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M.Sc. Joschka Winz

M.Sc. Joschka Winz Photo of M.Sc. Joschka Winz

(+49)231 755-5124

(+49)231 755-5129


Fakultät Bio- und Chemieingenieurwesen
Lehrstuhl für Systemdynamik und Prozessführung
Geschossbau 2

Room 510


Short CV

Joschka Winz studied Chemical Engineering in Dortmund from 2014-2020. During his Bachelor studies, he spent one semester abroad at Carnegie Mellon University in Pittsburgh, USA. His Bachelor thesis is titled “Adaptive sequential sampling for surrogate modelling of fugacity coefficients”. During both the Bachelor’s and Master’s degree, he worked as a student assistant to the group. He completed his Master’s degree with a Thesis titled “Parameter estimation using a dynamic simulation of batch distillation experiments”, which was conducted at BASF SE in Ludwigshafen am Rhein. In June 2020 he joined the group as a research associate.

Consultation Hour

By arrangement via E-mail.

Research Interests
  • Data-based (Surrogate) modelling

  • Adaptive sampling strategies

  • Process optimization using hybrid models



The innovation platform KEEN connects scientific institutions and industrial partners to introduce artificial intelligence (AI) technology to the process industry. The consortium investigates the implementation of different AI methods in the process industry regarding topics of process modelling, plant engineering and optimization of operation including the implementation of self-optimizing plants. [http://keen-plattform.de/]



  • Sicheres und optimiertes Betreiben von Anlagen in der Chemie- und Pharmaindustrie (SOBA)
  • Einführung in die Programmierung

Supervised Theses




articleAzadi, Winz, Leo, Klock, Engell

A hybrid dynamic model for the prediction of molten iron and slag quality indices of a large-scale blast furnace

Computers and Chemical Engineering, 2021

articleNentwich, Winz, Engell

Surrogate modeling of fugacity coefficients using adaptive sampling

Industrial & Engineering Chemistry Research, 58, 18703-18716, 2019

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