Rishabh Goel
Researcher, Engineer, Student
I like building things that are cool and functional. Check some of it out here. I'm currently working on DNA sequence generation using deep learning techniques. I'm also a computer science student at UCLA, so if you're ever in LA or want to talk about cool stuff, reach out
Founder
Interchat
Created an AI-powered collaboration tool enabling multi-user communication with integrated AI assistants. Scaled platform to 100+ users across 5 organizations.
Machine Learning Research Intern
Invista Health
Developed a Flutter-based survey analysis tool to support remote patient monitoring of geriatric patients. Deployed in active use for 600+ patients with 2+ comorbidities
Product Management Intern
Pacific Links Foundation
Led and directed an initiative creating AI-powered English tutors with real-time voice-to-voice technology. Used by 2,000+ human-trafficking survivors in Vietnam, expanding scalable access to English education
Software Engineering Intern
Rezolve AI
Developed a sentiment-aware voice AI customer support agent with a RAG-based context system for a Series A startup. Deployed production-ready demo on Google Cloud for 150+ businesses
DNA Discovery Research
Designing a discrete diffusion model with score-entropy optimization to generate novel cis-regulatory DNA sequences. Aiming to improve predictive modeling of gene regulation and accelerate discovery of therapeutic DNA elements
VibeCAD
Built a text-to-CAD agent that generates 3D models from text descriptions. The 3D models are generated using OpenSCAD and then exported directly into Onshape.Used AWS Bedrock for LLM inference and MCP server hosting and Next.js for the frontend.
Courseium
Built a course recommender system for UCLA students using collaborative filtering, content-based filtering, and hybrid filtering. Trained on Bruin Walk with over 1000 courses saved.
Quantum Cryptography Research
Developed a transformer-based validator for Quantum RNGs, introducing a novel alternative to statistical tests. Achieved state-of-the-art speed and efficiency, with research presented at IEEE ISNCC 2024 and open-sourced
Clinical Text Classification Research
Applied text-embedding models for clinical document classification, removing training overhead and improving LLM compatibility. Conducted at UCLA CS Department and published in the Journal of Emerging Investigators
Let's work together
I'm always interested in hearing about new projects and opportunities. Whether you have a question or just want to say hi, feel free to reach out.