Dr. Nils Kroell
Dr. Nils Kroell

Research & Development Engineer

About Me

I work as a research & development engineer for digital solutions at STADLER Anlagenbau GmbH. My passion for environmental technologies began in school with “Jugend Forscht” competitions, leading me to pursue environmental engineering at RWTH Aachen University, where I also did my PhD on sensor-based material flow charactization and build up the “sensor technology & data science” research group at the Department of Anthropogenic Material Cycles (ANTS). My current research focuses on enhancing mechanical sorting and recycling processes using sensor technology and data science, particularly optical sensor data like NIR, VIS-RGB, and 3DLT. I apply machine and deep learning algorithms to characterize heterogeneous anthropogenic material flows and optimize the processes based on the acquired data.

Interests
  • Machine & Deep Learning
  • Data Science
  • Sensor Technology
  • Mechanical Recycling
Education
  • PhD (Dr.-Ing.) in Environmental Engineering

    RWTH Aachen University

  • M. Sc. in Environmental Engineering

    RWTH Aachen University

  • B. Sc. in Environmental Engineering

    RWTH Aachen University

Experience

  1. Research & Development Engineer

    STADLER Anlagenbau GmbH
    Research & development activities as part of STADLER’s Digital Solutions Team.
  2. Research Group Leader

    RWTH Aachen University, Department of Anthropogenic Material Cycles

    Group lead of “Sensor Technology & Data Science” research group (10 researchers & developers, since 04/2023).

    • Conceptualization and successful acquisition of 8 national and international research projects and larger research contracts (9.8+ Mio. € funding in total, 3.6+ Mio. € funding ANTS only).
    • Initiator & overall project lead of BMBF-funded research projects „ReVise“ and “ReVise-UP” in the area of plastic recycling and sensor technology (consortium of 18 industry and research institutions, 3.9 Mio. € funding).
    • Initiator of the BMBF-funded research project „KIMBA“ in the area of CDW recycling and sensor technology (consortium of 6 industry and research institutions, 1.2 Mio. € funding).
    • Applied and fundamental research in the field of sensor technology & data science for mechanical recycling processes, resulting in 26+ scientific publications (10+ as first author, www.researchgate.net/profile/Nils-Kroell).
    • Supervision of 25+ bachelor, project, and master theses on sensor technology applications in recycling processes.
    • 7 lectures per semester for course “Sensor Technology in Resource Management” (approx. 35 students; overall rating from students: 1.1 [scale from 1 {++} to 5 {–}]).
  3. Scientific Employee

    RWTH Aachen University, Department of Anthropogenic Material Cycles

    Sensor technology & machine/deep learning applications in mechanical recycling processes for plastics, construction & demolition waste & metals.

    • Applied and fundamental research in the field of sensor technology & data science for mechanical recycling processes, resulting in 26+ scientific publications (10+ as first author, www.researchgate.net/profile/Nils-Kroell).
    • Initiator & overall project lead of BMBF-funded research projects „ReVise“ and “ReVise-UP” in the area of plastic recycling and sensor technology (consortium of 18 industry and research institutions, 3.9 Mio. € funding).
    • Initiator of the BMBF-funded research project „KIMBA“ in the area of CDW recycling and sensor technology (consortium of 6 industry and research institutions, 1.2 Mio. € funding).
    • Supervision of 25+ bachelor, project, and master theses on sensor technology applications in recycling processes.
    • Head of organization team for the “Sensor-Based Sorting & Control 2022” conference (international conference with 132 participants from 14 countries and 24 expert presentations, www.sbsc.rwth-aachen.de)
    • 7 lectures per semester for course “Sensor Technology in Resource Management” (approx. 35 students; overall rating from students: 1.1 [scale from 1 {++} to 5 {–}]).
  4. Student Research Assistant

    RWTH Aachen University, Department of Processing and Recycling

    Student assistant in the research areas metal recycling and sensor technology.

    • Programming in the field of sensor technology (image processing, machine learning; Python, MATLAB).
    • Collaboration in research projects and scientific publications.
    • Research, execution and evaluation of experiments at technical lab scale.
    • Preparation of project proposals.
  5. Tutor & Student Teaching Assistant

    RWTH Aachen University

    Tutor for the courses “Principles of Mechanics and Machinery Components 1” (SoSe 2017), “Principles of Mechanics and Machinery Components 2” (WiSe 2017/18) and “Introduction to Process Engineering” (SoSe 2018).

    • Preparation and execution of global exercises (80-120 students).
    • Preparation and execution of tutorial sessions (20-40 students).
    • Preparation of exercise and exam assignments.
    • Creation of exercise and learning materials.
  6. Student Trainee & Web Developer

    BLACK 'n BLUE - IT-Lösungen

    Part-time job during my university studies.

    • Conception and implementation of web design projects.
    • Independent planning and implementation of customer trainings on content management systems for websites.
  7. Intern

    STEINERT GmbH

    Voluntary internship during my master studies.

    • Supporting customer trials and in-house research projects in the field of sensor technology and magnetic sorting.
    • Supporting feasibility studies in the field of sensor-based sorting.
    • Sensor technologies used: NIR, VIS-RGB, XRT, XRF, LIBS, Induction.
  8. Intern

    ABO Wind

    Voluntary internship on wind turbine project development in preparation for my university studies.

    • Preparation of plans and overviews in AutoCAD.
    • Support in the preparation of feasibility studies.
    • Support in the permission planning of wind farms (BImSchG).
  9. Intern

    LANUV NRW

    Voluntary school internship on surface water monitoring.

    • Automated and manual sampling of water bodies.
    • Analysis of the water samples in the laboratory.
    • Support in embedding the analysis results in early warning systems.

Education

  1. PhD (Dr.-Ing.) in Environmental Engineering

    RWTH Aachen University

    Grade: summa cum laude (with distinction) Topic: “Sensor-based characterization of anthropogenic material systems: Developing characterization methods and novel applications for optimizing the mechanical recycling of lightweight packaging waste”

    Supervisors: Univ.-Prof. Dr. rer. nat. Kathrin Greiff & Univ.-Prof. Dr. mont. Dipl.-Ing. Roland Pomberger

  2. M. Sc. in Environmental Engineering

    RWTH Aachen University

    Grade: 1.1 (with distinction) [top 0.3% of all graduates] Area of Specialisation: Recycling

    Master Thesis: “Optical material flow characterization of metal-containing fine fractions through machine learning” Grade: 1.0 (very good)

    Project Thesis: “Development of a calibration software for dual camera 3D laser triangulation measurements” Grade: 1.0 (very good)

