Christina Schenk

Research Associate at IMDEA Materials Institute

Presently I am a research associate at IMDEA Materials Institute in Getafe, Madrid (Spain). At IMDEA Materials, I have been collaborating with several groups developing models and algorithms enhanced by artificial intelligence concepts. In detail, my research has focused on modeling and the development of machine learning algorithms for the control of complex diffusion models applied to disease transmission dynamics and for autonomous materials discovery. Furthermore, we have been developing models for the prediction of metamaterial properties and for the prediction of steel creep behavior.
Before coming to IMDEA, I was a postdoctoral researcher in Elena Akhmatskaya's group on Modeling and Simulation in Life and Materials Sciences at BCAM for two years. Within this role, I mainly focused on predictive modeling of metabolism through Monte Carlo sampling and Machine Learning for metabolic modeling in collaboration with researchers from Lawrence Berkeley National Lab (LBL, USA) and Washington University in St. Louis (USA). I was still an affiliate researcher at LBL and a visiting fellow at BCAM for more than one more year.
Before moving to Spain, I had been a postdoctoral researcher in Lorenz Biegler´s group on Optimization and Numerical Methods for Process Design, Analysis, Operations and Control at Carnegie Mellon University in Pittsburgh, PA (USA) for almost two years.
I received my Bachelor´s, Master´s, and doctoral degree in (Applied) Mathematics from Trier University in Trier (Germany) in 2011, 2013, and 2018, respectively. My Ph.D., under the supervision of Volker Schulz in the group on PDE-Constrained Optimization, focused on Modeling, Simulation, and Optimization of Fermentation Processes.

Research

  • Modeling, simulation and optimization with particular focus on energy and healthcare applications:
    • Development of models for predicting steel creep behavior
    • Development of models for the prediction of metamaterial properties with deep learning
    • Development of models and algorithms for autonomous materials discovery
    • Mathematical modeling and development of machine learning algorithms for the control of complex diffusion models applied to disease transmission dynamics
    • Analysis of systems of reaction-diffusion equations
    • Optimal scaling for reducing model complexity for population balance models, e.g. for Latex Particles Morphology Formation
    • Machine learning for metabolic modeling and optimal design
    • Predictive metabolic modeling through advanced sampling techniques
    • Algorithm and software development for variance and parameter estimation of reaction kinetics from spectroscopic data coming from chemical or pharmaceutical processes
    • Mixed-effects models for kinetic parameter estimation
    • Robust CFD-based optimization of biogas power plants
    • Economic nonlinear model predictive control with parameter and state estimation for wine fermentation
    • Numerical modeling and analysis of integro-differential equations, systems of weakly hyperbolic differential equations or respectively reaction-advection equations
    • Population balance models

