Publications

Journal Articles

2024

  1. 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.
  2. 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.
  3. 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 & Technology, 2024, 196, 105285.
  4. 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, Trends in Food Science & Technology, 2024, 143, 104297.
  5. 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.

2019

  1. M Onel, B Beykal, K Ferguson, WA Chiu, TJ McDonald, L Zhou, JS House, FA Wright, DA Sheen, I Rusyn, EN Pistikopoulos. Grouping of Complex Substances Using Analytical Chemistry Data: A Framework for Quantitative Evaluation and Visualization. PLoS ONE, 2019, 14(10): e0223517.

2018

  1. B Beykal, F Boukouvala, CA Floudas, EN Pistikopoulos. Optimal Design of Energy Systems Using Constrained Grey-Box Multi-Objective Optimization. Computers & Chemical Engineering, 2018, 116, 488-502.
  2. B Beykal, F Boukouvala, CA Floudas, N Sorek, H Zalavadia, E Gildin. Global Optimization of Grey-Box Computational Systems Using Surrogate Functions and Application to Highly Constrained Oil-Field Operations. Computers & Chemical Engineering, 2018, 114, 99-110.

2017

  1. N Sorek, E Gildin, F Boukouvala, B Beykal, CA Floudas. Dimensionality Reduction for Production Optimization Using Polynomial Approximations. Computational Geosciences, 2017, 21, 247-266.

2015

  1. B Beykal, M Herzberg, Y Oren, MS Mauter. Influence of Surface Charge on the Rate, Extent, and Structure of Adsorbed Bovine Serum Albumin to Gold Electrodes. Journal of Colloid and Interface Science, 2015, 460, 321-328.

2013

  1. E Uzunlar, B Beykal, K Ehrlich, D Sanli, A Jonáš, BE Alaca, A Kiraz, H Urey, C Erkey. Frequency Response of Microcantilevers Immersed in Gaseous, Liquid, and Supercritical Carbon Dioxide. The Journal of Supercritical Fluids, 2013, 81, 254-264.

Chapters in Books

  1. B Beykal, EN Pistikopoulos. Chapter 5 – Data-Driven Optimization Algorithms. Artificial Intelligence in Manufacturing. ELSEVIER, 2024, Paperback ISBN: 9780323991346, eBook ISBN: 9780323996723 .

Conference Proceedings

2023

  1. B Cohen, B Beykal, G Bollas. Dynamic System Identification from Scarce and Noisy Data Using Symbolic Regression, 2023 62nd IEEE Conference on Decision and Control (CDC) , 2023.
  2. Z Aghayev, GF Walker, F Iseri, M Ali, AT Szafran, A Tran, HS Ganesh, F Stossi, MA Mancini, EN Pistikopoulos, B Beykal. Binary Classification of the Endocrine Disrupting Chemicals by Artificial Neural Networks, Computer Aided Chemical Engineering, 2023, 52, 2631-2636, Elsevier.

2022

  1. M Di Martino, I Pappas, A Tran, RC Allen, RR Husfeld, S Eleff, SG Moffatt, S Avraamidou, B Beykal, EN Pistikopoulos. A Framework to Facilitate Decision Making for Infrastructure Options Analysis of Distribution and Utilities Systems in Chemical Production Plants, Computer Aided Chemical Engineering, 2022, 51, 835-840, Elsevier.
  2. B Beykal, NA Diangelakis, EN Pistikopoulos. Continuous-Time Surrogate Models for Data- Driven Dynamic Optimization, Computer Aided Chemical Engineering, 2022, 51, 205-210, Elsevier.
  3. B Beykal, Z Aghayev, O Onel, M Onel, EN Pistikopoulos. Data-driven Stochastic Optimization of Numerically Infeasible Differential Algebraic Equations: An Application to the Steam Cracking Process, Computer Aided Chemical Engineering, 49, 1579-1584.

2021

  1. B Beykal, S Avraamidou, EN Pistikopoulos. Bi-level Mixed-Integer Data-Driven Optimization of Integrated Planning and Scheduling Problems, Computer Aided Chemical Engineering, 2021, 50, 1707-1713, Elsevier.
  2. HS Ganesh, B Beykal, AT Szafran, F Stossi, L Zhou, MA Mancini, EN Pistikopoulos. Predicting the Estrogen Receptor Activity of Environmental Chemicals by Single-Cell Image Analysis and Data-driven Modeling, Computer Aided Chemical Engineering, 2021, 50, 481-486, Elsevier.

2019

  1. R Mukherjee, M Onel, B Beykal, AT Szafran, F Stossi, MA Mancini, L Zhou, FA Wright, EN Pistikopoulos. Development of the Texas A&M Superfund Research Program Computational Platform for Data Integration, Visualization, and Analysis. Computer Aided Chemical Engineering, 2019, 46, 967-972, Elsevier.

2018

  1. M Onel, B Beykal, M Wang, FA Grimm, L Zhou, FA Wright, TD Phillips, I Rusyn, EN Pistikopoulos. Optimal Chemical Grouping and Sorbent Material Design by Data Analysis, Modeling and Dimensionality Reduction Techniques. Computer Aided Chemical Engineering, 2018, 43, 421-426, Elsevier.
  2. S Avraamidou, B Beykal, IPE Pistikopoulos, EN Pistikopoulos. A hierarchical Food-Energy-Water Nexus (FEW-N) Decision-making Approach for Land Use Optimization. Computer Aided Chemical Engineering, 2018, 44, 1885-1890, Elsevier.