Superfund Research Program

Efstratios N. Pistikopoulos

Texas A&M University
Artie McFerrin Department of Chemical Engineering
3127 TAMU

Phone: 979-458-0259
Email: stratos@tamu.edu

Projects

• Texas A&M University: Data Management and Analysis Core (2022-2027)

Publications

2023

• Aghayev Z, Szafran AT, Tran A, Ganesh HS, Stossi F, Zhou L, Mancini MA, Pistikopoulos EN, Beykal B. 2023. Machine learning methods for endocrine disrupting potential identification based on single-cell data. Chem Eng Sci 281:119086. doi:10.1016/j.ces.2023.119086 PMID:37637227 PMCID:PMC10448728
• Aghayev Z, Walker GF, Iseri F, Ali M, Szafran AT, Stossi F, Mancini MA, Pistikopoulos EN, Beykal B. 2023. Binary classification of the endocrine disrupting chemicals by artificial neural networks. ESCAPE 52:2631-2636. doi:10.1016/b978-0-443-15274-0.50418-2 PMID:37575176 PMCID:PMC1041341

2022

• Beykal B, Avraamidou S, Pistikopoulos EN. 2022. Data-driven optimization of mixed-integer bi-level multi-follower integrated planning and scheduling problems under demand uncertainty. Computers & Chemical Engineering 156:107551. doi:10.1016/j.compchemeng.2021.107551 PMID:34720250 PMCID:PMC8553017
• Beykal B, Diangelakis NA, Pistikopoulos EN. 2022. Continuous-time surrogate models for data-driven dynamic optimization. ESCAPE 51:205-210. doi:10.1016/b978-0-323-95879-0.50035-7 PMID:36622647 PMCID:PMC9823268
• Gordon CA, Pistikopoulos EN. 2022. Data-driven and safety-aware holistic production planning. J Loss Prev Process Ind 77:104754. doi:10.1016/j.jlp.2022.104754

2021

• Beykal B, Avraamidou S, Pistikopoulos EN. 2021. Bi-level mixed-integer data-driven optimization of integrated planning and scheduling problems. ESCAPE 50:1707-1713. doi:10.1016/b978-0-323-88506-5.50265-5 PMID:34414400 PMCID:PMC8370828
• Ganesh HS, Beykal B, Szafran AT, Stossi F, Zhou L, Mancini MA, Pistikopoulos EN. 2021. Predicting the estrogen receptor activity of environmental chemicals by single-cell image analysis and data-driven modeling. ESCAPE 50:481-486. doi:10.1016/b978-0-323-88506-5.50076-0 PMID:34355221 PMCID:PMC8331057
• Gordon CA, Pistikopoulos EN. 2021. Data-driven prescriptive maintenance toward fault-tolerant multiparametric control. AIChE Journal 12:doi:10.1002/aic.17489
• Orr AA, Wang M, Beykal B, Ganesh HS, Hearon S, Pistikopoulos EN, Phillips TD, Tamamis P. 2021. Combining experimental isotherms, minimalistic simulations, and a model to understand and predict chemical adsorption onto montmorillonite clays. ACS Omega 6(22):14090-14103. doi:10.1021/acsomega.1c00481 PMID:34124432 PMCID:PMC8190805
• Pappas I, Avraamidou S, Katz J, Burnak B, Beykal B, Turkay M, Pistikopoulos EN. 2021. Multiobjective optimization of mixed-integer linear programming problems: A multiparametric optimization approach. Ind Eng Chem Res 60:8493-8503. doi:10.1021/acs.iecr.1c01175 PMID:34219916 PMCID:PMC8248908

