News

We are thrilled to announce that Dario Zanca has received the Emerging Talents Initiative (ETI) funding in 2023 for the preparation of a research project that aims to advance research in human-inspired deep learning systems and their implications in terms of behavioral plausibility, robustness, and ...

We were exceptionally happy to present our SMART Start project to the Federal Minister for Health Karl Lauterbach! This project is funded by the Bundesministerium für Gesundheit with 3.54 Million € and develops an integrative, digital care model for pregnant women. A project with FAU: Mach...

Abstract: Clustering is at the very core of machine learning, and its applications proliferate with the increasing availability of data. However, as datasets grow, comparing clusterings with an adjustment for chance becomes computationally difficult, preventing unbiased ground-truth comparisons and ...

We are happy to share the news that our user study on Active Learning of Ordinal Embeddings by Löffler et al. is now published in the Transactions on Machine Learning Research (TMLR), see OpenReview. This work improves upon our prior work on information retrieval in a football trajectory dataset (se...

Title: Optimization-in-the-loop ML for energy and climate When: Wednesday 26.04. 2pm-3pm via Zoom: https://fau.zoom.us/j/64359005780?pwd=MEdqVXVoN0QxNGVVTEhuSDBmclNmUT09 Speaker: Dr. Priya Donti (co-founder and Executive Director of Climate Change AI and MIT Assistant Professor from fall 2023)...

The MaD Lab’s Animal Behavior Research Group Team VERA published their latest dataset ??‍❄️ https://www.mdpi.com/2076-2615/13/5/801 Zuerl, M.; Dirauf, R.; Koeferl, F.; Steinlein, N.; Sueskind, J.; Zanca, D.; Brehm, I.; Fersen, L.v.; Eskofier, B. PolarBearVidID: A Video-Based Re-Identification ...

Exciting news! Our new paper has been published today in @PeerJ: https://peerj.com/articles/14852/. Our research explores the use of optimal control simulations in musculoskeletal models to reconstruct change of direction motions without prior knowledge of the motion path. Optimal control simulation...

The Tensor Tournament T3, held as part of the VHB courses "Machine Learning for Engineers I" and "Machine Learning for Engineers II", was a thrilling experience for all 27 teams of students who participated. The competition, which took place on January 21, 2023, challenged teams to solve thr...

We are happy to announce that our paper titled “Perspective on “in the wild” movement analysis using machine learning” is published: https://doi.org/10.1016/j.humov.2022.103042. Recent advances in wearable sensing and machine learning have created ample opportunities for “in the wild” movement analy...