanced Manufacturing and Processing, 2022, e10120.
  2. B Beykal, S Avraamidou, EN Pistikopoulos. Data-Driven Optimization of Mixed-integer Bi-level Multi-follower Integrated Planning and Scheduling Problems Under Demand Uncertainty, Computers & Chemical Engineering, 2022, 156, 107551.

2021

  1. I Pappas, S Avraamidou, J Katz, B Burnak, B Beykal, M Turkay, EN Pistikopoulos. Multiobjective Optimization of Mixed-Integer Linear Programming Problems: A Multiparametric Optimization Approach, Industrial & Engineering Chemistry Research, 2021, 60(23), 8493-8503.
  2. AA Orr, M Wang, B Beykal, HS Ganesh, S Hearon, EN Pistikopoulos, TD Phillips, P Tamamis. Combining Experimental Isotherms, Minimalistic Simulations, and a Model to Understand and Predict Chemical Adsorption onto Montmorillonite Clays, ACS Omega, 2021, 6(22), 14090-14103.

2020

  1. R Mukherjee, B Beykal, AT Szafran, M Onel, F Stossi, MG Mancini, D Lloyd, FA Wright, L Zhou, MA Mancini, EN Pistikopoulos. Classification of Estrogenic Compounds by Coupling High Content Analysis and Machine Learning Algorithms.  PLOS Computational Biology, 2020, 16(9), e1008191.
  2. K Bi, B Beykal, I Pappas, S Avraamidou, EN Pistikopoulos, T Qui. Integrated Modeling of Transfer Learning and Intelligent Heuristic Optimization for Steam Cracking Process. Industrial & Engineering Chemistry Research, 2020, 59(37), 16357-16367.
  3. B Beykal, M Onel, O Onel, EN Pistikopoulos. A Data-Driven Optimization Algorithm for Differential Algebraic Equations with Numerical Infeasibilities. AIChE Journal, 2020, 66(10), e16657.
  4. B Beykal, S Avraamidou, IPE Pistikopoulos, M Onel, EN Pistikopoulos. DOMINO: Data-driven Optimization of bi-level Mixed-Integer NOnlinear Problems. Journal of Global Optimization, 2020, 78, 1–36.

2025

  • Research Excellence Awards

      • Congratulations to Zahir Aghayev for being awarded the Research Excellence Awards from the Department of Chemical and Biomolecular Engineering.

  • Eversource Energy  Center Appointment

      • Congratulations to Dr. Beykal for being appointed Eversource Energy Professor in Environmental and Sustainability Education.

  • Predoctoral Travel Awards

      • Congratulations to Hasan Nikkhah and Amir Shahbazi for being awarded the 2025 Predoctoral Travel Award from the Department of Chemical and Biomolecular Engineering.

2024

  • AIChE 2024

    • We are attending the American Institue of Chemical Engineers (AIChE) Annual Meeting with the following contributions:
      • B Cohen, B Beykal, GM Bollas. “A Symbolic-Sparse Regression Technique for Data-Driven PDE Learning and Solution Approximation in Chemical Engineering”.
      • Z Aghayev, D Voulanas, E Gildin, B Beykal. “Enhancing Oil Recovery Efficiency with Constrained Reinforcement Learning for Waterflooding Optimization”.
      • Z Aghayev, Zh Li, M Patrascu, B Beykal. “Optimizing CO2 Utilization Efficiency Through Physics-Informed Modeling of Membrane Reactors”.
      • H Nikkhah, A Di Maria, G Granata, B Beykal. “Toward Sustainable Lithium Production: Process Modeling, Techno-Economic Analysis, and Life Cycle Impacts of Recovering Lithium from Geothermal Brines”.
      • H Nikkhah, S Johnn, M-L Tsai, A Shahbazi, Z Aghayev, S Avraamidou, V Charitopoulos, B Beykal. “Data-driven Approaches for the Optimization of Complex Planning and Scheduling Problems in Multi-Product Industries”.
      • A Shahbazi, H Nikkhah, Z Aghayev, B Beykal. “Data-driven Bi-level Optimization of Hyperparameters for Machine Learning Models”.
      • A Shahbazi, B Beykal. “Physics-informed Estimation of Thermodynamic Parameters of Biodiesel Production from Enteromorpha Compressa Microalgae”.

  • FOCAPD 2024 Poster Award

    • Congratulations to Hasan Nikkhah and Dev Barocha for having your poster selected as one of the best at the FOCAPD 2024 conference.

