Research & Publications
Contributing to the advancement of AI through research in privacy-preserving machine learning, continuous learning systems, and ethical AI development
Publications & Thesis
Privacy Threats in Continuous Learning: Machine Learning Security Analysis
Saint Louis University • Expected: May 2025
My thesis explores the delicate balance between model adaptation and data privacy. This research is personal to me - I believe we can have intelligent systems without compromising user trust.
Impact: Proposing novel techniques that could protect millions of users' data in real-time ML systems
This research combines my passion for privacy with cutting-edge ML - it's not just my thesis, it's my contribution to safer AI.
Inspecting CNN and ANN Algorithms using Digit Recognition Model
International Research Journal of Engineering and Technology (IRJET) • Volume 7, Issue 6
My first publication! This research optimized CNN and ANN algorithms for digit recognition, achieving 99.2% accuracy on MNIST. It taught me the importance of systematic experimentation and clear scientific communication.
Impact: Contributed novel architectural insights that improved training efficiency by 30%
This paper represents my entry into the research world - proof that curiosity and persistence can lead to meaningful contributions.
Current Research Interests
Privacy-Preserving Machine Learning
Developing techniques to protect sensitive data in ML systems while maintaining model performance.
Continuous Learning Systems
Investigating security and privacy challenges in models that continuously adapt to new data.
Ethical AI Development
Implementing fairness, transparency, and accountability in production AI systems.
Large Language Models
Optimizing and deploying transformer-based models for enterprise applications.
Interested in Research Collaboration?
I'm always excited to collaborate on research projects in privacy-preserving ML, continuous learning, and ethical AI development.
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