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M.Sc. Laura Neuendorf

M.Sc. Laura Neuendorf Photo of M.Sc. Laura Neuendorf

(+49)231 755-5120

(+49)231 755-8084


Fakultät Bio- und Chemieingenieurwesen
Arbeitsgruppe ApparateDesign
Geschossbau 3

Room 513


Curriculum Vitae

Laura Neuendorf has studied Biochemical Engineering at the TU Dortmund University since 2013. She completed her bachelor thesis with the topic ‘Amphiphilic copolymer networks based on poly(2-ethyl-2-oxazoline) and poly(cis-1,4-isoprene)’ at the Chair of Biomaterials and Polymer Sciences.

After a research internship abroad at Nippon Paper Industries in Tokyo, Laura graduated with the master thesis ‘Three-dimensional investigation of droplet generation using microCT’ at the Laboratory of Equipment Design in 2020.

Since 2020 she works as a research associate at the Laboratory of Equipment Design, participating in the KEEN project (http://keen-plattform.de/). Within the scope of this project she develops AI-supported image analysis for optimal process selection of complex multiphase mixtures.


In the KEEN project, AI-based methods, models, tools and reference applications for the development and operation of chemical and biotechnological production processes are investigated, adapted and, if necessary, further developed. AI-based image analysis tools with the help of an AI-based Design of experiments for optimal process selection of extraction, crystallization and sublimation are developed. These tools enable AI-based process automation.

Thesis vacancy

You're curious about artificial intelligence and how it can be used in the process industry?

Contact me via mail and we will discuss a topic for a thesis (Bachelor or Master / German or English) or take a look at our moodle page for open vacancies.


Journal Articles

journalO. S. Bayomie, R. F. L. de Cerqueira, L. Neuendorf, I. Kornijez, S. Kieling, T. H. Sandermann, K. Lammers, N. Kockmann

Detecting flooding state in extraction columns: Convolutional neural networks vs. a white‐box approach for image‐based soft sensor development

Computers & Chemical Engineering, 2022, vol. 164, https://doi.org/10.1016/j.compchemeng.2022.107904

journalL. Neuendorf, Fatemeh Baygi, Pia Kolloch, N. Kockmann

Implementation of a Control Strategy for Hydrodynamics of a Stirred Liquid–Liquid Extraction Column Based on Convolutional Neural Networks

ACS Engineering Au, 2022, https://doi.org/10.1021/acsengineeringau.2c00014

journalJ. Oeing, L. Neuendorf, L. Bittorf, W. Krieger, N.Kockmann

Flooding Prevention in Distillation and Extraction Columns with Aid of Machine Learning Approaches

Chem. Ing. Tech., 2021, doi: 10.1002/cite.202100051

Conference Proceedings

proceedingJulia Schuler, Laura Maria Neuendorf, Kai Petersen, Norbert Kockmann

3D Investigation of Droplet Generation in a Miniaturized Coflowing Device Using Micro-Computed Tomography

ICNMM2020-1061, 2020, vol. 2020, p. V001T16A004, 10.1115/ICNMM2020-1061


talkA. Behr, L. Neuendorf, P. Sakthithasan, K. Boettcher, N. Kockmann

Process control using AI on a digital twin of an extraction column in VR

IEEE German Education Conference 2022, 11. - 12.082022, Berlin, Germany

talkL. Neuendorf, P. Kolloch, F. Baygi, M. Schwing, N. Kockmann

Online Process Monitoring and Control of an Extraction column using Machine Learning (ML)

Jahrestreffen der ProcessNet-Fachgruppen Extraktion, Phytoextrakte und Membrantechnik, 23. - 24.05.2022, Frankfurt am Main, Germany

talkL. Neuendorf, Pia Kolloch, Fatemeh Baygi, N. Kockmann

Development of a smart sensor for extraction column control

ProcessNet JT PAAT, 22.-23.11.2021


posterL. Neuendorf, P. Kolloch, M. J.Alam, L. Marsollek, P. Müller, C. Bergeest, N. Kockmann

Artificial Intelligence (AI)-based optical sensors

Workshop digitale Sensorik, 13.06.2022, Frankfurt, Germany

posterL. Neuendorf, Md Jahangir Alam, N. Kockmann

AI-based sensors for extraction column control

ProcessNet JT Fluidverfahrenstechnik, 02.-03.05.2022, Frankfurt am Main

posterLaura Neuendorf, Pascal Müller, Norbert Kockmann

Single Droplet Generation and Rising Velocity Analysis with Convolutional Neural Networks (CNNs) to estimate Fluid Properties

micro FIP2021, St. Louis, USA

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Scientific Theses

BachelorMohammad Moradi (Supervisor: Laura Neuendorf)

Modelling the control of a Spinning Band Distillation Column using Reinforcement Learning

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 18.07.22

MasterTobias Kock (Supervisor: Laura Neuendorf)

Development of a MTP based Optical AI-Sensor

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 01.07.22

MasterTimo Betting (Supervisor: Stefan Höving, Laura Neuendorf)

AI-based determination of crystal size distribution using µCT

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 09.05.22

MasterMarvin Schwing (Supervisor: Laura Neuendorf)

Deep Reinforcement Learning based Control of a stirred Extraction Column

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 09.05.22

MasterChristian Bergeest (Supervisor: Laura Neuendorf)

Liquid-Liquid Coalescence Tracking using Convolutional Neural Networks

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 06.04.2022

Show more scientific theses..