  3. B. Sc. in Environmental Engineering

    RWTH Aachen University
    Grade: 1.3 (with distinction) [top 1.7% of all graduates]Grade: 1.3 (with distinction) [top 1.7% of all graduates] Bachelor Thesis: “Implementation of code systems for the identification of woven textiles with UV-active markers” Grade: 1.0 (very good)
Awards
Borchers’ Plaque
RWTH Aachen University ∙ October 2024
The Borchers’ Plaque is awarded by the Rector of RWTH to individuals who have completed their doctoral studies with the highest distinction, “summa cum laude".
Best Paper Award DGAW 2022 (1st place)
Deutsche Gesellschaft für Abfallwirtschaft e.V. ∙ March 2022
Prize for the best presentation by a jury of university professors (1st place out of 22 presentations; 1.500 € prize money) at the DGAW Science Congress (DGAW 2022). Presentation title: »Sensorbasierte Vorhersage von Korngrößenverteilungen durch Machine Learning Modelle auf Basis von 3D-Lasertriangulationsmessungen« [Sensor-based prediction of particle size distributions using machine learning models based on 3D laser triangulation measurements] (N. Kroell, P. Schönfelder, X. Chen, K. Johnen, A. Feil, and K. Greiff).
Best Paper Award 5th OCM Conference
Conference on Optical Characterization of Materials ∙ March 2021
Prize for the best presentation by an expert jury (1st place out of 20 presentations; book prize) at the 5th Conference on Optical Characterization of Materials (OCM 2021). Presentation title: »Fine metal-rich waste stream characterization based on RGB data: Comparison between feature-based and deep learning classification methods« (N. Kroell, K. Johnen, X. Chen, and A. Feil).
Springorium Commemorative Coin
RWTH Aachen University ∙ October 2021
The Springorium Commemorative Coin is a special honor for graduates of RWTH Aachen University with an excellent masters degree.
5x RWTH Dean’ List (Top 5%)
RWTH Aachen University ∙ September 2020
I have been awarded for being among the top 5% of students in Environmental Engineering for five of five of my academic years (2015/16, 2016/17, 2017/18, 2018/19, 2019/20).
2x Germany Scholarship
German Federal Ministry of Education and Research (BMBF) ∙ September 2020
I have been awarded with two Germany scholarships during my studies (2018/19, 2019/20).
Publications
Assessment of lossless compression algorithms and their performance on near-infrared spectral images
Maghmoumi, Abtin, Shekhar, Harsh, Scherling, Tabea, Kroell, Nils, Feil, Alexander, Greiff, Kathrin (2025). Assessment of lossless compression algorithms and their performance on near-infrared spectral images . OCM 2025 - Optical Characterization of Materials: Conference Proceedings.
Assessing the resource potential of paper and board in lightweight packaging waste sorting plants through manual analysis and sensor-based material flow monitoring
Spies, Alena Maria, Kroell, Nils, Ludes, Annika, Küppers, Bastian, Raulf, Karoline, Greiff, Kathrin (2024). Assessing the resource potential of paper and board in lightweight packaging waste sorting plants through manual analysis and sensor-based material flow monitoring . Waste Management.
Developing a prediction model in a lightweight packaging waste sorting plant using sensor-based sorting data combined with data of external near-infrared and LiDAR sensors
Schloegl, Sabine, Kamleitner, Josef, Kroell, Nils, Chen, Xiaozheng, Vollprecht, Daniel, Tischberger-Aldrian, Alexia (2024). Developing a prediction model in a lightweight packaging waste sorting plant using sensor-based sorting data combined with data of external near-infrared and LiDAR sensors . Waste Management & Research.
Mechanische Aufbereitung von Post-Consumer Verpackungsmaterialien für das werkstoffliche Recycling von Kunststoffen
Feil, Alexander, Kroell, Nils, Greiff, Kathrin (2024). Mechanische Aufbereitung von Post-Consumer Verpackungsmaterialien für das werkstoffliche Recycling von Kunststoffen . Handbuch Kreislaufwirtschaft: Recht, Ingenieur- und Naturwissenschaften, Nachhaltigkeit, Klimaschutz, Digitalisierung.
Near-infrared-based sortability of polyester-containing textile waste
Becker, Amrei, Datko, Annika, Kroell, Nils, Küppers, Bastian, Greiff, Kathrin, Gries, Thomas (2024). Near-infrared-based sortability of polyester-containing textile waste . Resources, Conservation and Recycling.
10th Sensor-Based Sorting & Control 2024
Greiff, Kathrin, Feil, Alexander, Weitkämper, Lars, Kroell, Nils, Scherling, Tabea, Gürsel, Devrim, Merz, Vincent (2024). 10th Sensor-Based Sorting & Control 2024 .
Near-infrared-based quality control of plastic pre-concentrates in lightweight-packaging waste sorting plants
Kroell, Nils, Chen, Xiaozheng, Küppers, Bastian, Schlögl, Sabine, Feil, Alexander, Greiff, Kathrin (2023). Near-infrared-based quality control of plastic pre-concentrates in lightweight-packaging waste sorting plants . Resources, Conservation and Recycling.
Towards digital twins of waste sorting plants: Developing data-driven process models of industrial-scale sensor-based sorting units by combining machine learning with near-infrared-based process monitoring
Kroell, Nils, Maghmoumi, Abtin, Dietl, Tobias, Chen, Xiaozheng, Küppers, Bastian, Scherling, Tabea, Feil, Alexander, Greiff, Kathrin (2023). Towards digital twins of waste sorting plants: Developing data-driven process models of industrial-scale sensor-based sorting units by combining machine learning with near-infrared-based process monitoring . Resources, Conservation and Recycling.
Sensor-based sorting
Chen, Xiaozheng, Kroell, Nils, Feil, Alexander, Greiff, Kathrin (2023). Sensor-based sorting . Handbook of recycling.
NIR-MFCO dataset: Near-infrared-based false-color images of post-consumer plastics at different material flow compositions and material flow presentations
Kroell, Nils, Chen, Xiaozheng, Maghmoumi, Abtin, Lorenzo, Julius, Schlaak, Matthias, Nordmann, Christian, Küppers, Bastian, Thor, Eric, Greiff, Kathrin (2023). NIR-MFCO dataset: Near-infrared-based false-color images of post-consumer plastics at different material flow compositions and material flow presentations . Data in Brief.
Sensortechnik in der Sortierung und Aufbereitung von Kunststoffverpackungen - Potenziale und Grenzen
Kroell, Nils, Chen, Xiaozheng, Feil, Alexander, Greiff, Kathrin (2023). Sensortechnik in der Sortierung und Aufbereitung von Kunststoffverpackungen - Potenziale und Grenzen .
  1. Kreislaufwirtschaftstage Münster
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Improving drum sieve performance in lightweight packaging waste recycling by automatic parameter adjustment through 3D laser triangulation-based process monitoring
Chen, Xiaozheng, Kroell, Nils, Hofmann, Benedikt, Schlögl, Sabine, Greiff, Kathrin (2023). Improving drum sieve performance in lightweight packaging waste recycling by automatic parameter adjustment through 3D laser triangulation-based process monitoring . Resources, Conservation and Recycling.
Near-infrared-based determination of mass-based material flow compositions in mechanical recycling of post-consumer plastics: Technical feasibility enables novel applications
Kroell, Nils, Chen, Xiaozheng, Küppers, Bastian, Lorenzo, Julius, Maghmoumi, Abtin, Schlaak, Matthias, Thor, Eric, Nordmann, Christian, Greiff, Kathrin (2023). Near-infrared-based determination of mass-based material flow compositions in mechanical recycling of post-consumer plastics: Technical feasibility enables novel applications . Resources, Conservation and Recycling.
Implementierung von Sensor-based Material flow Monitoring in einer Kunststoffsortieranlage
Schlögl, Sabine, Kamleitner, Josef, Kroell, Nils, Chen, Xiaozheng (2022). Implementierung von Sensor-based Material flow Monitoring in einer Kunststoffsortieranlage . Vorträge-Konferenzband zur 16. Recy & DepoTech-Konferenz.
Optimierte Sortierung von Leichtverpackungs-abfällen durch ein intelligentes Stoffstrommanagement
Kroell, Nils, Chen, Xiaozheng, Nordmann, Christian, Pfund, Elias, Lorenzo, Julius, Dietl, Tobias, Maghmoumi, Abtin, Küppers, Bastian, Feil, Alexander, Greiff, Kathrin (2022). Optimierte Sortierung von Leichtverpackungs-abfällen durch ein intelligentes Stoffstrommanagement . Vorträge-Konferenzband zur 16. Recy & DepoTech-Konferenz.
Enabling mechanical recycling of plastic bottles with shrink sleeves through near-infrared spectroscopy and machine learning algorithms
Chen, Xiaozheng, Kroell, Nils, Althaus, Malte, Pretz, Thomas, Pomberger, Roland, Greiff, Kathrin (2022). Enabling mechanical recycling of plastic bottles with shrink sleeves through near-infrared spectroscopy and machine learning algorithms . Resources, Conservation and Recycling.
Sensorbasierte Vorhersage von Korngrössenverteilungen durch Machine Learning Modelle auf Basis von 3D-Lasertriangulationsmessungen
Kroell, Nils, Schönfelder, Paula, Chen, Xiaozheng, Johnen, Kay, Feil, Alexander, Greiff, Kathrin (2022). Sensorbasierte Vorhersage von Korngrössenverteilungen durch Machine Learning Modelle auf Basis von 3D-Lasertriangulationsmessungen .
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Assessment of sensor-based sorting performance for lightweight packaging waste through sensor-based material flow monitoring: Concept and preliminary results
Kroell, Nils, Dietl, Tobias, Maghmoumi, Abtin, Chen, Xiaozheng, Küppers, Bastian, Feil, Alexander, Greiff, Kathrin (2022). Assessment of sensor-based sorting performance for lightweight packaging waste through sensor-based material flow monitoring: Concept and preliminary results . 9th Sensor-Based Sorting & Control 2022.
Relevance and challenges of plant control in the pre-processing stage for enhanced sorting performance
Küppers, B., Schlögl, Sabine, Kroell, Nils, Radkohl, Verena (2022). Relevance and challenges of plant control in the pre-processing stage for enhanced sorting performance . 9th Sensor-Based Sorting & Control 2022.
9th Sensor-Based Sorting & Control 2022
Greiff, Kathrin, Wotruba, Hermann, Feil, Alexander, Kroell, Nils, Chen, Xiaozheng, Gürsel, Devrim, Merz, Vincent (2022). 9th Sensor-Based Sorting & Control 2022 .
Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms
Kroell, Nils, Chen, Xiaozheng, Maghmoumi, Abtin, Koenig, Morgane, Feil, Alexander, Greiff, Kathrin (2021). Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms . Waste Management.
Influence of long-term natural degradation processes on near-infrared spectra and sorting of post-consumer plastics
Chen, Xiaozheng, Kroell, Nils, Dietl, Tobias, Feil, Alexander, Greiff, Kathrin (2021). Influence of long-term natural degradation processes on near-infrared spectra and sorting of post-consumer plastics . Waste Management.
Nahinfrarot-basierte Stoffstromüberwachung von Bau- und Abbruchabfällen
Parrodi, Juan Carlos Hern'andez, Kroell, Nils, Chen, Xiaozheng, Dietl, Tobias, Pfund, Elias, Küppers, Bastian, Nordmann, Christian (2021). Nahinfrarot-basierte Stoffstromüberwachung von Bau- und Abbruchabfällen . Mineralische Nebenprodukte und Abfälle.
Influences of bioplastic polylactic acid on near-infrared-based sorting of conventional plastic
Chen, Xiaozheng, Kroell, Nils, Li, Ke, Feil, Alexander, Pretz, Thomas (2021). Influences of bioplastic polylactic acid on near-infrared-based sorting of conventional plastic . Waste management & research.
Fine metal-rich waste stream characterization based on RGB data: Comparison between feature-based and deep learning classification methods
Kroell, Nils, Johnen, Kay, Chen, Xiaozheng, Feil, Alexander (2021). Fine metal-rich waste stream characterization based on RGB data: Comparison between feature-based and deep learning classification methods . OCM 2021 - Optical Characterization of Materials: Conference Proceedings.
Determining the composition of post-consumer flexible multilayer plastic packaging with near-infrared spectroscopy
Chen, Xiaozheng, Kroell, Nils, Wickel, Jan, Feil, Alexander (2021). Determining the composition of post-consumer flexible multilayer plastic packaging with near-infrared spectroscopy . Waste Management.
Determination of the composition of multilayer plastic packaging with nir spectroscopy
Chen, Xiaozheng, Kroell, Nils, Feil, Alexander, Pretz, Thomas (2020). Determination of the composition of multilayer plastic packaging with nir spectroscopy . Detritus.
Entwicklung einer Methodik zur Wertstoffgehaltsbestimmung von feinkörnigen Abfällen
Johnen, Kay, Kroell, Nils, Feil, Alexander (2020). Entwicklung einer Methodik zur Wertstoffgehaltsbestimmung von feinkörnigen Abfällen . Recy & DepoTech 2020.
Quantitative Klemmkornbestimmung mittels Bildauswertung am Beispiel der Siebung von Abfallfeinfraktionen
Johnen, Kay, Kroell, Nils (2020). Quantitative Klemmkornbestimmung mittels Bildauswertung am Beispiel der Siebung von Abfallfeinfraktionen .
  1. Wissenschaftskongress Abfall- und Ressourcenwirtschaft
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