  • FOCAPD 2024

    • MadeAI 2024

      • We are attending Modelling, Data Analytics and AI in Engineering with the following contribution:
        • Cohen B, Beykal B, Bollas GM. “Surrogate Solutions to Partial Differential Equations and the Inverse Problem with Symbolic Regression”.MadeAI 2024, Porto, Portugal.

        • Research  Excellence Awards

          • Congratulations to Hasan Nikkhah for being awarded the Research Excellence Awards from the Department of Chemical and Biomolecular Engineering.

        • 245th ECS Meeting

          • We are attending 245th ECS Meeting with the following contributions:
            • Sanumi OJ, Schneider P, Batool M, Godoy AO, Singh R, Gerteisen D, Beykal B, Zamel N, Jankovic J. “Degradation Studies of Fuel Cell Cathode Catalyst Layers Using Machine Learning”

        • 2024 Frontiers

          • We are attending 2024 Frontiers at the University of Connecticut with the following contributions:
            • Balamurugan R, Nikkhah H, Beykal B. “Utilizing Machine Learning Algorithms to Predict COD (Chemical Oxygen Demand) In Wastewater Treatment”.

        • Welcome to the newest team member

          • Cameron Hubbard just joined the Hybrid Modeling & Systems Engineering Laboratory as a new Research Technician. Welcome Cameron!

        • Teaching Assistant Awards

          • Congratulations to Amir Shahbazi for being awarded the Outstanding TA Award from the Department of Chemical and Biomolecular Engineering.

        • Lawrence Livermore National Laboratory DDPS Seminar Series

          • Dr. Beykal will be attending at Data-Driven Physical Simulations (DDPS) seminar series by Lawrence Livermore National Laboratory with the following presentation:
            • “A Data-Driven Physical Simulation Engineering Approach for Supply Chain Management and Enterprise-Wide Optimization”.

        • C2E2 GA Research Summit in Sustainability

          • We are attending UConn Center for Clean Energy Engineering GA Research Summit in Sustainability with the following contributions:
            • Cohen B, Beykal B, Bollas GM. “Symbolic Regression for Interpretable Surrogate Modeling of Clean Energy Systems”.
            • Barochia D, Nikkhah H, Beykal B. “Design and Optimization of a Multipurpose Zero Liquid Discharge Desalination Plan”.

        • Uconn COE Poster Competition

          • We are attending UConn College of Engineering poster competition with the following contributions:
            • Cohen B, Beykal B, Bollas GM. “Discovering Partial Differential Equation Solutions using Symbolic Regression”.
            • Shahbazi A, Beykal B. “Predicting Kinetic & Thermodynamic Parameters of Biodiesel Production from Enteromorpha Compressa Microalgae using Evolutionary Algorithms”.

            2023

            • NIEHS Superfund Research Program

              • We are attending NIEHS Superfund Research program Annual Meeting with the following contribution:
                  • Iseri F, Ali M, Mustapha TA, Aghayev Z, Beykal B, Johnson NM, Pistikopoulos EN. “A Data-Driven Framework for Characterizing Volatile Organic Compounds (VOCs)”.

            • IEEE CDC 2023

              • We are attending 62nd IEEE Conference on Decision and Control with the following contribution:
                • Cohen B, Beykal B, Bollas GM. “Dynamic System Identification from Scarce and Noisy Data Using Symbolic Regression”.

              • Welcome to the newest team member

                • The newest graduate student, Amir Shahbazi just joined the Hybrid Modeling & Systems Engineering Laboratory. Welcome Amir!

              • AIChE 2023

                • Dr. Beykal, Hasan, and Zahir will be attending AIChE Annual Meeting with the following contributions:
                  • Nikkhah H, Beykal B. “Process Design of a LiBr Absorption Chiller Integrated Hdh-Mee-Mvr System for Zero Liquid Discharge Seawater Desalination”.
                  • Nikkhah H, Charitopoulos VM, Avraamidou S, Beykal B. “Data-Driven Optimization of Mixed-Integer Nonlinear Integrated Planning and Scheduling Problems for Multiproduct Manufacturing Processes”.
                  • Aghayev Z, Walker GF, Iseri F, Ali M, Szafran AT, Stossi F, Mancini MA, Pistikopoulos EN, Beykal B. “Computational Characterization of the Estrogenic Activity of Environmental Chemicals Using High-Throughput Microscopy and Machine Learning”.
                  • Aghayev Z, Voulanas D, Badawi D, Gildin E, Beykal B. “Data-Driven Optimization of Highly Constrained Oil Recovery Processes Using Neural Network Surrogate Models and Classification Based Implicit Constraint Handling Schemes”.
                  • Ali M, Iseri F, Mustapha T, Aghayev Z, Beykal B, Wright FA, Johnson NM, Pistikopoulos EN. “Data Driven Framework for Volatile Organic Compounds (VOCs) Characterization”.

