Shreya Biswas

PhD Student in Computer Science

Specializing in Few-Shot Computer Vision, Vision-Language models, Domain Adaptation, and Medical Imaging

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About Me

I specialize in few-shot learning, vision–language models, and domain adaptation for computer vision. My research focuses on designing algorithms that can learn effectively from limited data.

I aim to push the boundaries of data-efficient AI by collaborating with interdisciplinary teams of clinicians and scientists, and contributing solutions that impact healthcare, climate resilience, and real-world decision making.

10+

Publications

6+

Years Research Experience

3+

Leadership Roles

Education

PhD in Computer Science

SUNY Stony Brook | 2023 - 2028 (Expected)

B.E. in Electronics and Telecommunication

Jadavpur University | 2019 - 2023 | GPA: 9.29/10

Research Areas

Computer Vision

Developing advanced algorithms for low-shot image analysis, object detection, and pattern recognition.

Deep Learning

Designing neural network architectures for few-shot complex classification and segmentation tasks.

Medical Imaging

Applying machine learning techniques for medical diagnosis, including brain tumor segmentation and COVID-19 prediction from medical scans.

Publications

Parkinson's Disease Detection Diagram

DOTGraph: CLIP-Driven Feature Disentanglement and Optimal Transport based Graph Learning for Few-Shot Segmentation

Under Review, WACV 2026

Parkinson's Disease Detection Diagram

TaSP: Target Style Guided Pruning for Cross Domain Few Shot Segmentation

Under Review, IEEE TIP

Parkinson's Disease Detection Diagram

Granulated Mask-RCNN and Eye Detection Index (EDI) for detection and localization of the eye of tropical cyclones from satellite imagery

Journal of Data, Information and Management 2024

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SCENIC Hardware Accelerator Diagram

SCENIC: An Area and Energy-Efficient CNN-based Hardware Accelerator for Discernable Classification of Brain Pathologies using MRI

VLSID 2022

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Parkinson's Disease Detection Diagram

Moth-flame Optimization based Deep Feature Selection for Cardiovascular disease Detection using ECG Signal

Handbook of Moth-Flame Optimization Algorithm, 2022

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Parkinson's Disease Detection Diagram

An Ensemble of CNN Models for Parkinson's Disease Detection Using DaTscan Images

Diagnostics, 2022

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Breast Cancer Detection Diagram

Breast cancer detection from thermal images using a Grunwald-Letnikov-aided Dragonfly algorithm-based deep feature selection method

Computers in Biology and Medicine, 2021

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COVID-19 CT Detection Diagram

Prediction of COVID-19 from Chest CT Images Using an Ensemble of Deep Learning Models

Applied Sciences, 2021

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Multi-Level Image Segmentation Diagram

Multi-Level Image Segmentation Using Kapur Entropy Based Dragonfly Algorithm

ISDA 2022

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Featured Projects

Coastal Flooding Visualizer

Research Project | 2025 - Present

  • Engineered and deployed a geospatial web app (Flask + Leaflet + GEE) to simulate global coastal flooding at 30m resolution.
  • Integrated >10 GB of sea level rise and hurricane datasets for real-time hazard mapping and interactive analytics.
  • Processed 90+ years of hurricane records with <3s query response time for projections and storm overlays.
  • Enabled chatbot-assisted decision support for local-scale climate risk assessment.

WHISPER for Parkinson's

CSE 538 NLP Project | 2024

  • Fine-tuned Whisper on Parkinson's speech data, improving dysarthric speech recognition by 49.1% over baseline.
  • Reduced Word Error Rate by 15%, advancing assistive speech technologies.

Prediction of Video Sequences

Undergraduate Thesis Project | 2023

  • Designed a predictive video-sequence framework using Taylor series, reducing error by 12% vs. baselines.
  • Introduced RL-based Adaptive Probabilistic Learning Matrix, improving stability by 20%.

Research Experience

2023-Present

Graduate Researcher

Stony Brook University (SUNY) Advisor: Dr. Zhaozheng Yin

  • Proposed an Optimal Transport-based graph-alignment pipeline with CLIP-driven foreground–background disentanglement and a novel Graph Contrastive Loss to improve mIoU by 1.5% to set a new benchmark for few-shot segmentation.
  • Developed TaSP, a cross-domain few-shot classification model involving a structure-preserving style transfer framework with a novel pruning mechanism to adapt visual features from unlabeled target data, retaining transferable features and improving accuracy by ≥2% over SOTA.
Fall 2023

Undergraduate Research Intern

Indian Statistical Institute (ISI) Advisor: Dr. Sankar K. Pal

  • Engineered a cyclone detection model by integrating granulation with Mask-RCNN which boosted detection accuracy by 34%.
  • Introduced a novel Eye Detection Index to reduce false alarm rate by 11%, and improve compactness by 56%.
Spring 2022

Summer Research Intern

Machine Intelligence Research Labs (MIR Labs) Advisor: Dr. Ajith Abraham

  • Developed a nature-inspired multi-threshold image part-segmentation technique combining Dragonfly Algorithm and Kapur’s Entropy.
Fall 2021

Computer Vision Research Intern

SUNY Polytechnic University Advisor: Dr. Janet Paluh

  • Devised SCENIC, a depth-wise separable convolution based deep-learning system for glioma tumor classification from MRI modalities to achieve 98.3% tumor detection and 99.6% modality classification accuracy, while reducing energy consumption by 24%.
  • Collaborated with SUNY Polytechnic Hospital to showcase the potential for energy-efficient models for medical diagnostics.
Fall 2020

Winter Research Intern

Indian Institute of Technology (IIT) Kharagpur Advisor: Dr. Sudipta Mukhopadhyay

  • Implemented deep hashing methods for large-scale image retrieval.

Professional & Leadership Experience

Graduate Teaching Assistant

Department of computer Science 2021 – 2022

  • CSE 532: Theory of Database Systems - under Dr. Fusheng Wang
  • CSE 519: Introduction to Data Science - under Dr. Steven Skienna

Chairperson

IEEE Jadavpur University Computer Society Chapter 2022 – Jan 2023

  • Led AICSSYC’22 with 300+ participants, coordinating speakers, program, and logistics.
  • Organized “Machine Learning Accelerator Summit 2.0”, focusing on hands-on ML workflows.

Secretary

IEEE Jadavpur University Computer Society Chapter 2021 – 2022

  • Produced the “Pass the Mic ’21” podcast series highlighting student research journeys.
  • Co-organized “DoubleSlash” 48-hour hackathon; managed judging rubric and outreach.

Technical Skills

Programming Languages

Python Java C/C++ Matlab HTML/CSS JavaScript NodeJS React Flask

Libraries & Frameworks

PyTorch TensorFlow Keras OpenCV Pandas Numpy Matplolib

Tools & Platforms

VS Code Google Earth Engine Git Google Cloud Platform