Hello World!

I’m a Machine Learning Engineer at HARP Research, where I help build and improve AI systems for real-world use. Before this, I worked as a Research Assistant in the Data Security and Privacy Lab with Professor Lei Yu, studying privacy risks in machine learning and large language models. I also conducted research in Professor Oshani Seneviratne’s BRAIN Lab, focusing on label inference attacks in federated learning.

I graduated from Rensselaer Polytechnic Institute with a degree in Computer Science and a minor in Economics. During my time there, I developed a strong foundation in Python, PyTorch, TensorFlow, and full-stack development—skills I’ve applied in both research and production settings.

I care most about building things that work well in the real world—something clear, useful, and reliable. Whether it’s a research prototype or a production system, I try to focus on what actually makes an impact: code that’s easy to maintain, systems that can scale, and tools that solve real problems for real people.

Research Interests:

• Trustworthy AI
• Adversarial Robustness
• Privacy in Machine Learning and LLMs
• Secure AI System Design and Evaluation

Current and Past Explorations:

• Membership Inference Attacks
• Label Inference Attacks
• Privacy and Security in AI BOM and AI SBOM
• AI for Social Good