I am a B.Sc. Computer Science student at BRAC University, graduating in 2026. I have experience developing full‑stack web applications using React, Next.js, Node.js, and databases such as MySQL and MongoDB. I designed a federated learning framework for multimodal breast‑cancer detection that improved accuracy by 11.8% on the smallest dataset.
B.Sc. · Computer Science
B.Sc. · Computer Science
VocabBangla – English-Bengali Vocabulary Learning Platform
Live swipe-based vocabulary app covering 3,363 Cambridge B1 words, with JWT-authenticated progress
tracking, a session-history dashboard, and a serverless Express API.
Readdy AI – Voice AI Mock Technical Interview Platform AssemblyAI Hackathon
Built a voice-first interview agent with a finite 4-stage state machine, silence/inactivity watchdogs, and
anti-jailbreak guardrails against prompt injection and topic derailment; generates assessment reports.
E-Commerce Storefront – Online Store & Admin Portal
Built a storefront with a persistent cart (Context + localStorage) and COD checkout, plus an admin
portal for order fulfillment and inventory management across a relational schema (products, orders,
order_items, admins).
Money Tracker Personal finance app
Personal finance app with category-based budgeting and spending-trend dash-
boards
Care4All Full-Stack healthcare booking platform
Full-Stack healthcare booking platform appointment scheduling and
patient records with role-based access
A Shared Embedding Framework for Interpretable Heterogeneous Federated Learning in Multimodal Breast Cancer Detection without Raw Data Sh
Designed a federated learning framework (PyTorch, Flower) unifying 3 structurally different breast-
cancer datasets into a shared embedding space; equal-weight aggregation improved the smallest
dataset’s accuracy by +11.8% (70.8% → 79.2%) over local-only training while holding 98.3–98.8%
accuracy on the larger nodes, with SHAP-based interpretability and differential-privacy-protected
aggregation.