I'm a Software Engineer and AI Researcher working at the intersection of privacy, fairness, and production AI systems.

I design systems that are not only functional — but measurable, secure, and robust against adversarial inference.

• Bias-aware semantic anonymization
• Adversarial inference on LLMs
• Fairness metrics (demographic parity, equal opportunity, predictive parity)
• Formal privacy guarantees in domain-specific text
• Medical NLP & high-stakes AI evaluation systems

• Production-grade backend APIs (FastAPI / Flask)
• Microservice architectures (Docker, Kubernetes, CI/CD)
• Fairness & bias evaluation pipelines in Python
• AI-driven simulation systems (exam training / decision systems)
• Secure ML deployment workflows

Head of Software Engineering Program

I teach:

• Computer Architecture (8086 Assembly)
• Networks & Information Security
• Algorithms using Python

I enjoy bridging theoretical foundations with real-world system design.

I’m exploring the intersection of:

• Privacy and robustness in large language models
• Fairness-aware system design
• Secure deployment of high-stakes AI systems

With a focus on building AI systems that are both technically rigorous and production-ready. focuses on improving the reliability, privacy, and fairness of AI systems operating in sensitive domains.

Interested in collaborating on:

• Privacy-preserving NLP
• Fairness in AI systems
• Medical AI training platforms
• Secure AI infrastructure