About
Computer Science & Engineering student at IUBAT with hands-on experience building full-stack web applications and AI-integrated systems using Python, C#, PHP, Django, and ASP.NET Core. Also engaged in machine learning research, including an ongoing thesis on breast cancer detection and published work in hospital comfort prediction.
Education
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B.Sc. in Computer Science & EngineeringInternational University of Business Agriculture and Technology (IUBAT)Computer Science & Engineering · 2023 – 2027
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Alim – ScienceTa'mirul Millat Kamil MadrasahScience · 2020 – 2021
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Dakhil – ScienceTa'mirul Millat Kamil MadrasahScience · 2018 – 2019
Skills
Tools / apps / platforms
Projects
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AI Resume AnalyzerReact 19, TypeScript, Zustand, Tailwind CSS, ASP.NET Core 8, Entity Framework Core, SQL Server, Llama 3, Ollama
Built a full-stack ATS resume analysis platform that scores resumes against job descriptions, provides categorized feedback, and includes analytics dashboards and role-based access.
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Car Auction & Trading Management System (POS)HTML, CSS, JavaScript, PHP, MySQL
Developed a POS and trading platform for a vehicle import business, including vehicle lifecycle tracking, shipment tracking, LC records, multi-currency support, customer modules, and reporting.
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Django E-Commerce PlatformPython, Django, SQLite, HTML, CSS, JavaScript, SSLCommerz
Built a responsive e-commerce application with authentication, product catalog, cart and wishlist, sandbox checkout, order tracking, and admin inventory management.
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Blood Bank Management SystemPHP, MySQL, HTML, CSS
Built a blood bank management system with admin authentication, donor/recipient CRUD, blood stock tracking, compatibility validation, and workflow status management.
Courses & certifications
- Code in Place (Python) · Stanford University
- Robotics Camp — Level 1 & Level 2 (IoT and Robotics)
- Hult Prize OnCampus Program
- HSK Level 1 · Chinese Language Course
- BBLTJ 11 Program Graduate · BYLC
📚 Publications
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Improving Hospital Building Thermal Comfort Prediction: A Machine Learning Approach
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A Machine Learning Approach for Predicting Thermal and Visual Comfort in Naturally Ventilated Hospital Buildings in Rural Regions