Research

Research Interests:

Pattern recognition, recognition of graphical structures, computer vision, speaker understanding, large language models, multi-modal deep learning, natural language processing.

Current work:

My current focus revolves around developing a fast, interpretable visual parser for math and chemical formulas. Exploring innovative graph attention-based task interaction techniques, I aim to enhance contextual information while maintaining a natural and interpretable graph representation to recognize graphical notations, including complex math and chemical formulas, across various mediums like born-digital PDFs, typeset images, and handwritten strokes.

Past/ongoing research works: