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Bild  Malin Lachmann

Malin Lachmann

Research Assistant WG Optimization and Optimal Control

Room: NEOS 3310
Email: mlachman@uni-bremen.de
Phone: (0421) 218-64355
ORCID iD:  0000-0002-6313-4415

Presentations

Malin Lachmann, Francesca Jung, Markus Weber, Christof Büskens: Computationally efficient identification of databased models applied to a milk cooling system, CCIS Conference of Computational Interdisciplinary Science, Atlanta, March 19, 2019
Malin Lachmann, Francesca Jung, Christof Büskens: Identification of Databased Models to Forecast Renewable Energy Generation , 3rd IMA Conference on the Mathematical Challenges of Big Data, London, December 11, 2018

Public Relations

04/2021 Presentation "Mathematikstudium und dann?", Studien- und Berufsinformationstag for high school students of the high schools in Stade, Germany, Vincent-Lübeck-Gymnasium Stade, April 24, 2021
03/2021 Jury member student competion "Jugend forscht" in the area Mathematics/Computer Science, Regional competition in Bremen-Mitte, Bremen, March 2021
10/2020 Participation in the event "Nachgefragt! Math-IT – GIRLS, go!" for (female) high school students, U Bremen, October 8, 2020
10/2020 Jury member "Fachpreis Mathematik der Dr. Hans Riegel-Stiftung 2020" (Award for senior projects of high school students)
02/2020 Jury member student competion "Jugend forscht" in the area Mathematics/Computer Science, Regional competition in Bremen-Mitte, Bremen, February 2020
10/2019 Jury member "Fachpreis Mathematik der Dr. Hans Riegel-Stiftung 2019" (Award for senior projects of high school students)
2016-2019 Participation in the conceptual design and implementation of the "Optimization Research Days" for high school students
03/2019 Jury member student competion "Jugend forscht" in the area Mathematics/Computer Science, Regional competition in Bremen-Mitte, Bremen, March 2019
10/2018 Jury member "Fachpreis Mathematik der Dr. Hans Riegel-Stiftung 2018" (Award for senior projects of high school students)
02/2018 Jury member student competion "Jugend forscht" in the area Mathematics/Computer Science, Regional competition in Bremen-Mitte, Bremen, February 2018
11/2017 Presentation "Mathematikstudium und dann?", Studien- und Berufsinformationstag for high school students of the high schools in Stade, Germany, Vincent-Lübeck-Gymnasium Stade, November 11, 2017
11/2017 Jury member "Fachpreis Mathematik der Dr. Hans Riegel-Stiftung 2017" (Award for senior projects of high school students)

Research Areas

Projects

  1. hyBit: Hydrogen for Bremen's industrial transformation (01.09.2022 - 28.02.2026)
  2. SmartFarm (01.01.2016 - 31.03.2019)

Courses (Selection)complete list

  1. Anwendungen von Optimierung in Energie und Umwelt (Sommersemester 2021)
  1. Übungen Mathematik 2b für Produktionstechniker (Sommersemester 2020)
  2. Übungen Mathematik 2a für Produktionstechniker (Wintersemester 2019/2020)
  3. Übungen Mathematik 1b für Produktionstechniker und Wirtschaftsingenieure (Sommersemester 2019)

Theses (Selection)complete list

  1. Physikalische und datenbasierte Modellierung einer Wärmepumpe im Vergleich (Miriam Wilks)
  2. Modellreduktion in der Datenbasierten Modellierung mittels k-facher Kreuzvalidierung (Matthias Otten)

Publications (Selection)complete list

  1. M. Lachmann, C. Büskens.
    A Hybrid Approach for Data-Based Models Using a Least-Squares Regression.
    OLA 2021 Int. Conf on Optimization and Learning.

    DOI: 10.1007/978-3-030-85672-4_5

  2. M. Lachmann, J. Maldonado, W. Bergmann, F. Jung, M. Weber, C. Büskens.
    Self-Learning Data-Based Models as Basis of a Universally Applicable Energy Management System.
    Energies, 13(8), 2084, 2020.

    DOI: 10.3390/en13082084

  3. M. Lachmann, F. Jung, C. Büskens.
    Computationally efficient identification of databased models applied to a milk cooling system.
    Conference of Computational Interdisciplinary Science, CCIS, 19.03.-22.03.2019, Atlanta, USA.
    Campinas: Galoa, 2020.

    online at: https://proceedings.science/ccis-2019/papers/computationally-efficient-identification-of-databased-models-applied-to-a-milk-cooling-system

  4. F. Jung, M. Lachmann, C. Büskens.
    SmartFarm - Data based optimization for optimal energy management.
    88th GAMM Annual Meeting of the international Association of Applied Mathematics and Mechanics (GAMM).
    Proc. Appl. Math. Mech., 17(1):741-742, 2017.

    DOI: 10.1002/pamm.201710338