Tim Puphal

Research Scientist

A portrait of Tim Puphal

Employment

HRI Japan
Senior Research Scientist. Working on learning-based motion planning. Doing an expatriate training in Japan.
Apr 2024 - (current)
Tokyo, Japan
HRI Europe
Senior Research Scientist. Worked on cooperative planning and human-robot interaction. Deputy group leader.
Jun 2021 - Mar 2024
Offenbach, Germany
HRI Europe
Research Scientist. Worked on robust planning and safety.
Sept 2016 - May 2021
Offenbach, Germany
Continental AG
Management intern. Worked on project management software.
Mar 2015 - Jun 2015
Shanghai, China
Samson Controls, Ltd.
Engineer intern. Supported automated manufacturing engineering team.
Aug 2012 - Sept 2012
Frankfurt, Germany

Education

TU Darmstadt
Ph.D. in Electrical Engineering, advised by Julian Eggert and Jürgen Adamy.
Supported by the European Unions Horizon 2020 programme.
Fall 2016 - Spring 2021
TU Darmstadt
M.Sc. in Electrical Engineering, Major Robotics Control Theory.
Fall 2013 - Spring 2016
TU Darmstadt
B.Sc. in Electrical Engineering, Minor in Computer Science and Mechanical Engineering.
Fall 2010 - Spring 2013
CEGEP - John Abbott College
Mathematics and Economics Major, Certificate of Academic Excellence.
Spring 2008

Publications

Probabilistic Collision Risk Estimation for Pedestrian Navigation Assistive device for the vision impaired using uncertainty-aware motion prediction for surrounding objects.
IEEE/RSJ IROS, 2025
Finding the Easy Way Through – the Probabilistic Gap Planner for Social Robot Navigation Probabilistic gap planner which improves robot navigation by guiding short-term planners towards low-density crowd regions.
IEEE ROMAN, 2025
Negotiating Cooperative Ordering Problems with Bimodal Planning Cooperative ordering resolved by switching-aware negotiation to handle dynamic intent in urban mobility scenarios.
IEEE IV, 2025
Risk-Based Filtering of Valuable Driving Situations in the Waymo Open Motion Dataset Filtering method identifies valuable complex interactions from large driving datasets to improve automated vehicle testing.
IEEE IAVVC, 2025
Reducing Warning Errors in Driver Support with Personalized Risk Maps Personalized assistance system adapts signals based on driver behavior style to reduce false positives and false negatives. Best Paper Award
IEEE ICVES, 2024
Considering Human Factors in Risk Maps for Robust and Foresighted Driver Warning Human-robot interaction using human state detection and behavior models to anticipate errors and provide adaptive support.
IEEE ROMAN, 2023
Automated Driving in Complex Real-World Scenarios using a Scalable Risk-Based Behavior Generation Framework An analytic behavior planner enables autonomous vehicles to generate high-quality decisions without relying on predefined behavior primitives.
IEEE ITSC, 2021
Asymmetry-based Behavior Planning for Cooperation at Shared Traffic Spaces Cooperative behavior planning using asymmetry-based outcome prediction to navigate narrow passages without communication.
IEEE IV, 2021