publications
As to why I got drawn to machine learning or computer vision, I do believe it is one of the richest modalities but also read this excerpt when I was quite young, from the book, “Visual Reconstruction” by Andrew Blake and Andrew Zisserman, some of my favourite researchers:
We count it a great privilege to be working in a field as exciting as Vision. On the one hand there is all the satisfaction of making things that work - of specifying, in mathematical terms, processes that handle visual information and then using computers to bring that mathematics to life. On the other hand there is a sense of awe (when time permits) at the sheer intricacy of creation. Of course it is the Biological scientists who are right in there; but computational studies, in seeking to define Visual processes in mathematical language, have made it clear just how intrinsically complex must be the chain of events that constitutes “seeing something”.
2024
- NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the WildPMLR 2024
- SEE-2-SOUND : Zero-Shot Spatial Environment-to-Spatial SoundICMLW 2024
2023
- Orchestrating Machine Learning on Edge Devices with PyTorch and WebAssembly (Oral)PyTorch Conference 2023 (Oral)
- CPPE-5: Medical Personal Protective Equipment DatasetSN Computer Science 2023