Publications

Articles

  • C. Schenk, M. Haranczyk (2024): CASTRO -Efficient constrained sampling method for material and chemical experimental design (under review, Preprint )
  • B. Ozdemir, M. Hernández-del-Valle, M. Gaunt, C. Schenk, L. Echevarría-Pastrana, J.P. Fernandez-Blazquez, D.Y. Wang, M. Haranczyk (2024): Advancing the Prediction of 3D Printability for Polymer Nanocomposites (under review, Preprint )
  • C. Schenk, A. Vasudevan, M. Haranczyk, I. Romero (2024): Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems, Optimal Control Applications and Methods (available here , Preprint )
  • M. Hernández-del-Valle, C. Schenk, L. Echevarría-Pastrana, B. Ozdemir, E. Dios-Lázaro, J. Ilarraza-Zuazo, D.-Y. Wang, and M. Haranczyk (2023): Robotically automated 3D printing and testing of thermoplastic material specimens, Digital Discovery (available here)
  • T. Backman, C. Schenk, T. Radivojevic, D. Ando, J. Singh, J. J. Czajka, Z. Costello, J. D. Keasling, Y. Tang, E. Akhmatskaya, H. Garcia Martin (2023): BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale, PLOS Computational Biology (available here , Preprint )
  • J. Bartsch, A. Borzì, C. Schenk, D. Schmidt, J. Müller, V. Schulz, K. Velten (2023): An Extended Model of Wine Fermentation Including Aromas and Acids. in: J. Wittmann, K. Chudej (eds), Simulation in den Umwelt- und Geowissenschaften, Workshop Bayreuth 2023, Berichte aus der Umweltinformatik, Shaker Verlag, ISBN: 9783844092509, pp 125-136 ( Preprint)
  • I. Romero, C. Schenk (2023): Connecting beams and continua: variational basis and mathematical analysis, Meccanica, 58:1973–1982, DOI: 10.1007/s11012-023-01702-0, (available here)
  • G. W. Roell, C. Schenk, W. E. Anthony, R. R. Carr, A. Ponukumati, J. Kim, E. Akhmatskaya, M. Foston, G. Dantas, T. S. Moon, Y. J. Tang, H. García Martín (2023): A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism, ACS Synthetic Biology, 12(6):1632–1644, DOI:10.1021/acssynbio.2c00618 (available here, Supplementary Info )
  • C. Schenk, D. Portillo, and I. Romero (2023): Linking discrete and continuum diffusion models: Well-posedness and stable finite element discretizations, Int. Journal for Numerical Methods in Engineering, 124(9):2105-2121, DOI: doi.org/10.1002/nme.7204 (available here, Preprint )
  • S. Rusconi, C. Schenk, A. Zarnescu and E. Akhmatskaya (2023): Reducing model complexity by means of the optimal scaling: Population balance model for latex particles morphology formation, Applied Mathematics and Computation, 443:127756, DOI: 10.1016/j.amc.2022.127756 (available here)
  • C. Schenk and V. Schulz (2022): Existence, Uniqueness, and Numerical Modeling of Wine Fermentation Based on Integro-Differential Equations, SIAM Journal on Applied Mathematics, 82(4), DOI: 10.1137/20M1362309 (available here, Preprint)
  • J. Bartsch, A. Borzì, J. Müller, C. Schenk, D. Schmidt, V. Schulz and K. Velten (2021): Energy conservation for wine fermentation - Nonlinear model predictive control for placement and real-time control of cooling plates, in: A. Milde, K.-H. Küfer, P. Maass and V. Schulz (eds.), "German Success Stories in Industrial Mathematics", Mathematics in Industry, Springer (available here)
  • C. Schenk, L. T. Biegler, L. Han and J. Mustakis (2020): Kinetic Parameter Estimation from Spectroscopic Data for a Multi-Stage Solid-Liquid Pharmaceutical Process, Organic Process Research & Development, DOI: 10.1021/acs.oprd.0c00277 (available here, Preprint)
  • J. Müller*, C. Schenk*, R. Keicher, D. Schmidt, V. Schulz and K. Velten (2020): Optimization of an Externally Mixed Biogas Plant Using a Robust CFD Method, Computers and Electronics in Agriculture, Volume 171, 105294, DOI: 10.1016/j.compag.2020.105294 (available here, Preprint)
  • C. Schenk*, M. Short*, J. S. Rodriguez, D. Thierry, L. T. Biegler, S. Garcia-Muñoz, W. Chen (2020): Introducing KIPET : A novel open-source software package for kinetic parameter estimation from experimental datasets including spectra, Computers and Chemical Engineering, Volume 134, 106716, DOI: 10.1016/j.compchemeng.2019.106716 (available here, Preprint)
  • M. Short, C. Schenk, D. Thierry, J. S. Rodriguez, L. T. Biegler, S. Garcia-Muñoz (2019): KIPET - An Open-Source Kinetic Parameter Estimation Toolkit, Computer Aided Chemical Engineering, Proceedings of the 9th International Conference on Foundations of Computer-Aided Process Design, Volume 47, Pages: 299-304, DOI: 10.1016/B978-0-12-818597-1.50047-3 (available here, Preprint)
  • C. Schenk, V. Schulz, A. Rosch, C. von Wallbrunn (2017): Less cooling energy in wine fermentation - A case study in mathematical modeling, simulation and optimization, Food and Bioproducts Processing, Volume 103, Pages: 131-138, DOI: 10.1016/j.fbp.2017.04.001 (available here, Preprint)
  • C. Schenk, V. Schulz (2015): Energy-optimal control of temperature for wine fermentation based on a novel model including the yeast dying phase. IFAC-PapersOnLine, 48(23), 5th IFAC Conference on Nonlinear Model Predictive Control (NMPC'15), Seville, Spain, 452-457, doi:10.1016/j.ifacol.2015.11.320 (available here, Preprint)
  • *: Co-first authors

