Research Interests: Pattern recognition, computer vision, and speech and natural language processing. detection and recognition of graphical structures, multi-modal deep learning, speech and natural language processing, visual scene parsing.

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 research works: