SEEMANDHARJAIN
PhD student @ UC San Diego, advised by Prof. Manmohan Chandraker. I build multi-agent LLM systems that do 3D vision research autonomously — and this page is rendered the way I see the world: as a cloud of gaussians, optimizing itself into something meaningful. Watch it train. →
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Point cloud → person
Every 3DGS scene starts as structureless noise; so does every research career. Mine initialized at IIT Indore (B.Tech, CSE), where I founded HealthAIgnite, a healthcare computer-vision consultancy — my first densification step.
The optimizer then routed me through an MS at UIUC (GPA 3.92/4) with Prof. David Forsyth — single-shot 3D reconstruction, convex decomposition, intrinsic images, relighting with diffusion models — and a Siebel Scholar (Class of 2024) award.
Today I'm a PhD student at UC San Diego working at the intersection of LLM agents and 3D vision: multi-agent systems that read papers, write code, run experiments, and discover new methods on their own. Recent splats in my covariance: Nerfify (CVPR 2026 Highlight) which turns NeRF papers into executable code, Splatify — its 3DGS counterpart with knowledge discovery — and Idea2Paper, a pipeline that goes from literature to novel method to validated paper, end-to-end.
Along the way: Google (Student Researcher, BigML — optimized SANA diffusion for Veo, built Gemma-2 captioning), Aireal (Research Scientist, CV), DOCOMO Innovations, and Salesforce (AMTS, AI).
What my gradients flow toward
Autonomous Research Agents
Multi-agent LLM frameworks that reproduce, discover, and innovate: papers → trainable code → new methods. Nerfify, Splatify, Idea2Paper.
Radiance Fields & 3DGS
NeRFs, 3D Gaussian Splatting, single-shot reconstruction, convex decomposition — explicit and implicit 3D, and the tooling to automate it.
Generative 3D & Diffusion
Diffusion models for 3D-aware image/video synthesis, relighting, intrinsic decomposition; faster sampling with better geometric consistency.
Converged publications
// each paper below is one cluster in the galaxy behind this text — 12 clusters, 12 papers
Recent densification events
Loss curve of a career
PhD, Computer Science · UC San Diego
Advisor: Prof. Manmohan Chandraker. LLM agents × 3D vision: autonomous research systems for NeRF/3DGS, generative 3D.
Student Researcher · Google (BigML, NYC)
Optimized SANA diffusion for Veo; Gemma-2-based captioning at scale.
Research Scientist (CV) · Aireal
Single-image → textured 3D mesh; AI interior design product (Livvy).
MS, Computer Science · UIUC
Advisor: Prof. David Forsyth. GPA 3.92/4. Siebel Scholar '24. 3D reconstruction, convex decomposition, relighting.
Salesforce (AMTS, AI) · DOCOMO Innovations (Research Intern)
Applied ML in production; large-scale contact tracing & recommendation research.
B.Tech, CSE · IIT Indore — founded HealthAIgnite
Healthcare-AI consulting focused on computer vision. Iteration 0.
Render a new view — together
The splats behind this card just spelled it out: I'm always up for collaborations on agents × 3D, radiance fields, and autonomous science.
sejain [at] ucsd [dot] edu