Shubhashis Roy Dipta
PhD Researcher ⎟ Decomposition-based Reasoning ⎟ Multimodal, NLP

Shubhashis Roy Dipta
sroydip1@umbc.edu
Affiliations
Amazon Science
Applied Research Scientist Intern
Summer 2025
Manager: Dr. Lichao Wang
Mentor: Dr. Daniel Bis
University of Maryland, Baltimore County
Ph.D. in CS
Spring 2021 - Present
Advisor: Dr. Frank Ferraro
Grade: 4.00/4.00
Publications: See Here (From 2023)
University of Maryland, Baltimore County
M.Sc. in CS
Spring 2021 - Spring 2023
Awards: Phi Kappa Phi
Grade: 4.00/4.00
Morgan State University
Volunteer Researcher (Remote)
2017 - 2019
Advisor: Dr. Iman Dehzangi
Publications: 4 Journals (Genes, Elsevier, IEEE Access, Springer)
Military Institute of Science & Technology
B.Sc. in CS
Spring 2013 - Fall 2017
Advisor: Dr. Wali Mohammad Abdullah
Grade: 3.51/4.00
Professional Services
Reviewer of ELVM workshop at CVPR 2025
Reviewer of ACL 2025 (6 papers)
Reviewer of W-NUT workshop at NAACL 2025
Reviewer of TrustNLP Workshop at NAACL 2025 (2 Papers)
Reviewer of NAACL Industry Track 2025 (1 Paper)
Reviewer of COLING 2025 (2 Papers)
Reviewer of BMC Bioinformatics (July 2024)
Reviewer of Scientific Reports (July 2024)
Reviewer of SRW at NAACL 2024 (2 Papers)
Reviewer of SemEval-2024 (4 papers)
Reviewer of Scientific Reports, Nature (Jan 2024)
Reviewer of Plant Methods (Jan 2024)
Reviewer of W-NUT workshop at EACL 2024
Reviewer of Plant Methods (Dec 2023)
Reviewer of Computational and Structural Biotechnology Journal (Mar 2023)
Secondary Reviewer of *SEM 2023
Shubhashis is a Computer Science PhD Researcher under Dr. Frank Ferarro at the University of Maryland, Baltimore County (UMBC). His research combines Natural Language Processing (NLP) and Computer Vision (CV).
His broad research focuses on Decomposition-based Reasoning using text or vision data. Currently, he is focused on question based decomposition to understand the scientific feasibility of a given task.
Over the years, he has worked on Outcome and Intention based Decomposition and how it can be used for video-text retrieval. This research has applications in video/image retrieval system, especially where there is no text metadata available for the video (e.g., most of the videos on the internet, social media, and surveillance videos). Also, his previous work, a hierarchical variational autoencoder for Event Representation Learning, has applications in text summarization, question answering, and counterfactual reasoning (Published in *SEM 2023, ACL).
In Summer 2025, he is interning at Amazon Science as a Applied Scientist. He is researching on optimization of Alexa conversation latency, cost and performance. He was mentored by Dr. Daniel Bis and managed by Dr. Lichao Wang.
In Summer 2024, he interned at Scale.AI as a Machine Learning Researcher. He explored how RLHF can improve the text2SQL generation (currently under ARR review). He also worked on Many-Shot text2SQL and text2SQL AutoEval using SLM. He was mentored by Vijay Kalmath and managed by Dr. Adrian Lam.
Actively looking for Research Collaboration in Natural Language Processing or Multimodal (Language + Vision) Work. Please contact me if you want to collaborate.
Shubhashis has a strong background in ML programming, including PyTorch, 🤗 HuggingFace, NLTK, Spacy, Matplotlib, Seaborn, and more. He has excelled in machine learning competitions (Kaggle top-70 🥉) and coding competitions (ACM ICPC 8th out of 300+ teams) and more. He was the founder of UniShopr (2018-2022), a cross-border e-commerce for his home country (Bangladesh).
Research Interest
✓ Decomposition-based Reasoning using Multimodal Data
✓ (Outcome & Intention Based) Video-Text Retrieval
✓ Natural Language Understanding
Recent News (See All)
May 19, 2025 | Started my summer internship at Amazon in Alexa AI team. I am working on optimizing the Alexa conversation latency, cost and performance. |
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May 16, 2025 | Served as a judge for the National Round of the Bangladesh AI Olympiad 2025. You can solve the problem here. |
Jan 23, 2025 | My summer internship project at Scale.AI has been featured on the Scale.AI blog. |
Dec 20, 2024 | Accepted a position as a Applied Research Scientist Intern at Amazon Science. Excited to join the team and work on cutting-edge research in NLP and ML. |
Nov 16, 2024 | Attended EMNLP-2024 in Florida, Miami. Excited to meet researchers from all over the world. |
Featured Publications
Check out Google Scholar for a full list of my publications.