    Preprints

    • A. Borzì, J. Merger, J. Müller, A. Rosch, C. Schenk, D. Schmidt, S. Schmidt, V. Schulz, K. Velten, C. von Wallbrunn, M. Zänglein (2014): Novel model for wine fermentation including the yeast dying phase. ArXiv-Preprint, arXiv:1412.6068 (available here)

    Book Reviews

    • C. Schenk (2019): Review of Pyomo: Optimization Modeling in Python (William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil, Bethany Nicholson, and John D. Siirola, 2nd Edition). SIAM Rev., 61(1), pp. 209-225 (available here)

    Theses

    • C. Schenk (2018): Modeling, Simulation and Optimization of Wine Fermentation, PhD thesis, Examiners: Prof. Dr. Volker Schulz (Trier University) and Prof. Dr. Lorenz T. Biegler (Carnegie Mellon University) (available here)
    • C. Schenk (2013): Optimal Design of Cardiovascular Stents, Master's thesis
    • C. Schenk (2011): Nonlocal Diffusion Equations, Bachelor's thesis

    Media

  • Tackling the green steel challenge: AID4GREENEST celebrates its one-year anniversary (2024)
  • F. Wang, Q. Gallagher, A. Gupta, C. Schenk (2024): What is the role of molecular featurization in Bayesian optimization? (Github repo), 5th Place in Bayesian Optimization Hackathon for Chemistry and Materials 27-28 March 2024, sponsored by the Acceleration Consortium and Merck KGaA
  • C. Schenk (2024): Image contribution to 2024 Math Remix Creative Challenge
  • Postdoctoral Research at IMDEA Materials with Christina Schenk (2023)
  • C. Schenk (2023) - Testimonial, Her Maths Story (available here)
  • C. Schenk (2023) - Testimonial, Mathematics Embassy at Trier University (in German) (available here)
  • The Voices of IMDEA Materials - Volume 1 (2022)
  • Get to know IMDEA Materials with Christina Schenk (2022)
  • C. Schenk (2021) - Testimonial, Women at BCAM, BCAM Activity Report 2020 (available here)
  • C. Schenk (2021) - Testimonial, FemSTEM (available here)
  • C. Schenk (2021) - Talk at San Felix School in Ortuella to 13-year-old students on "The role of hidden figures for becoming the next Katherine Johnson, Marie Curie or Ada Lovelace" ("El papel de las figuras ocultas para convertirse en la próxima Katherine Johnson, Marie Curie o Ada Lovelace") (in English and Spanish) as part of the "11 de febrero” initiative in the context of the International Day of Women and Girls in Science, BCAM News Article.
  • Article on our "Optimization of an Externally Mixed Biogas Plant Using a Robust CFD Method" article in “Mapping Ignorance”: Optimal mixer placement in industrial-size biogas fermenters by César Tomé López (2020) (available here)
  • C. Schenk (2020): The scientists who inspired us (I): Ada Lovelace, BCAM News (available here)
  • L. Biegler: The Optimization of Chemical Engineering
  • Zauberei im Keller (German)
  • Study Mathematics at Trier University (German)
  • C. Schenk (STEM Woman) (since 2015): MINT-Frau (STEM Woman) Ada Lovelace Project (in German) (Profile available here)
  • Activities

