Publikationen von Edgar Ivan Sanchez Medina

Griehl, C.; Sanchez Medina, E. I.; Sundmacher, K.: Rapid phosphine ligand discovery in homogeneous catalysis: Bayesian optimization approach for low-throughput experimentation. CHISA 2024, Prague, Czech Republic (2024)

König-Mattern, L.; Sanchez Medina, E. I.; Rihko-Struckmann, L.; Sundmacher, K.: Machine learning-based solvent screening for lignocellulose biorefineries and lignin upgrading. BioSPRINT Spring School: Opportunities and challenges of process intensification application in lignocellulosic biorefineries, Frankfurt am Main, Germany (2024)

Peterson, L.; Sanchez Medina, E. I.; Khalid, M. M.; Sundmacher, K.: Surrogate modeling of dynamical systems: deep learning or model-order reduction? ECML 2024 (ML4CCE workshop), Vilnius, Lithuania (2024)

Sanchez Medina, E. I.; Linke, S.; Stoll, M.; Sundmacher, K.: Predicting Activity Coefficients at Infinite Dilution Using Hybrid Residual Graph Neural Networks. 2022 AIChE Annual Meeting, Phoenix, USA (2022)

Sanchez Medina, E. I.; Linke, S.; Sundmacher, K.: Prediction of Bioconcentration factors (BCF) using Graph Neural Networks. 31st European Symposium on Computer-Aided Process Engineering (ESCAPE-31), Istanbul, Turkey (2021)

Sanchez Medina, E. I.; Rodriguez Vallejo, D.; Chachuat, B.; Sundmacher, K.; Petsagkourakis, P.; del Rio Chanona, E. A.: Acyclic modular flowsheet optimization using multiple trust regions and Gaussian process regression. 31st European Symposium on Computer-Aided Process Engineering (ESCAPE-31), Istanbul, Turkey (2021)

Sanchez Medina, E. I.: Hybrid Graph Neural Networks for the prediction of activity coefficients in separation processes. Dissertation, Otto-von-Guericke-Universität, Magdeburg (2024)

Sanchez Medina, E. I.; Sundmacher, K.: Graph Neural Networks embedded into Margules model for vapor-liquid equilibria prediction. (2025)