Machine Learning Group at Technische Universität Berlin: Postdoctoral Researcher
Berlin Institute for the Foundations of Learning and Data: Senior Researcher
Google Scholar: https://scholar.google.com/citations?user=eSjfzOUAAAAJ
Research Gate: https://www.researchgate.net/profile/Robert_Vandermeulen
DBLP PID: 137/3375
I am a machine learning researcher currently based in Berlin. My primary research focuses are deep anomaly detection and nonparametric density estimation. My research on deep anomaly detection primarily focuses on one-class approaches, which were initially developed by myself (and collaborators) while I was at TU: Kaiserslautern and Humboldt-Universität zu Berlin. For nonparametric density estimation I am interested particularly in factorized density estimates which can used as an approach to nonparametric mixture models or as a general means for improving density estimates.
I was born and raised in the Pacific Northwest in the USA and did my graduate work at University of Michigan before moving to Berlin for my postgraduate studies.
- 2-2022: First website update since 5-2021
- 9-2021: Paper accepted to NeurIPS
- 9-2021: Invited talk at Kyung Hee University
- 7-2021: Invited talk at Hawai‘i Data Science Institute
- 7-2021: Presenting paper at ICML: Workshop on Uncertainty and Robustness in Deep Learning
- 5-2021: Paper accepted to ICML
- 4-2021: I will be PCing 3 anomaly detection workshops this year: [KDD: ANDEA] [KDD:ODD] [IJCAI: AI4AN]
- 4-2021: Paper accepted to IJCAI
- 1-2021: Papers accepted to ICLR and Proceedings of the IEEE
- 12-2020: New website!
- 11-2020: Submission accepted to NeurIPS Pre-registration conference: A Proposal for Supervised Density Estimation