Current:
- 🔬Machine Learning Researcher at Apple, working on multimodal learning 🇪🇸.
💼 Previous Experience:
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🔬Research Intern at Google DeepMind working on video segmentation🇨🇭. Supervised by Stefano Pellegrini, Jasper Uijlings, and Cordelia Schmid
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🔬 Research Intern & Student Researcher at Google Research working on efficient adaptation of lare-scale models🇫🇷. Supervised by Anurag Arnab, Alexey Gritsenko, and Cordelia Schmid
- 🤝 Collaborated with Aleksandra Nowak, Utku Evci, and Yann Dauphin from Google DeepMind on a related project.
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🔬 Machine Learning Researcher at Everseen working on tracking and re-identification🇷🇴.
🎓 Education:
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🎓 IMPRS-IS Computer Science PhD Student in the Explainable Machine Learning Group in Munich, with a guest affiliation at Helmholtz Munich & the Technical University of Munich🇩🇪. Supervised by Prof. Zeynep Akata (TUM & Helmholtz Munich) & Prof. Andreas Geiger (University of Tübingen).
- Examination committee: Prof. Zeynep Akata (TUM & Helmholtz Munich), Prof. Andreas Geiger (University of Tübingen), Prof. Justus Thies (TU Darmstadt), Prof. Hildegard Kühne (University of Tübingen & MIT-IBM Watson AI Lab).
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🤖 MSc in Artificial Intelligence from the University of Edinburgh🇬🇧. MSc thesis supervised by Prof. Amos Storkey.
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💻 BEng in Computers and Information Technology from Politehnica University of Timisoara🇷🇴. BEng thesis supervised by Prof. Calin-Adrian Popa
⚡ Research Focus: Focused on enhancing deep learning efficiency through data-efficient (low-shot) and model-efficient (adaptation) methods for large-scale models. Experienced in multimodal learning (audio-visual), multi-modal large language models, video semantic segmentation, and tracking.
You can find me on Twitter or LinkedIn - for my research and latest updates, check out my Google Scholar and Homepage!