My research focuses on explainability and reasoning in Deep Learning, building human-understandable AI through concept-oriented representations and structured reasoning.
Feb 2023 Our work on semantic image compression with quantized autoencoders (Meta AI internship) is accepted at ICASSP 2023.
Sept 2022 Our work on quantitative metrics for evaluating DeepFake explanations (Huawei Research internship) is accepted at BMVC 2022.
Aug 2022 My master student Erik Dao graduated with a thesis on sparsity in transformers for object detection (DETR).
Mar 2022 Our work on object-centric learning is accepted at the ICLR 2022 Workshop on the Elements of Reasoning: Objects, Structure, and Causality.
Feb 2022 Accepted a research internship at FAIR (Meta AI) in Paris under the supervision of Hervé Jégou.
Jan 2022 Gave a presentation on evaluating DeepFake explanations at Digital Future’s Machine Learning Day.
Sept 2020 Started a summer internship at Huawei Research in Dublin!
Jan 2021 My master student Jindong Wu graduated with a thesis on pooling strategies for Graph Networks.
Aug 2020 Received an award for being an outstanding reviewer at ECCV 2020.
Jun 2020 Hosted a full-day workshop for my department on how use our in-house GPU cluster.
May 2019 Our work on GNN Explainability is accepted at the ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data.
Jan 2019 Presented my Master’s thesis on fashion image generation at the Northern Lights Deep Learning Workshop.
May 2018 Accepted a PhD position at KTH under the supervision of Hossein Azizpour.