Computer Science student specializing in Software Engineering, AI/ML, and Full-Stack Development. Built 8+ projects, won 10+ awards, and currently working as an ML Engineering Intern.
Consistent problem solving and open-source contribution
Proficiency based on project usage and problem-solving experience
Production-ready systems with real-world impact
Applied research in intelligent diagnostics, embedded systems, and responsible AI
This work investigates a hybrid diagnostic framework for veterinary care that combines a Decision Tree for interpretable, rule-based symptom triage with a Naïve Bayes classifier for probabilistic reasoning over incomplete or noisy symptom reports. To move beyond diagnosis alone, an A* search formulation is layered on top of the classifier output to generate ranked, cost-aware treatment pathways, treating each intervention as a node weighted by clinical cost and urgency. The system is exposed through a Flask REST API with a lightweight dashboard for real-time symptom entry and result inspection. Evaluated on held-out validation data, the hybrid approach outperforms either constituent model in isolation, while preserving the explainability required for a clinician to trust and act on its output.
Mushroom cultivation is highly sensitive to small deviations in temperature and humidity, where brief excursions outside optimal ranges can compromise an entire growing cycle. This project develops a closed-loop environmental control system built on the ESP32 microcontroller, using DHT22 sensors for continuous temperature and humidity sampling and relay-driven actuators for automated fan and misting control. Firmware written in C++ over the Arduino core performs non-blocking sensor polling, threshold-based control logic, and resilient Wi-Fi reconnection, with live telemetry surfaced through a remote dashboard. The system has been deployed on an active mushroom farm, where it replaces manual environmental checks with continuous, automated regulation — demonstrating a practical pattern for low-cost precision agriculture in resource-constrained settings.
Examines ethical concerns in digital health monitoring systems — including fairness, equity, privacy, and AI bias. Analyses real-world case studies (IBM Watson, Teladoc) through the ACM Code of Ethics and proposes solutions for responsible IoT-based healthcare deployment.
Internships, ambassadorships, and hands-on engineering roles
Building and deploying ML models for real-world AI-driven solutions.
Campus outreach, campaign leadership, and student-research liaison.
STEM outreach, event organization, and community building for women in tech.
Promoted AI developer tools and educated peers on AI-assisted workflows.
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United International University · 2023 — 2027
CGPA 3.50+
BAF Shaheen College Kurmitola
GPA 5.00
BAF Shaheen College Chattogram
GPA 5.00Open to Software Engineering, AI/ML, and Full-Stack internships and roles
