- π Iβm a fifth-year Ph.D. candidate at Rochester Institute of Technology (RIT), conducting research at the Document and Pattern Recognition Lab (DPRL), under the mentorship of Dr. Richard Zanibbi.
- π‘ My work centers around designing fast, efficient, and interpretable parsers for recognizing complex mathematical and chemical formulas. I explore graphical notations across multiple formats, including PDFs, typeset images, and handwritten strokes. Through graph attention-based techniques, I aim to enhance how contextual information is processed, while preserving a natural and interpretable graph representation.
- π― My goal is to deliver high accuracy in formula recognition through models that are not only faster but also easier to interpret than traditional encoder-decoder architectures.
- π» Recently, I developed ChemScraper, a molecule diagram parser that extracts characters and graphics directly from PDF molecule images. By utilizing typesetting instructions and simple graph transformations, it generates both visual and chemical graphs β without the need for OCR, GPUs, or vectorization. ChemScraper offers a practical approach to creating fine-grained, annotated datasets for training visual parsers, and also a visual parser for parsing molecule images (raster) directly.
- π Research interests: Pattern recognition, recognition of graphical structures, computer vision, speaker understanding, large language models, multi-modal deep learning, natural language processing .
- βοΈ I write blog posts that reflect my new learnings mostly related to python and AI.
- π± Iβm currently learning fundamental concepts and advancements in recognition (parsing) of graphical information from documents.
- π You can view my CV here: My CV
- Personal website: shahayush.com
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