Hi, there!

I am Moontaha Nishat Chowdhury, a volunteer researcher exploring Privacy-Preserving Machine Learning and Cryptography. I was a Lecturer of Computer Science and Engineering Department, at Ahsanullah University of Science and Technology, Dhaka, Bangladesh, and obtained my Bachelor of Science in CSE from the same institution. My research interest includes: Privacy-Preserving Computing, Cryptography, Distributed Decentralized Learning, Human Computer Interaction, and Machine Learning. I am actively seeking Ph.D. opportunities to further enhance my expertise and contribute to research in this domain. For additional information, please see my publications.

Research Interests

My current research focuses on privacy-preserving machine learning (PPML), particularly fully homomorphic encryption (FHE) based end-to-end privacy preserving recommendation system. In my most rescent publication, I have worked on developing efficient algorithms and optimization of matrix factorization on encrypted data, while solving the critical sparsity challenge, in order to reduce computational and communication overhead. In my ongoing work, I am developing an FHE Transformer framework that extends privacy-preserving capabilities for Large Language Models (LLMs) to enable inference on encrypted data in a distributed decentralized system.

Previously, I worked on smartphone sensor data analysis and recommendation systems, where I have analyzed Human Activity and Mobility through embedded smartphone sensor data, using machine learning techniques, and found meaningful insights and patterns from that data, which can be used as a metric for various real-time applications (e.g. Production, Retails, Health-Care Sector, etc.). This experience with data-intensive applications led me to privacy challenges in machine learning, where sensitive user information needs protection while maintaining system functionality.

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Email

chowdhurymoontaha3[at]gmail[dot]com

Feel free to contact regarding any queries. Thank you.