Publications and Research Talks

Zachary A. Kilwein, Suryateja Ravutla, and Fani Boukouvala. "Incorporating Neural ODEs into DAE-Constrained Optimization Problems." International Conference on Learning Representations (ICLR) 2025, under review.

Suryateja Ravutla, and Fani Boukouvala. "Effects of Surrogate Hybridization and Adaptive Sampling for Simulation-Based Optimization." Industrial & Engineering Chemistry Research, accepted.

Suryateja Ravutla, and Fani Boukouvala. "Data-Driven Lipschitz-Informed Convex Underestimators for Branch-And-Bound Optimization of Black-Box Functions." Journal of Global Optimization, under review.

Yuya Takakura, Suryateja Ravutla, Kim Jinsu, Keisuke Ikeda, Hiroshi Kajiro, Tomoyuki Yajima, Junpei Fujiki, Fani Boukouvala, Matthew Realff, Yoshiaki Kawajiri. "Surrogate model optimization of vacuum pressure swing adsorption using a flexible metal organic framework with hysteretic sigmoidal isotherms." International Journal of Greenhouse Gas Control, Volume 138, 2024, 104260, ISSN 1750-5836.

Suryateja Ravutla, and Fani Boukouvala. "Integrating Hybrid Modeling and Multifidelity Approaches for Data-Driven Process Model Discovery." LAPSE, Systems and Control Transactions (2024), Volume 3: pg 351 - 358.

Suryateja Ravutla, Jianyuan Zhai, and Fani Boukouvala. "Hybrid Modeling and Multi-Fidelity Approaches for Data-Driven Branch-and-Bound Optimization." In Computer Aided Chemical Engineering, vol. 52, pp. 1313-1318. Elsevier, 2023.

Kim, Sun Hye, Héctor Octavio Rubiera Landa, Suryateja Ravutla, Matthew J. Realff, and Fani Boukouvala. "Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption." Chemical Engineering Research and Design 188 (2022): 1013-1028

Andrew J Medford, Fani Boukouvala, Martha A Grover, David S Sholl, Carson Meredith, Pengfei Cheng, Sihoon Choi, Gabriel Sabenca Gusmao, Zachary A Kilwein, Suryateja Ravutla, Fatimah Wirth, Zaid Sewer and Jennifer L Wooley. "Online Graduate Certificate in Data Science for the Chemical Industry." Chemical Engineering Education 56, no. 4 (2022).

Abha Saxena, Suryateja Ravutla, Kishalay Mitra, Jayanta Chakraborty, David Murhammer, and Lopamudra Giri. "Evolution of a single-cell predictive model for packaging and budding of viruses based on TEM based measurements." Authorea Preprints (2021).

Abha Saxena, Suryateja Ravutla, Vikas Upadhyay, Soumya Jana, David Murhammer, and Lopamudra Giri. "Statistical modeling of cell-to-cell variability in viral infection during passaging in suspension cell culture: Application in Monte-Carlo simulation." Biotechnology and bioengineering 117, no. 5 (2020): 1483-1501.

Vikas Upadhyay,  Suryateja Ravutla, Vaibhav Dhyani, Kevin George, Sarpras Swain, Kishalay Mitra, and Lopamudra Giri. "A model screening framework for the generation of Ca 2+ oscillations in hippocampal neurons using differential evolution." In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 961-964. IEEE, 2019.

Sarpras Swain, Sathish Ande, Suryateja Ravutla, Soumya Jana, and Lopamudra Giri. "Spatially resolved calcium spiking in hippocampal neurons: Estimation via confocal imaging and model-based simulation." In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 279-283. IEEE, 2017.

Integrating Hybrid-Modeling with Sparse Regression - a Two-Stage Approach for Discovering Dynamics from Data. Suryateja Ravutla, and Fani Boukouvala - AIChE 2024, upcoming, October 2024

Integrating Hybrid Modeling and Multifidelity Approaches for Data-Driven Process Model Discovery. Suryateja Ravutla, and Fani Boukouvala - FOCAPD, July 2024.

Sampling-Based vs. Surrogate-Based Techniques for Data-Driven Optimization: A Comparison of Adaptive Sampling and Hybrid-Modeling Approaches. Suryateja Ravutla, and Fani Boukouvala - ChBE Graduate Symposium, Georgia Tech, 2024.

Sampling-Based vs. Surrogate-Based Techniques for Data-Driven Optimization: A Comparative Study of Adaptive Sampling and Hybrid-Modeling Approaches. Suryateja Ravutla, and Fani Boukouvala - 2023 AIChE Fall Meeting.

Data-Driven Lipschitz-Informed Convex Underestimators for Branch-And-Bound Optimization of Black-Box Functions. Suryateja Ravutla, and Fani Boukouvala - WCGO 2023.

Hybrid Modeling and Multi-Fidelity Approaches for Data-Driven Branch-and-Bound Optimization. Suryateja Ravutla, Jianyuan Zhai, and Fani Boukouvala - ESCAPE-33.

A Simultaneous Material Screening and Process Optimization Approach for Carbon Capture Using Machine Learning. Suryateja Ravutla, Kim, Sun Hye, Héctor Octavio Rubiera Landa, Matthew J. Realff, and Fani Boukouvala - 2023 AIChE Spring Meeting.

Multi-Fidelity Surrogate Models to Generate Low-Fidelity Data for Data-Driven Branch-and-Bound Optimization. Suryateja Ravutla, Jianyuan Zhai, and Fani Boukouvala - 2023 AIChE Spring Meeting.

Data-driven Spatial Branch-and-bound Algorithm For Black-box and Simulation Optimization. Suryateja Ravutla and Fani Boukouvala - 2023 CRIDC, Georgia Tech.

Global Convergence Analysis of Data-Driven Spatial Branch-and-Bound Algorithms. Suryateja Ravutla, Jianyuan Zhai, and Fani Boukouvala - 2022 AIChE Annual Meeting.

A Simultaneous Material Screening and Process Optimization Approach for Carbon Capture using Machine Learning. Suryateja Ravutla, Sun Hye Kim, Héctor Octavio Rubiera Landa, Matthew J. Realff, and Fani Boukouvala - Direct Air Capture Center (DirACC) launch, November 2022.

PyDDSBB: A Python Package for Simulation-Optimization Using Data-Driven Branch-and-Bound Techniques. Jianyuan Zhai, Suryateja Ravutla and Fani Boukouvala - 2021 AIChE Annual Meeting.

Efficient Optimization and Accurate Approximation Using Surrogate Models – Tools and Case Studies from RAPID Synopsis Project. Bianca Williams, Sun Hye Kim, Mohammed Sadaf Monjur, Suryateja Ravutla, Fani Boukouvala, Selen Cremaschi, M M Faruque Hasan, Simon Leyland and Joannah Otashu - 2021 AIChE Annual Meeting