    Upcoming Conferences/Workshops/Courses/Talks

    • 12/2024: Invited seminar talk at Trier University, Germany
    • 01/2025: Invited minisymposium talk at 16th Dynamical Systems Applied to Biology and Natural Science - DSABNS 2025 Conference, Naples, Italy
    • 02/2025: Invited talk at 4th Workshop on Optimal Control of Dynamical Systems and Applications, Villány, Hungary

    Past Conferences/Workshops/Courses/Talks

    • 09/2024: Invited SIAM - MTM joint seminar talk on "Computationally Guided Experiments and Predictions: A Path to Sustainable Materials" at KU Leuven, Leuven, Belgium
    • 09/2024: Presentation on "ACBICI – A Library for the Calibration of Complex and Expensive Models", Congress on Numerical Methods in Engineering 2024, Aveiro, Portugal
    • 05/2024: Presentation on "Calibrating Complex Material Models: A Comparative Analysis of Bayesian-Based, Optimization-Based and Neural Network-Based Approaches in the Presence of Uncertainty", SIAM Conference on Math. Aspects of Materials Science (MS24), Pittsburgh, PA, USA
    • 03/2024: Poster presentation on "A Novel Constrained Design of Experiments Technique Incorporating Experimental Knowledge for Computationally Guided Materials Experimentation" and gpCAM software demo at 2nd International Seminar on Modelling, Simulation and Machine Learning for the Rapid Development of Porous Materials, IMDEA Materials, Getafe, Spain
    • 02-03/2024: Poster presentation on "A Novel Constrained Design of Experiments Technique Incorporating Experimental Knowledge for Computationally Guided Materials Experimentation" at SIAM Conference on Uncertainty Quantification (UQ24), Trieste, Italy
    • 02/2024: Invited talk on "Mathematical modeling and control of thermal and disease transmission dynamics" at 15th Dynamical Systems Applied to Biology and Natural Science - DSABNS 2024 Conference, NOVA School of Science and Technology/FCT NOVA, NOVA University of Lisbon, Caparica, Portugal
    • 09/2023: Invited keynote on "Physical model-based, probabilistic and data-driven methods for a sustainable energy and materials future" at Workshop on Simulation and Optimization for Sustainable Engineering, University of Cantabria, Department of Chemical and Biomolecular Engineering, Santander, Spain
    • 11/2022: Invited seminar talk at Basque Center for Applied Mathematics on "Modeling and Reinforcement Learning-Based Control for Thermal and Disease Transmission Dynamics Problems", BCAM, Bilbao, Spain and online (available here)
    • 04/2022: Artificial Intelligence for the Fight Against COVID-19 Workshop, Bilbao, Spain
    • 11/2021: New Bridges Between Mathematics and Data Science Conference, University of Valladolid, Valladolid, Spain
    • 09/2021: DFG-SPP 1962 Summer School on Optimization under Uncertainty, Virtual Event (Philipps-Universität Marburg, Germany)
    • 08/2021: 13th International Conference on Monte Carlo Methods and Applications (MCM 2021), Virtual Event (University of Mannheim, Mannheim, Germany)
    • 07/2021: ALOP Workshop on Nonlocal Models, Virtual Event (Trier University, Trier, Germany)
    • 05/2021: SIAM Conference on Mathematical Aspects of Materials Science (MS20), Bilbao, Spain (Postponed from 2020 to 2021)
    • 04/2021: Workshop on Autonomous Discovery in Science and Engineering, Virtual Event (The Center for Advanced Mathematics for Energy Research Applications (CAMERA), Berkeley Lab, Berkeley, CA, USA)
    • 04/2021: 21st ECMI Conference on Industrial and Applied Mathematics, Invited talk on "Optimization Problems Arising in the Complex Industrial Processes of Wine Fermentation and Polymerization", Virtual Event (Bergische Universität Wuppertal, Wuppertal, Germany)
    • 02/2021: Invited plenary talk at 12th Dynamical Systems Applied to Biology and Natural Science - DSABNS 2021 Conference on "Predictive Mathematical Modeling of Dynamical Particle Morphology Formation in Polymerization Processes", Virtual Event (BCAM, Bilbao, Spain)
