Otniel-Bogdan Mercea

Currently, I am a Machine Learning Researcher at Apple, working on multimodal learning.

I did my PhD in CS with a specialization in AI at the Max Planck Institute for Intelligent Systems and the University of Tubingen, supervised by Prof. Zeynep Akata and Prof. Andreas Geiger within the IMPRS-IS doctoral program. I was also a guest PhD student at Helmholtz Munich and Technical University of Munich, supervised by Prof. Zeynep Akata. I earned my MSc in AI from the University of Edinburgh in 2020, with a thesis supervised by Prof. Amos Storkey, and my BEng in Computers and Information technology from Politehnica University of Timisoara in 2019, with a thesis supervised by Prof. Calin-Adrian Popa.

I applied my research expertise in industry through impactful roles, including internships at Google DeepMind (Autumn 2024), supervised by Stefano Pellegrini, Jasper Uijlings, and Cordelia Schmid, on improving SAM 2 for significant occlusion and movement scenarios; and Google Research (2023–2024), collaborating with Anurag Arnab, Alexey Gritsenko, and Cordelia Schmid on efficient adaptation of large-scale models. I also collaborated with Aleksandra Nowak, Utku Evci, and Yann Dauphin from Google DeepMind on related projects. Previously, I was a ML Researcher at Everseen, developing real-time multi-camera tracking systems.

My research focuses on improving the efficiency of deep learning through data-efficient (low-shot) and model-efficient adaptation methods for large-scale models. I also have extensive experience in multimodal learning (audio-visual, multimodal language models) and video semantic segmentation and tracking.