About
Nov. 2023-Present: Researcher in Machine Learning and Computer Vision at the Applied Machine Learning Lab, Jülich Supercomputing Centre. I study robustness to perturbations in generative diffusion models, with early access to JUPITER, Europe’s first exascale supercomputer.
Dec. 2017-Aug. 2019, Feb. 2021-Aug. 2022, Aug. 2022-Nov. 2023: Independent PhD candidate in computer science, Computer Vision Lab, University of Bonn.
Additional responsibilities included teaching and supervising Master’s students, e.g. Adversarial Synthesis of Human Pose from Text, which won the best Master’s thesis award in DAGM Young Researchers’ Forum 2020.
Due to a personal loss, I experienced delays in my research in 2023-2024.
New
Exploring and Exploiting Stability in Latent Flow Matching
Rania Briq, Michael Kamp, Ohad Fried, Sarel Cohen, Stefan Kesselheim
Accepted at the International Conference on Machine Learning (ICML), 2026.
publications
Research interests
During my PhD, I conducted research on
- Stability in flow matching and diffusion models
- Generating human motion conditioned on multiple actions while interning at Amazon, followed up by scene-constrained generation.
- Generating human poses conditioned on text
- Optical and scene flow for human body tracking during my internship at Facebook Reality Labs.
- Human pose estimation and ordinal prediction for sets
- Weakly supervised semantic segmentation using object size constraints.
MSc in computer science, University of Bonn.
BSc in computer and software engineering, Technion.
Research internships
Applied scientist intern at Amazon Go, August 2021-August 2022. My work focused on synthesizing conditional human motion data.
Research intern at Facebook Reality Labs, August 2019-Jan. 2020. I worked on differentiable rendering and optical flow for human body tracking.