COMPOSE: Hypergraph Cover Optimization for Multi-view 3D Human Pose Estimation
Neural Information Processing Systems (NeurIPS), 2026
I am a Research Fellow at Imperial College London, supported through the UK Royal Society Newton International Fellowship, where I pursue topics at the intersection of geometry, topology, and machine learning with exciting applications in the natural and physical sciences.
I completed my PhD with highest distinction (summa cum laude) at the Chair for Computer Aided Medical Procedures (CAMP) in Munich, supervised by Prof. Nassir Navab, where I also coordinated research of the Surgical Data Science team. Prior to this, I conducted my M.Sc. in Applied Mathematics at the Technical University of Munich with an emphasis on optimization and statistics, and Bachelor's in Mathematics and Computer Science from New York University's Courant Institute.
I also enjoyed stints in software and data science at H2oMetrics, a cloud water management startup, and as a research assistant at the MSKCC Levine Lab, developing computational tools for the genetic analysis of myeloid leukemias.
I study the geometry and topology hidden in data, building machine learning methods that exploit it. The resulting algorithms are relevant to numerous fields: i'm particular fond of applications in the natural sciences, including medicine, biology and physical systems.
Neural Information Processing Systems (NeurIPS), 2026
International Conference on Machine Learning (ICML), 2026
International Conference on Machine Learning (ICML), 2026
Medical Image Computing and Computer Assisted Intervention (MICCAI) - Early Accept (Top 9%), 2026
Computer Graphics Forum (Eurographics STAR) 2026, 2026
Advances in Neural Information Processing Systems (NeurIPS), 2025
IEEE International Conference on Computer Vision (ICCV) - Oral (Top 2.6%) , 2025
Medical Image Analysis (MedIA) (Journal IF 10.7, rank among CV venues), 2025