    • 12/2020: Invited talk in ALOP-Colloquium at Trier University, Department of Mathematics, on "Population Balance Modeling, Simulation and Optimization: From Wine Fermentation to Polymerization", Virtual Event (Trier, Germany)
    • 12/2020: Invited talk at BCAM Scientific Advisory Committee Annual Meeting 2020, on "Metabolic and Population Balance Modeling, Simulation and Optimization", Virtual Event (BCAM, Bilbao, Spain)
    • 11/2020: Invited seminar talk at the University of Surrey, Department of Chemical and Process Engineering, on "Population Balance Modeling, Simulation and Optimization for Advancements in Industrial Processes", Virtual Event (Guildford, England)
    • 08/2020: 14th International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing (MCQMC 2020), Virtual Event (Oxford, England)
    • 7/2020: GAMM Juniors' Summer School on Learning Models from Data: Model Reduction, System Identification and Machine Learning - SAMM 2020 (Participation and poster presentation on "A Hamiltonian Monte Carlo Bayesian Inference Approach Using Deep Learning for Modeling Metabolism"), Virtual Event (Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany)
    • 11/2019: Invited seminar talk at Carnegie Mellon University, Department of Mathematical Sciences, Center for Nonlinear Analysis, on "Numerical modeling of wine fermentation based on coupled weakly hyperbolic nonlinear integro-differential equations", Pittsburgh, PA, USA
    • 10/2019: ChEGSA Research Symposium (Participation), Pittsburgh, PA, USA
    • 08/2019: 2019 YinzOR Student Conference (Participation), Pittsburgh, PA, USA
    • 08/2019: Invited talk at TU Berlin on "Kinetic Parameter Estimation Based on Spectroscopic Data of Drug Manufacturing Processes - An Application-Oriented Approach", Berlin, Germany
    • 08/2019: International Conference on Continuous Optimization (ICCOPT) (Participation, co-organizer of minisymposium, session chair and talk on "Kinetic Parameter Estimation Based on Spectroscopic Data and Its Application to Drug Manufacturing Processes"), Berlin, Germany
    • 07/2019: Invited talk at Festo AG & Co. KG on "Economic nonlinear model predictive control with parameter and state estimation for energy conservation during wine fermentation - related challenges and solution approaches", Denkendorf, Germany
    • 07/2019: Invited talk at Trier University on "Investigations for Kinetic Parameter Estimation of Drug Manufacturing Processes - An Application-Oriented Approach", Trier, Germany
    • 05/2019: Cell Modeling Workshop (Participation), Pittsburgh Supercomputing Center, Pittsburgh, PA, USA
    • 03/2019: CAPD Annual Review Meeting (Participation and poster presentation on "Parameter Identification of Reaction Kinetics from Spectroscopic Data for Pharmaceutical Processes"), Pittsburgh, PA, USA
    • 02/2019: Invited Talk at Pfizer Inc. on ``Parameter Identification of Reaction Kinetics from Spectroscopic Data - Pfizer Case Studies", Groton, CT, USA
    • 10-11/2018: AIChE Annual Meeting 2018 (Participation and talk on "Parameter Estimation of Reaction Kinetics from Spectroscopic Data - Developments and Applications"), Pittsburgh, PA, USA
    • 10/2018: ChEGSA Research Symposium (Participation), Pittsburgh, PA, USA
    • 08/2018: 2018 YinzOR Student Conference (Participation), Pittsburgh, PA, USA
    • 08/2018: 6th IFAC Conference on Nonlinear Model Predictive Control (Participation and poster presentation on "Economic Nonlinear Model Predictive Control with Parameter and State Estimation - Energy Conservation During Wine Fermentation"), Madison, WI, USA
    • 08/2018: MOPTA Conference 2018 (Participation and talk on "Kinetic Parameter Identification Based on Spectroscopic Data - Advancements Illustrated by Case Studies"), Bethlehem, PA, USA
    • 08/2018: Invited talk at Trier University on "Parameter Estimation for Pharmaceutical Processes - Advancements and Case Studies", Trier, Germany
