Hyndhava Mahesh

I am an AI & ML undergraduate focused on building agentic systems that solve real-world problems in healthcare and legal tech. I combine hands-on project work with participation in competitive hackathons to iterate rapidly and deliver prototypes under tight deadlines.

My projects include privacy-preserving federated learning models that achieved high diagnostic accuracy and multi-agent workflows for both healthcare decision support and legal compliance. I emphasize scalable architectures, data privacy, and practical evaluation on synthetic and real-world datasets.

I have coordinated AI-focused events and hackathons, managing end-to-end logistics and mentoring teams to successful outcomes. I enjoy collaborating with faculty, judges, and organizing committees to create impactful student experiences.

I bring a technical toolkit spanning Python, ML libraries, federated learning, and prompt engineering, paired with strong teamwork and communication skills. I am motivated to join teams where I can apply agentic AI and privacy-preserving methods to production-ready solutions.