Graduate Teaching Assistant

• CSE : 560 - Data Models & Query Language(Summer 2025) Professor Shamsad Parvin
• Guided students & helped them in completion of course Project of developing a Database.
• Solved Doubts of students using online QA platform: Piazza
• Designed Weekly Quiz, Assignments & evaluated them for 50+ Graduate/Undergraduate students.
• Assisted with grading exams and maintaining course grading systems.
• Coordinated with the professor to ensure smooth lectures, handled logistics,and schedule alignment.
• CSE : 396 - Theory Of Computation (Spring 2025) Professor Xiangyu Guo
• Evaluated programming assignments and theoretical problem sets for 80+ undergraduate students.
• Assisted with grading exams and maintaining course grading systems.
• Coordinated with the professor to ensure grading fairness and schedule alignment.

Software Engineer

• Full Stack Developer working on Bank Compliance Application for Western Union.
• Tech Stack : Java-Spring Boot, Angular JS, Kafk, CouchBase, AWS, RabbitMQ, Camunda BPMN for workflow Design.
• Developed Application using Microservices Architecture, REST APIs in Agile Workflow Environment
• Assisted in Code Deployments, detailed understanding of CI/CD pipeline, Docker, and AWS containers.
• Project Integration SPOC, Backend Lead, Camunda Desinger during later years.

Softare Engineering Intern

Designed and Developed a Grievance Redressal System for Industry workers for a quick and effective way to resolve any disputes. Implemented two modules Grievance ETA updates and Grievance Ticket Tracker

Worked on MERN stack during the intership period

Self-Supervised Learning for Image Representation Learning and Classification of Alzheimer Disease

Presented out work at CSE Demo Day 2025, UB

• We developed a self-supervised learning (SSL) framework to classify Alzheimer's disease from MRI scans and demonstrated its cross-domain adaptability to brain tumor classification. This work addresses the challenges of limited annotated data in medical imaging by leveraging large-scale unlabeled MRI datasets (~86,000 images).

Key Contributions

• Model Architectures: Implemented and evaluated three SSL approaches:
  • SimCLR: Contrastive learning with NT-Xent loss.
  • MoCo v3: Momentum contrast with Vision Transformers.
  • BYOL: Bootstrap learning without negative pairs using online-target networks.
• Downstream Classification: Fine-tuned SSL-pretrained encoders on a limited labeled dataset (450 images/class) for Alzheimer's classification using ResNet-50.
• Cross-Domain Transfer: Extended BYOL encoder to classify brain tumor types (e.g., glioma, pituitary, meningioma) using just 300 labeled samples/class.
• Explainable SSL representation : Using Grad-CAM, assissted the doctors to find the important regions in MRI scans and provideing other important statisitics.
Project Performance Details

Performance Highlights

• Accuracy on Alzheimer’s Test Set:
  • MoCo v3: Accuracy 87.0% Model Parameters : 87.8 M
  • BYOL Accuracy: 86.3% Model Parameters : 49.4 M
  • SimCLR Accuracy 82.6% Model Parameters : 26.6 M
  • ResNet-50 (supervised): 74.4%
• Brain Tumor Classification: 86.67% accuracy using BYOL features and minimal labeled data.
• Sample Grad-CAM Image Representations


Technical Pipeline

• Preprocessing: Data cleaning, augmentation (rotation, flipping, jitter), and class balancing.
• Training Strategy: 25–100 epochs of SSL pretraining on unlabeled data, followed by supervised fine-tuning with linear classifiers.
• Model Comparison: Visualizations of parameter counts, class activation maps, and diagnostic regions to interpret model decisions.

Impact

This project showcases the power of self-supervised learning in healthcare AI, demonstrating robust performance in low-label settings and transferable representations across medical domains. Future directions include integrating multi-modal MRI and clinical data and exploring real-time clinical deployment.

Project Poster

• Alzheimer Disease Classifier Website

Inteligent Traffic Management System

Extra-Curricular Activities Database

Web Developer Volunteer