2020

• Beykal B, Avraamidou S, Pistikopoulos IP, Onel M, Pistikopoulos EN. 2020. DOMINO: Data driven optimization of bi level mixed integer nonlinear problems. J Glob Optim 36:doi:10.1007/s10898-020-00890-3 PMID:32753792 PMCID:PMC7402589
• Beykal B, Onel M, Onel O, Pistikopoulos EN. 2020. A data-driven optimization algorithm for differential algebraic equations with numerical infeasibilities. AIChE Journal doi:10.1002/aic.16657 PMID:32921798 PMCID:PMC7485937
• Bi K, Beykal B, Avraamidou S, Pappas I, Pistikopoulos EN, Qiu T. 2020. Integrated Modeling of Transfer Learning and Intelligent Heuristic Optimization for a Steam Cracking Process. Ind Eng Chem Res 59:16357-16367. doi:10.1021/acs.iecr.0c02657 PMID:33041499 PMCID:PMC7543991
• Mukherjee R, Beykal B, Szafran AT, Onel M, Stossi F, Mancini MG, Lloyd D, Wright FA, Zhou L, Mancini MA, Pistikopoulos EN. 2020. Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms. PLoS Comput Biol 16:24. doi:10.1371/journal.pcbi.1008191 PMID:32970665 PMCID:PMC7538107
• Onel M, Burnak B, Pistikopoulos EN. 2020. Integrated Data-Driven Process Monitoring and Explicit Fault-Tolerant Multiparametric Control. Ind Eng Chem Res 59(6):2291-2306. doi:10.1021/acs.iecr.9b04226 PMID:32549652 PMCID:PMC7299207

2019

• Mukherjee R, Onel M, Beykal B, Szafran AT, Stossi F, Mancini MA, Zhou L, Wright FA, Pistikopoulos EN. 2019. Development of the Texas A&M Superfund Research Program computational platform for data integration, visualization, and analysis. Computer Aided Chemical Engineering 46:967-972. doi:10.1016/B978-0-12-818634-3.50162-4 PMID:31612156 PMCID:PMC6791821
• Onel M, Beykal B, Ferguson K, Chiu WA, McDonald TJ, Zhou L, House JS, Wright FA, Sheen D, Rusyn I, Pistikopoulos EN. 2019. Grouping of complex substances using analytical chemistry data: A framework for quantitative evaluation and visualization. PLoS One 14(10):e0223517. doi:10.1371/journal.pone.0223517 PMID:31600275 PMCID:PMC6786635
• Onel M, Kieslich CA, Pistikopoulos EN. 2019. A nonlinear support vector machine based feature selection approach for fault detection and diagnosis: application to the Tennessee Eastman process. AIChE Journal 65(3):992-1005. doi:10.1002/aic.16497

2018

• Avraamidou S, Beykal B, Pistikopoulos IP, Pistikopoulos EN. 2018. A hierarchical Food-Energy-Water Nexus (FEW-N) decision-making approach for Land Use Optimization. Int Symp Process Syst Eng 44:1885-1890. doi:10.1016/B978-0-444-64241-7.50309-8 PMID:30397687
• Avraamidou S, Milhorn A, Sarwar O, Pistikopoulos EN. 2018. Towards a quantitative food-energy-water nexus metric to facilitate decision making in process systems: A case study on a dairy production plant. ESCAPE 43:391-396. doi:10.1016/B978-0-444-64235-6.50071-1 PMID:30320306
• Beykal B, Boukouvala F, Floudas CA, Pistikopoulos EN. 2018. Optimal design of energy systems using constrained grey-box multi-objective optimization. Computers & Chemical Engineering 116:488-502. doi:10.1016/j.compchemeng.2018.02.017 PMID:30546167 PMCID:PMC6287910
• Onel M, Beykal B, Wang M, Grimm FA, Zhou L, Wright FA, Phillips TD, Rusyn I, Pistikopoulos EN. 2018. Optimal chemical grouping and sorbent material design by data analysis, modeling and dimensionality reduction techniques. Computer Aided Chemical Engineering 43:421-426. doi:10.1016/B978-0-444-64235-6.50076-0 PMID:30534632
• Onel M, Kieslich CA, Guzman YA, Floudas CA, Pistikopoulos EN. 2018. Big data approach to batch process monitoring: simultaneous fault detection and diagnosis using nonlinear support vector machine-based feature selection. Computers & Chemical Engineering 115:46-63. doi:10.1016/j.compchemeng.2018.03.025 PMID:30386002 PMCID:PMC6205516
• Onel M, Kieslich CA, Guzman YA, Floudas CA, Pistikopoulos EN. 2018. Reprint of: Big data approach to batch process monitoring: simultaneous fault detection and diagnosis using nonlinear support vector machine-based feature selection. Computers & Chemical Engineering 116:503-520. doi:10.1016/j.compchemeng.2018.10.016
• Onel M, Kieslich CA, Guzman YA, Pistikopoulos EN. 2018. Simultaneous fault detection and identification in continuous processes via nonlinear Support Vector Machine based feature selection. Int Symp Process Syst Eng 44:2077-2082. doi:10.1016/B978-0-444-64241-7.50341-4 PMID:30534633