Maximilian Geisslinger

Research Scientist

Software Developer

Technology and Philosophy

AI and Robotics

Contact Me
About Me

Hi! I’m Max.
With the recent submission of my PhD thesis about autonomous driving ethics, I bring over four years of experience in the interdisciplinary field of computer science and philosophy. I am currently looking for new challenges in leveraging AI for the greater good at the forefront of technical advancement.

More than 5 years of coding experience
3 years of leadership experience
13 peer-reviewed published papers
5 open-source repositories
Resume
Experience
2020 - Present
Research Group Leader
TU Munich

Developing the next generation of autonomous driving software with a team of up to 15 PhD students

2019 - Present
Research Associate
Institute of Automotive Technology & Munich Institute for Robotics and Machine Intelligence

Interdisciplinary research on integrating ethical theories into autonomous driving algorithms.

2018 - 2019
Master Thesis
University Paul Sabatier (Toulouse) & TU Munich

Developing a novel method on camera radar fusion within an international student team.

2017 - 2017
Working Student
BMW Motorsport

Powertrain development and testing

2015 - 2017
Student Research and Teaching Assistent
TUM Institute of Automotive Technology

Driving simulation for ADAS

2016 - 2016
Intern
BMW Motorsport

Powertrain development and testing

2015 - 2015
Intern
Rolls-Royce Ltd & Co KG

Manufacturing engieering and stastical analysis

Education
2019 - Present
Ph.D. Student
Technical Unversity of Munich

Thesis: An Ethical and Risk-aware Framework for Motion Planning of Auontomous Vehicles

2016 - 2019
Master of Science
Technical University of Munich

Automotive Technology

2013 - 2016
Bachelor of Science
Technical University of Munich

Mechanical Engineering

Skills & Interests
Languages
German (native), English (fluent), Latin (Latinum), Ancient Greek (Graecum)
Technology
Python, C++, Git, Matlab/Simulink, Excel VBA
Societies
KI Bundesverband, Program Committee Autonomous Driving Conference
Interests
Machine Learning, Hiking, Skiing, Running

Awards & Honors
  • 2022 IEEE ITS Outstanding Application Award with the TUM Autonomous Motorsport team
  • 2021 Winner (1st place) of the Indy Autonomous Challenge with 1 Mio. $ price award (Video)
  • 2nd place at the Autonomous Challenge @ CES in Las Vegas with 50k $ price award
  • 2nd place at the ANSYS simulation race with 50k $ price award
List of Publications
List of Publications
  1. M. Geisslinger, F. Poszler, and M. Lienkamp, “An Ethical Trajectory Planning Algorithm for Autonomous Vehicles,” Nat. Mach. Intell., vol. 5, pp. 137–144, Feb. 2023.
    Paper | Code
  2. M. Geisslinger, F. Poszler, J. Betz, C. Lütge, and M. Lienkamp, “Autonomous Driving Ethics: from Trolley Problem to Ethics of Risk,” Philos. Technol., Apr. 2021.
    Paper
  3. F. Nobis, M. Geisslinger, M. Weber, J. Betz, and M. Lienkamp, “A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detection,” in 2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2019, pp. 1–7.
    Paper | Code
  4. M. Geisslinger, R. Trauth, G. Kaljavesi, and M. Lienkamp, “Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning,” IEEE Open J. Intell. Transp. Syst., vol. 4, pp. 570–579, 2023.
    Paper | Code
  5. M. Geisslinger, P. Karle, J. Betz, and M. Lienkamp, “Watch-and-Learn-Net: Self-supervised Online Learning for Probabilistic Vehicle Trajectory Prediction,” in 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021, pp. 869–875.
    Paper | Code
  6. P. Karle, M. Geisslinger, J. Betz, and M. Lienkamp, “Scenario Understanding and Motion Prediction for Autonomous Vehicles - Review and Comparison,” IEEE Trans. Intell. Transp. Syst., vol. 23, no. 10, pp. 16962–16982, 2022.
    Paper
  7. P. Karle, F. Török, M. Geisslinger, and M. Lienkamp, “MixNet: Structured Deep Neural Motion Prediction for Autonomous Racing,” vol. 11, no. August, 2022.
    Paper | Code
  8. J. Betz et al., “TUM Autonomous Motorsport: An Autonomous Racing Software for the Indy Autonomous Challenge,” J. F. Robot., Jan. 2023
    Paper
  9. Wischnewski et al., “Indy Autonomous Challenge - Autonomous Race Cars at the Handling Limits,” in 12th International Munich Chassis Symposium 2021, Springer Berlin Heidelberg, 2022, pp. 1–16.
    Paper
  10. F. Poszler, M. Geisslinger, and C. Lütge, “A five-step ethical decision-making model for self-driving vehicles: Which (ethical) theories could guide the process and what values need further investigation?,” in International Conference on Computer Ethics, 2023, no. 1, pp. 1–3.
    Paper
  11. R. Trauth, M. Kaufeld, M. Geisslinger, and J. Betz, “Learning and Adapting Behavior of Autonomous Vehicles through Inverse Reinforcement Learning,” in 2023 IEEE Intelligent Vehicles Symposium (IV), 2023, pp. 1–8.
    Paper
  12. F. Poszler and M. Geißlinger, “AI and Autonomous Driving : Key ethical considerations,” no. February, 2021.
    Paper
  13. Heilmeier, M. Geisslinger, and J. Betz, “A Quasi-Steady-State Lap Time Simulation for Electrified Race Cars,” in 2019 14th International Conference on Ecological Vehicles and Renewable Energies, EVER 2019, 2019, pp. 1–10.
    Paper | Code
Open-Source Software
GitHub Repositories
CameraRadarFusionNet
Convolutional neural network fusion architecture for multi-level fusion of camera and radar data

Stars Forks Issues

EthicalTrajectoryPlanning
Ethical and risk-aware approach to AV trajectory planning based on EU recommendations

Stars Forks Issues

Wale-Net
Recurrent neural network for probabilistic vehicle trajectory prediction

Stars Forks Issues

laptime-simulation
Laptime simulation for motorsport such as Formula One or DTM

Stars Forks Issues

MixNet
Considering physics in pattern-based motion prediction for race vehicles

Stars Forks Issues

Media Appearances
Appearances List
  • Ethics of Autonomous Vehicles - SRF1 Einstein (TV) in SRF Media Library
    Date: 14.09.2023
  • Autonomous driving: New algorithm distributes risk fairly in TUM Press Release
    Date: 02.03.2023
  • "Neuer Algorithmus soll ethische Fragen adressieren" in Automotive IT
    Date: 21.12.2022
  • "Autonomes Fahren: Die TU München ist schneller als die Hersteller" in WELT
    Date: 21.12.2022
  • "Interview about autonomes vehicles" in Bayern 2 Radiowelt
    Date: 24.05.2022
  • "Automation of trucks" in F.A.Z.
    Date: 07.04.2022
  • "Autonomous Challenge @ CES" in Süddeutsche Zeitung
    Date: 07.04.2022
  • "Autonomous Driving Ethics" in Bild der Wissenschaft (Print)
    Date: 06/2021
  • "Autonomous Driving and Infrastructure" in Podcast Automobil
    Date: 07.05.2021
  • Autonomous Driving Ethics - beta stories (TV) in ARD Media Library
    Date: 21.05.2021
  • Challenges in Autonomous Driving - Tagesspiegel
    Date: 30.04.2021