Funda Iseri

Ph.D. Student funda_iseri@tamu.edu

Publications

  1. Iseri, H.; Iseri, F.; El-Halwagi, M.; Iakovou, E.; Pistikopoulos, E. N. A Data-Driven Optimization Framework for the Design and Operations of Adaptive and Resilient Energy Supply Chain Networks under Uncertainty. ESCAPE-36; 2026; p Submitted.
  2. Abdelhady, M.; Iseri, F.; Iseri, H.; Iakovou, E.; Pistikopoulos, E. N. Cost-Competitive and Sustainable Energy Portfolios for AI Infrastructure / Data Centers. SuSChemE; 2026; p Accepted.
  3. Iseri, F.; Iseri, H.; El-Halwagi, M. M.; Iakovou, E.; Pistikopoulos, E. N. Adaptive Energy Systems Planning: A Rolling Horizon Framework with AI-Enabled Scenario Generation. Applied Energy 2026, 424, 128500.
  4. Iseri, H.; Iseri, F.; Iakovou, E.; Pistikopoulos, E. N. Adaptive Risk-Aware Rolling-Horizon Microgrid Operations with Contextual Learning. FOCAPO-CPC 2027; 2026; p Accepted.
  5. Iseri, H.; Iseri, F.; Turkay, M.; Iakovou, E.; Pistikopoulos, E. N. AI-based Adaptive Forecasting under Evolving Uncertainty in the Energy Sector: STORM. Submitted 2026,.
  6. Iseri, F.; Iseri, H.; Shah, H.; Iakovou, E.; Pistikopoulos, E. N. Planning Strategies in the Energy Sector: Integrating Bayesian Neural Networks and Uncertainty Quantification in Scenario Analysis & Optimization. Computers and Chemical Engineering 2025, Accepted.
  7. Iseri, F.; Iseri, H.; Iakovou, E.; Pistikopoulos, E. N. A Circular Economy Systems Engineering Framework for Waste Management of Photovoltaic Panels. Industrial & Engineering Chemistry Research 2025, Accepted.
  8. Iseri, H.; Iseri, F.; El-Halwagi, M.; Iakovou, E.; Pistikopoulos, E. N. A Multi-Objective Optimization Framework for Renewable Energy Transportation. International Journal of Hydrogen Energy 2025, Accepted.
  9. Iseri, F.; Iseri, H.; Chrisandina, N. J.; Iakovou, E.; Pistikopoulos, E. N. AI-Based Predictive Analytics for Enhancing Data-Driven Supply Chain Optimization. Journal of Global Optimization 2025, Accepted.
  10. Montano Flores, B. S. M.; Iseri, F.; Iseri, H.; Kakodkar, R.; Serrate Cuellar, W. O.; Mejia Brown, G.; Lazo Duabyakosky, M.; Pappas, K.; Pistikopoulos, E. N. A Multiscale Framework for the Design and Analysis of Energy Systems in Bolivia. Submitted 2025,.
  11. Iseri, H.; Iseri, F.; El-Halwagi, M.; Iakovou, E.; Pistikopoulos, E. N. An Enhanced Decision-Making Framework for Designing Renewable Energy Supply Chains. International Conference on Intelligent and Fuzzy Systems; 2025; pp 722-732.
  12. Iseri, F.; Iseri, H.; Iakovou, E.; Pistikopoulos, E. N. Advances in Data-Driven Scenario Generation Powered by Machine Learning and Stochastic Modeling. International Conference on Intelligent and Fuzzy Systems; 2025; pp 321-329.
  13. Iakovou, E.; Pistikopoulos, E. N.; Walzberg, J.; Iseri, F.; Iseri, H.; Chrisandina, N. J.; Vedant, S.; Nkoutche, C. Next-Generation Reverse Logistics Networks of Photovoltaic Recycling: Perspectives and Challenges. Solar Energy 2024, 271, 112329.
  14. Iseri, F.; Iseri, H.; Chrisandina, N. J.; Vedant, S.; Iakovou, E.; Pistikopoulos, E. Design of a Reverse Supply Chain Network for Photovoltaic Panels. ESCAPE-34; 2024.
  15. Baratsas, S.; Iseri, F.; Pistikopoulos, E. N. A Hybrid Statistical and Machine Learning Based Forecasting Framework for the Energy Sector. Computers and Chemical Engineering 2024, 108740.
  16. Baratsas, S.; Iseri, F.; Pistikopoulos, E. A hybrid forecasting framework for the energy sector. ESCAPE-33; 2023; pp 539-545.
  17. Aghayev, Z.; Walker, G.; Iseri, F.; Ali, M.; Pistikopoulos, E.; Beykal, B. Binary Classification of the Endocrine Disrupting Chemicals by Artificial Neural Networks. ESCAPE-33; 2023; pp 2631-2636.
  18. Allen, R C.; Iseri, F.; Demirhan, C D.; Pappas, I.; Pistikopoulos, E. N Improvements for decomposition based methods utilized in the development of multi-scale energy systems. Computers & Chemical Engineering 2023, 108135.
  19. Aghayev, Z.; Iseri, F.; Ali, M.; Pistikopoulos, E.; Beykal, B. Predicting the estrogenic potential of chemical contaminants through high-throughput image analysis and supervised machine learning algorithms. ACS Fall Meeting; 2023; p Presented.

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