About
Engineer by trade, researcher at heart
I move between shipping production AI systems and publishing research on making them efficient — here's the longer story.
I am an AI Research Engineer at Robot Bulls and a Research Assistant at MILAB, North South University, where I completed my B.Sc. in Computer Science and Engineering in December 2025 with a CGPA of 3.83/4.00 and a Merit Scholarship for ranking in the top 1% of my class.
My work sits at the intersection of research and production: at Robot Bulls, I'm researching and building a real-time Talking Head system — letting users hold natural, face-to-face voice conversations with AI. At MILAB, I co-authored Z-Pruner, a post-training LLM pruning method published at IEEE AICCSA 2025, and developed TimeClipAI, a real-time temporal action localization framework. My research spans Temporal Action Localization, Efficient LLM Deployment, and Small Language Models for edge AI.
I am actively open to research collaborations and AI engineering opportunities, with a particular interest in real-time conversational AI, efficient model deployment, and real-world applications of large language models.
Education
Academic background
North South University
Bachelor of Science in Computer Science and Engineering
Sep 2021 – Dec 2025 · Dhaka, Bangladesh
- Merit Scholarship - Top 1% of class
- Published research at IEEE AICCSA 2025
- Led multiple AI and full-stack development projects
Skills
Technical toolkit
Everything I use across research prototyping and production engineering.
Languages & Frameworks
Machine Learning & AI
Data & Visualization
Database & DevOps
Tools & Productivity
Philosophy
How I think about the work
The most impactful research doesn't stay in the paper — it ships.
My research philosophy centers on bridging the gap between cutting-edge AI research and practical, real-world applications. The most impactful research not only advances theoretical understanding but also provides tangible benefits to society.
I am particularly passionate about making AI more accessible and efficient. Through my work on LLM pruning and RAG systems, I aim to democratize access to powerful AI capabilities — enabling deployment in resource-constrained environments and underserved communities.
In engineering work, I prioritize scalable, maintainable systems that integrate AI seamlessly, and I believe strongly in interdisciplinary collaboration and open science.
Graduate Studies
Pursuing advanced research in efficient AI systems and model optimization.
Research Impact
Publishing impactful research that advances AI accessibility and efficiency.
Global Collaboration
Collaborating with researchers worldwide on meaningful AI projects.
Get in touch
Let's build something together
I'm open to AI engineering roles, research collaborations, and PhD opportunities — particularly around efficient LLM deployment and production AI systems.