Tanish Nagrani — Operations Associate

I’m a MS in Computer Science (Fall ’25) student at the University of Colorado Boulder (GPA: 4.0/4.0), focused on building AI-driven systems and scalable software that solve real-world problems across healthcare, recommender systems, sustainability, and distributed systems. Previously, I worked as a Data Science Intern at SigTuple, where I built and deployed production-grade deep learning pipelines for veterinary blood diagnostics. My work spanned EfficientNet and YOLOx-based vision models, training optimization and INT8 quantization, and integration into a NATS-based microservices architecture, enabling low-latency, high-accuracy inference in real clinical workflows. I’ve also been actively involved in research at the intersection of NLP, recommender systems, and knowledge graphs. I co-authored and presented a Knowledge Graph–enhanced Conversational Recommender System at IEEE ICCCNT ’24, and my work on improving EV ecosystems in urban environments received the 2nd Best Paper Award at IEEE IATMSI ’25. Beyond technical work, I enjoy contributing to academic and student communities. I’ve served as a DBMS and Data Science course grader, Vice President of IIIT Vadodara’s Cultural Committee, and Public Relations Co-Lead at Google Developer Student Clubs, experiences that strengthened my ability to collaborate, lead, and communicate across diverse teams. I’m currently seeking Summer 2026 internships and longer-term opportunities where I can contribute to AI/ML products, distributed backend systems, and applied research. If you’re building something impactful in ML, data systems, or large-scale software, I’d love to connect.

Stackforce AI infers this person is a Healthcare-focused AI/ML Developer with strong software engineering skills.

Location: Boulder, Colorado, United States

Experience: 2 yrs