Martin Becker

Assistant Professor (Jun.-Professor), PI

Contact

Room: 271

About Me

I am passionate about highly collaborative projects and research that impact high-stake real-world problem settings at the intersection of medicine, environmental change, and human behavior through artificial intelligence and machine learning.

In this context I am interested in methods from multi-modal learning, network analysis, and exceptional model mining to Bayesian modeling, deep learning, representation learning, explainable AI, and human computer interaction.

Also, I love to dance 💃, read 📚, and whenever I get the chance I go surfing 🏄.

Short CV

For my publications and projects, please refer to Google Scholar and my lab page.

2022 - now: Assistant Professor; University of Rostock (Germany); Chair for Intelligent Data Analytics
2022 - 2025: Research Group Leader (BMBF AI Program); University of Rostock (Germany);
Research topic: Leveraging background knowledge for understanding and modeling complex systems
2018 - 2022: Postdoctoral researcher; Aghaeepour Lab, Stanford University (CA, USA);
Research topic: Artificial Intelligence, Machine Learning, and Multiomics Integration for Systems (Bio-)Medicine and Clinical Applications
2018: Postdoctoral researcher; DMIR, University of Würzburg (Germany)
2011 - 2018 Research assistant and PhD student; DMIR, University of Würzburg (Germany) and L3S Research Center (Germany);
Thesis: Understanding Human Navigation using Bayesian Hypothesis Comparison
2006 - 2011: Diploma: Computer science major, mathematics minor; University of Würzburg (Germany) and University of Texas at Austin (TX, USA);
Thesis: Constraint Based Descriptive Pattern Mining

Community Service

  • PC member of / reviewer for computer science journals, conferences and workshops: npj Digital Medicine (Journal); Machine Learning (Journal); Frontiers in Artificial Intelligence (Journal); Frontiers in Big Data (Journal); EPJ Data Science (Journal); KDD, AAAI; IJCAI; ICDM; WWW; ECML/PKDD; ECAI; ICWSM; ISWC; ESWC; ECIR; DSAA; SocInfo; INFORMATIK; IoP; MUSE; KDML; and more.

  • Summer school organization: ECML/PKDD Summer School 2019 on Machine Learning and Data Mining for Geo-Spatial Data/Volunteered Geographic Information, Quality of Experience, and HCI

Teaching

  • Explainable Artificial Intelligence
  • Data Science
  • Information Retrieval