Context-based A/B Test Validation. - Michael Nolting; Jan Eike von Seggern (WWW (Companion Volume), 2016)

Multi-objective optimization of charging infrastructure to improve suitability of commercial drivers for electric vehicles using real travel data. - Timo Krallmann; Martin Döring; Marek Stess; Timo Graen; Michael Nolting (EAIS, 2018)

OJO: Fuzzy Logic based Digital Health Coaching for Scalable Diabetes Prevention. - Michael Nolting; Ulf Wittke (PervasiveHealth, 2019)

Do You Just Discuss or Do You Solve?: Meeting Analysis in a Software Project at Early Stages. - Jil Klünder; Nils Prenner; Ann-Kathrin Windmann; Marek Stess; Michael Nolting; Fabian Kortum; Lisa Handke; Kurt Schneider; Simone Kauffeld (ICSE (Workshops), 2020)

On the Importance of Contextual Information for Building Reliable Automated Driver Identification Systems. - Li Zeng; Mohammad Al-Rifai; Sergiu Chelaru; Michael Nolting; Wolfgang Nejdl (ITSC, 2020)

Towards Autonomous Digital Health Coaching for Scalable Chronic Disease Prevention. - Michael Nolting; Julian Roth; Ulf Wittke (PervasiveHealth, 2020)

Optimization of future charging infrastructure for commercial electric vehicles using a multi-objective genetic algorithm and real travel data. - Li Zeng; Timo Krallmann; Andrea Fiege; Marek Stess; Timo Graen; Michael Nolting (Evol. Syst., 2020)

When Fast Means More Hassle: Online Deliveries Revisited. - Daniel Erik Brylla; Gianfranco Walsh; Michael Nolting; Julian Roth (ICIS, 2021)

How to Integrate with Real Cars - Minimizing Lead Time at Volkswagen. - Jan Kantert; Michael Nolting (ICSE (SEIP), 2021)

Challenges in the Development of Mobile Online Services in the Automotive Industry - A Case Study. - Nils Prenner; Jil Klünder; Michael Nolting; Oliver Sniehotta; Kurt Schneider (ICGSE/ICSSP, 2021)

Environmental Data Collection as a Byproduct for Autonomous Ride-Hailing Services. - Leonie Frantzen; Patrick Liedtke; Timo Graen; Andrea Fiege; Michael Nolting; Wolfgang Nejdl (ITSC, 2021)

Triplet Loss for Effective Deployment of Deep Learning Based Driver Identification Models. - Li Zeng; Mohammad Al-Rifai; Michael Nolting; Wolfgang Nejdl (ITSC, 2021)

Demand-Driven Data Acquisition for Large Scale Fleets. - Philip Matesanz; Timo Graen; Andrea Fiege; Michael Nolting; Wolfgang Nejdl (Sensors, 2021)

Towards building reliable deep learning based driver identification systems. - Li Zeng; Mohammad Al-Rifai; Michael Nolting; Wolfgang Nejdl (ICTAI, 2022)

Ego-Vehicle Speed Prediction with Walk-Ahead. - Philip Matesanz; Nicolas Tempelmeier; Michael Nolting; Thorben Funke (ITSC, 2022)

Multi-Modal Motion Prediction with Graphormers. - Shimon Wonsak; Mohammad Al-Rifai; Michael Nolting; Wolfgang Nejdl (ITSC, 2022)

Using Vehicle Data to Enhance Prediction of Accident-Prone Areas. - Kelvin Sopnan Wowo; Rajjat Dadwal; Timo Graen; Andrea Fiege; Michael Nolting; Wolfgang Nejdl; Elena Demidova; Thorben Funke (ITSC, 2022)

Towards Sub-Maneuver Selection for Automated Driver Identification. - Kelvin Sopnan Wowo; Michael Nolting; Nicolas Tempelmeier (ITSC, 2022)

Visense for Vehicle Load Estimation and Fatigue Analysis. - Nils Henke; Mohammad Al-Rifai; Mirko Wagner; Michael Nolting; Nicolas Tempelmeier (ITSC, 2023)

CondTraj-GAN: Conditional Sequential GAN for Generating Synthetic Vehicle Trajectories. - Nils Henke; Shimon Wonsak; Prasenjit Mitra; Michael Nolting; Nicolas Tempelmeier (PAKDD (2), 2023)

Towards Data-Driven Planning of Mobile Charging Infrastructure for Electric Vehicles. - Leonie von Wahl; Clara Mautsch; Stefan Ladwig; Michael Nolting; Nicolas Tempelmeier (SuMob@SIGSPATIAL, 2023)

Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets. - Leonie von Wahl; Niklas Heidenreich; Prasenjit Mitra; Michael Nolting; Nicolas Tempelmeier (AAAI, 2024)

Is AI the Future of Weight Loss Coaching? Exploring Digital Methods for Automated Health Guidance. - Michael Nolting; Gianfranco Walsh; Daniel Erik Brylla (ECIS, 2024)

Adaptive Dispatching of Mobile Charging Stations using Multi-Agent Graph Convolutional Cooperative-Competitive Reinforcement Learning. - Shimon Wonsak; Nils Henke; Mohammad Al-Rifai; Michael Nolting; Wolfgang Nejdl (SIGSPATIAL/GIS, 2024)