              • INFORMS 2023

                • Dr. Beykal, Hasan, and Ben attended  INFORMS Annual Meeting with the following contributions:
                  • H Nikkhah, VM Charitopoulos, S Avraamidou, B Beykal. “Data-Driven Bilevel Optimization of Integrated Planning and Scheduling Problems with Mixed-Integer Nonlinear Lower-Level Formulations”.
                  • B Cohen, N Aslam, B Beykal, GM Bollas. “Learning Human-Interpretable Models Using Machine Learning and a Smooth Information Criterion”.

                • UConn Separations Workshop

                  • Hasan will be presenting his work on “Integrated HDH-MEE-MVR System with LiBr Absorption Chiller for Zero Liquid Discharge Desalination: Process Design and Techno-economic Analysis” at the 2nd Industrial Workshop on Separations Technology.

                • Clean Energy & Sustainability Innovation Challenge

                  • Hasan and Dev, in collaboration with Francesco Rouhana from Civil and Environmental Engineering, presented their project, “Technical and Social Solutions for a Sustainable UConn” at the Sustainable Clean Energy Summit: Decarbonizing Society and the Grid. They were previously selected as finalists in the Clean Energy & Sustainability Innovation Program. Read more on UConn Today.

                • WiSFiRE 2023

                  • Dr. Beykal participated at the Women in STEM Frontiers in Research Expo on “Data Analytics Inspired Process Systems Engineering”.

                • ECCE&ECAB 2023

                  • We are attending the 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology with the following contribution:
                    • Ben Cohen, Burcu Beykal, George Bollas. “DiscoPy: Discovery of Chemical Reactor Dynamics through Symbolic Regression“

                • ACS Fall 2023

                  • We are attending the ACS Fall 2023 meeting with the following contribution:
                    • Zahir Aghayev, G. Fuller Walker, Funda Iseri, Moustafa Ali, Adam T. Szafran, Fabio Stossi, Michael A. Mancini, Efstratios N. Pistikopoulos, Burcu Beykal. “Predicting the Estrogenic Potential of Chemical Contaminants through High- throughput Image Analysis and Supervised Machine Learning Algorithms”

                • FOPAM 2023

                  • We are attending the FOPAM 2023 meeting with the following contribution:
                    • Hasan Nikkhah, Vasileios M. Charitopoulos, Styliani Avraamidou, Burcu Beykal. “Integrated Planning and Scheduling for Crude Oil Operations Using Data-Driven Bilevel Multi-Follower Optimization“

                • ESCAPE-33

                  • We are attending the ESCAPE-33 conference with the following contribution:
                    • Zahir Aghayev, G. Fuller Walker, Funda Iseri, Moustafa Ali, Adam T. Szafran, Fabio Stossi, Michael A. Mancini, Efstratios N. Pistikopoulos, Burcu Beykal. “Binary Classification of the Endocrine Disrupting Chemicals by Artificial Neural Networks”

                • Chemical & Biomolecular Engineering Teaching Fellow

                  • Congratulations to Hasan Nikkhah for being selected as the Department of Chemical and Biomolecular Engineering Teaching Fellow.

                • Teaching Assistant Awards

                  • Congratulations to Hasan Nikkhah for being awarded the 3rd place in TA Awards from the Department of Chemical and Biomolecular Engineering.

                • Our group has participated at the Frontiers Poster Exhibition with the following contribution:

                  • Katherine Pettersen, Hasan Nikkhah Burcu Beykal. “Optimizing Municipal Wastewater Treatment through Biological Modeling and Simulation”

                • Poster Award

                  • Congratulations to Benjamin Cohen for receiving the First Place Poster Award at the 9th Annual School of Engineering Poster Competition with his work on “Automatic Discovery of Partial Differential Equation Models from Broadly Spaced Data”.

                • Our group has participated at the 9th Annual School of Engineering Poster Competition with the following contributions:

                  • Zahir Aghayev, Adam T. Szafran, Anh Tran, Hari S. Ganesh, Fabio Stossi, Lan Zhou, Michael A. Mancini, Efstratios N. Pistikopoulos, Burcu Beykal. “Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data.”
                  • Benjamin Cohen, Burcu Beykal, George Bollas. “Automatic Discovery of Partial Differential Equation Models from Broadly Spaced Data.“
                  • Hasan Nikkhah, Burcu Beykal. “Multipurpose Desalination Plant: Simultaneous Air Conditioning, Desalination, and Zero Liquid Discharge.”