3rd Place at ACM SIGSPATIAL GisCup 2019

Optimizing the Spatio-Temporal Resource Search Problem With Reinforcement Learning

Felix Borutta, Sebastian Schmoll and Sabrina Friedl won the 3rd Place at ACM SIGSPATIAL GisCup 2019 for their contribution "Optimizing the Spatio-Temporal Resource Search Problem with Reinforcement Learning".

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13.11.2025

Explaining AI Decisions: Shapley Values Enable Smart Exosuits

AI meets wearable robotics: MCML and Harvard researchers make exosuits smarter and safer with explainable optimization, presented at ECML-PKDD 2025.

10.11.2025

MCML at ICDM 2025

MCML researchers are represented with 2 papers at ICDM 2025.

Link to Research on human-centred Exosuit technology highlighted in Börsen-Zeitung

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03.11.2025

Research on Human-Centred Exosuit Technology Highlighted in Börsen-Zeitung

Julian Rodemann worked with Harvard on interpretable algorithms for “Back Exosuits,” improving human–machine interaction.

02.11.2025

MCML at EMNLP 2025

MCML researchers are represented with 39 papers at EMNLP 2025 (18 Main, 13 Findings, and 8 Workshops).

30.10.2025

Language Shapes Gender Bias in AI Images

Alexander Fraser shows AI image generators reproduce gender stereotypes differently across languages, highlighting the need for fair multilingual AI.

3rd Place at ACM SIGSPATIAL GisCup 2019

Optimizing the Spatio-Temporal Resource Search Problem With Reinforcement Learning

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