College Completed
Academic foundation
Completed higher secondary education and prepared for the next stage in computer science.
01 AI ENGINEER · SOFTWARE BUILDER · RESEARCHER
I’m Md. Minhajul Islam — a CSE graduate and AI Engineer Intern at NEXVIX, turning computer vision, deep learning, and agentic ideas into tested software products.
02 ENGINEERING TOOLKIT
Built through production-minded projects, research experiments, and end-to-end software. Each capability now assembles visibly from 0% when it enters view.
03 SELECTED WORK
Each project explains the real problem, the system I built, and the engineering evidence behind it.
Removes people from crowded photographs and reconstructs the hidden background. I built a multi-stage pipeline that detects each person, refines the mask, performs global inpainting, and locally restores difficult regions.
YOLOv8x-seg → LaMa → Stable Diffusion 2, evaluated for visual quality and residual detections.
Turns a dealership into an AI-assisted operation. Customers can search inventory and speak with a voice agent while staff manage leads, appointments, inventory, and traceable call outcomes.
Production-style FastAPI architecture with secure Supabase data access and deterministic relational test data.
Investigates how to make image inpainting faster without sacrificing generation quality. I designed and compared lighter U-Net configurations against a Stable Diffusion baseline.
Eight-month senior design project with reproducible experiments, deployment code, and quality-efficiency analysis.
Guides a user through a PHQ-9 mental-health screening conversation, calculates severity, detects crisis language, and produces a downloadable assessment report.
Local LLaMA 3 inference keeps the conversational model on-device; JWT and MongoDB support secure user sessions.
Classifies brain tumors from MRI scans. The work progressed from an overly simple binary dataset to a more realistic multiclass Figshare dataset and a complete CNN evaluation workflow.
Shows model-development judgment: dataset correction, preprocessing, multiclass training, and evidence-based evaluation.
A browser-based communication product where authenticated users exchange messages instantly through persistent, bidirectional connections.
Built as a software-engineering project with Express APIs, Socket.io events, and a responsive Tailwind/DaisyUI interface.
Connects a conversational sales agent to live vehicle inventory and real appointment availability. The agent can answer product questions, explain trade-offs, find matching cars, and schedule a test drive during the call.
Containerized Node service with protected inventory tools, Cal.com booking integration, health checks, and production deployment guidance.
Reduces manual toll-booth processing through a web-based workflow for vehicle identification, transaction handling, and centralized record management.
Demonstrates end-to-end product thinking across interface design, application logic, and persistent operational data.
Brings fashion shopping and customer support into one AI-assisted retail experience. A React storefront connects to tools for product search, comparison, stock checks, order tracking, and return eligibility.
FastAPI + Supabase tool gateway with typed requests, policy retrieval, audit logs, and confirmation checks for order changes—keeping database credentials out of the AI layer.
04 SYSTEMS IN MOTION
A rotating product-level view of the experiences and pipelines behind the repositories.
“I found two SUVs within your budget. Would you like to book a test drive?”
“Over the last two weeks, how often have you felt little interest or pleasure in doing things?”
Current score8Moderate range · supportive guidance prepared
05 RESEARCH PRACTICE
I approach AI as an engineering discipline: understand the failure, research the evidence, build the smallest convincing system, validate it, and turn the result into something people can use.
A Machine Learning-Driven Framework for Enhancing Cognitive Function Using tDCS and Brain Gym Interventions
Machine Learning-Enhanced Cardiovascular Disease Risk Prediction: A Clinical Intelligence Framework
FORTHCOMING06 CAREER SIGNAL
Education became research. Research became engineering. The next step is building ambitious AI products with a team that values depth, ownership, and measurable impact.
Completed higher secondary education and prepared for the next stage in computer science.
Built foundations in software engineering, machine learning, deep learning, and computer vision.
Began university research in lightweight diffusion, image inpainting, and object removal.
Advanced a multi-stage computer-vision pipeline from failure analysis to reproducible results.
Engineering AI capabilities and dependable software workflows for real product use.
Ready to build intelligent systems that move from research evidence to production value.

07 THE PERSON BEHIND THE PIPELINE
I combine a researcher’s skepticism with an engineer’s urgency. Whether I’m reconstructing a missing scene, designing safer conversational AI, or shipping a real-time product, the goal is the same: rigorous systems that create clear value.
Scouting leadership shaped how I work — stay calm under constraints, communicate clearly, and move a team toward the objective. I am now growing that discipline at NEXVIX as an AI Engineer Intern.
08 START A CONVERSATION
Hiring for an AI or software role? Building a product that needs vision, agents, or dependable engineering? Send the context directly.
Email me directly