
Thesis on machine learning with an applied focus on business impact and model interpretability. Expected graduation December 2025.
Senior BI Analyst & Data Engineer • Promoting Secure, Sustainable, and Ethical AI
I build clear, sustainable, and actionable intelligence—bridging data engineering, analytics, and responsible AI to help organizations make confident decisions.
What I explore and bring into client solutions.
I am actively seeking research and innovation opportunities at the intersection of Ethical AI, Data Science, and Big Data — with a focus on interpretability, fairness, and building robust, scalable systems. My goal is to develop solutions that uphold academic rigor while meeting the practical demands of high‑stakes, real‑world applications. I aim to work collaboratively with faculty, researchers, and industry leaders on transparent models, bias mitigation, and human‑centered decision support — turning data into actionable, trustworthy intelligence that drives both scholarly advancement and measurable business impact.
Thesis on machine learning with an applied focus on business impact and model interpretability. Expected graduation December 2025.
Thesis: Machine Learning & Black Swan Events (Supervisor: Prof. Mahbubul Alam Majumdar).
Java Core, J2EE, JavaFX, Servlet, WebSocket, JDBC, REST, JSON, XML.
About: National capacity-building program emphasizing enterprise Java development and deployment best practices.
SDLC, Requirements Engineering, System Design & Analysis.
About: Hands-on workshops covering end-to-end lifecycle with tooling for traceability and governance.
For AI/BI projects, advisory, or speaking—reach out. I respond within 1–2 business days.