My research blends Computer Vision with Arts and Cultural Heritage, developing novel AI solutions for preservation, interpretation, and reconfiguration of arts across diverse media. I focus on generative models, 3D reconstruction, multimodal large language models, depth estimation, visual saliency, and multitask learning aiming to push the boundaries of how AI integrates into society.

 I am passionate about exploring how AI interacts with human cognition and understanding the ethical and social impacts of AI technologies. My work seeks to create AI systems that align with human values, ensuring that they are responsible and inclusive.

I enjoy teaching courses in Visual Computing, Computer Vision, AI Ethics, and Machine Learning.

Teaching is not just about imparting knowledge, but inspiring creativity and critical thinking. I strive to create an inclusive classroom where diverse perspectives are encouraged, and students can collaborate on cutting-edge AI projects.

 As the Chair of the Department’s Self-Assessment Team (DSAT) and a member of the Equality, Diversity, & Inclusion Committee, I am committed to fostering a culture that values diversity in STEM. I have been recognised for my outreach efforts as a mentor for various non-profit initiative for teaching children and empowering women in technology. I am the organiser of Women in Computer Vision Workshop in CVPR 2025, Nashville, and in the past in CVPR 2024, Seattle. I have been a mentor for Women in STEM in ECCV 2024, Milan. I also led the organisation of  workshops ike AI for Visual Arts at ECCV 2024, co-chairing the publicity of CVPR 2025, hosted events for early-career researchers in flagship conferences like CVPR 2024, creating spaces for networking and collaboration internationally. Through these efforts, I aim to bring STEM to communities inclusive of all representations- gender, sexual orientation, nationality, and race.

 I am always excited to supervise doctoral students who are passionate about Computer Vision. I have supervised 5 doctoral students until now, 26 Master research students and 18 Bachelor students across the UK, US, Switzerland, aand China. If you are interested in computer vision  (preferrably for visual arts and/or cultural heritage and/or media and/or content creation), please reach out. I am happy to chat more about impact-driven research brought by interdisciplinary AI. Email: db2466 (at) bath (dot) ac (dot) uk