    • 07/2018: IFIP TC 7 Conference on System Modelling and Optimization (Participation and invited talk on "Optimal Control of Wine Fermentation"), Essen, Germany
    • 08/2017: Autumn School: Optimization in Machine Learning and Data Science, Trier, Germany
    • 11/2017: Invited talk on "LaTeX - Not Only for Natural Scientists", Brownbag Event of the Center for Equal Opportunities at Trier University, Trier, Germany
    • 07/2017: SIAM Conference on Control and Its Applications (Participation, co-organizer of minisymposium, session chair and talk on "Nonlinear Optimal Feedback Control for Wine Fermentation by Economic NMPC"), Pittsburgh, PA, U.S.A.
    • 06/2017: ROENOBIO Workshop (Participation and talk on "Investigations for energy-optimal control of wine fermentation"), Würzburg, Germany
    • 04/2017: Campus Dialogue Research (Invited poster presentation on "Magic in the Wine Cellar - Mathematics for the Energy-Optimization of Wine Fermentation"), Trier University, Trier, Germany
    • 03/2017: Workshop Women in Optimization (Participation), Trier, Germany
    • 02/2017: KoMSO Challenge Workshop - Challenges for Mathematical Modeling, Simulation and Optimization for Advanced Process Control of Batch Processes (Participation), Heidelberg, Germany
    • 09-10/2016: SIAM Conference on Mathematics of Planet Earth (Participation and talk on "Energy-optimal control of temperature for wine fermentation"), Philadelphia, PA, U.S.A.
    • 04/2016: SIGOPT - International Conference on Optimization (Participation and session chair), Trier, Germany
    • 03/2016: KoMSO Challenge Workshop - Mathematical Modeling, Simulation and Optimization in Food Industries (Participation and talk on "Economic model predictive control with parameter and state estimation for energy consumption during wine fermentation"), Trier, Germany
    • 03/2016: Joint Annual Meeting of DMV and GAMM 2016 (Participation and talk on "Robust optimization of inlet orientation and outlet position of biogas plants"), Braunschweig, Germany
    • 09/2015: 5th IFAC Conference on Nonlinear Model Predictive Control (Participation and poster presentation on "Energy-optimal control of temperature for wine fermentation based on a novel model including the yeast dying phase"), Seville, Spain
    • 08/2015: 4th Symposium of the German SIAM Student Chapters (Participation), Trier, Germany
    • 07/2015: OpenFOAM Introductory Course (Participation), Genoa, Italy
    • 03/2015: 86th Annual Meeting of the International Association of Applied Mathematics and Mechanics - GAMM 2015 (Participation and talk on "Numerical simulation for wine fermentation based on IDEs"), Lecce, Italy
    • 03/2015: Workshop Women in Optimization (Participation and poster presentation on "MSO - Modeling, simulation and optimization of fermentation processes"), Heidelberg, Germany
    • 09/2014: Workshop MSO-Tools 2014 (Participation and talk on "Modeling, simulation and parameter estimation for wine fermentation"), Berlin, Germany
    • 08/2014: 3rd Symposium of the German SIAM Student Chapters (Participation and talk on "Numerical modeling of wine fermentation"), Magdeburg, Germany
    • 04/2014: Campus Dialogue Research (Invited poster presentation on "ROENOBIO - Robust Energy-Optimization of Fermentation Processes for the Production of Biogas and Wine"), Trier University, Trier, Germany
    • 03/2014: 85th Annual Meeting of the International Association of Applied Mathematics and Mechanics - GAMM 2014 (Participation and talk on "Parameter estimation of wine fermentation with respect to the mass structure of yeast cells"), Erlangen, Germany
    • 02/2014: Compact Course and Challenge Workshop on Industrial Optimization (Participation), Heidelberg, Germany
    • 08/2013: 2nd Symposium of the German SIAM Student Chapters (Participation), Heidelberg, Germany
    • 07/2013: Summer School in Computational Engineering Sciences (Participation), Luxembourg, Luxembourg

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