Projects

Things I've built

Production autonomy at Rivian, plus the robotics, manufacturing, and medical-device projects that led there.

Video: Autonomy & AI Day Highlights © Rivian

Rivian · 2020 – present

Hands-free driving, on every Rivian

I build the scene understanding, motion planning, and control behind Rivian's driver-assistance features, and led several of them from zero to launch. These systems decide where the lanes are, which one the vehicle is in, and the path it should take, then steer it there smoothly. They run on every Rivian platform, and Universal Hands-Free now works on more than 3.5 million miles of roads in the US and Canada. I also drive my own R2 every day, and it's always great to test my own software.

Universal Hands-Free Automated Lane Change Large driving model Scene understanding LKA · LDW · AEB · FCW Patent pending
  • Large driving model: my most recent work is on post-training and guardrail design for Rivian's large driving model.
  • Zero-to-one launches across the planning and control stack: the lateral controller, scene-understanding and lane-geometry engines, the move to in-house perception, and HD/SD-map integration.
  • Lane-level localization: a Bayesian filter that fuses bird's-eye-view lane topology, SD-map, and barrier cues with turn-signal intent to estimate lane count and the ego lane with calibrated confidence.
  • Motion planning and trajectory optimization powering hands-free driving and automated lane changes.
  • In-house safety features (lane keeping, lane departure warning, automatic emergency braking, forward collision warning) from prototype to production-intent validation.
  • Technical lead: set architecture and roadmap, ran design and code reviews, and mentored engineers on planning, controls, and V&V.

“On the highway, hands-free driving was sublime. It easily handled lane changes and congested roads without drama.”

Engadget, 2027 Rivian R2 review, Oct 2026

Rivian “just leap frogged nearly every competitor in the hands-free driving race.”

The Drive, Dec 2025

“UHF provides hands-free driving assistance on 3.5 million miles of roads… That puts it ahead of GM's Super Cruise.”

GreenCars, R2 first drive, Jul 2026

The video clip is embedded from Rivian's official YouTube channel and belongs to Rivian Automotive. Quotes are excerpts from the linked articles. This site is not affiliated with or endorsed by Rivian. Learn more at rivian.com/autonomy.

Before Rivian

Where I started on vehicles

Lyft Level 5 · 2019

Steering control for a self-driving fleet

Built a high-fidelity vehicle model for control design and closed-loop simulation, benchmarked it against standard frameworks, and designed a steering-angle controller that was tested on Level 5's autonomous fleet.

Rivian · 2017, 2018

Sensors and fault monitors for actuation

Integrated long-range and corner radar, ultrasonic, and driver-monitoring sensors, and built fault detection and tolerance monitors for steering and braking. Also built vehicle models and logging/replay tools for a dSPACE prototyping rig.

IIT Bombay Racing · 2011 – 2015

India's first electric car to finish endurance

IIT Bombay Racing was the first Indian team ever to complete the endurance event at Formula Student with an electric car, at Silverstone. I led the powertrain team and built the car's first electronic differential using torque vectoring, for 23% better acceleration and 46% less weight.

Related papers →

Personal projects

Outside of work

Side project · Python, FastAPI, Claude

A self-hosted household finance dashboard

It's a private, self-hosted dashboard that brings a household's finances into one place. It syncs bank and brokerage accounts through Plaid and SnapTrade, adds hand-entered ones for everything else, and turns them into four views: net worth, monthly expenses, investments, and a stock watchlist.

Highlights include a Monte Carlo projection of where savings are headed, a time-weighted return chart against the S&P 500, transaction categorization that explains why each purchase landed where it did, and Claude-powered Q&A and auto-categorization that only applies approved changes. It also has guards that stop a flaky bank feed from looking like a real drop in net worth.

It's built with a FastAPI backend, a single SQLite file, and a plain HTML, CSS, and JavaScript frontend with hand-drawn SVG charts. Tokens are encrypted at rest, and the app is reachable only by its two users.

Read the design notes

Built after I got fed up managing our finances across several platforms, with apps that kept failing to link accounts.

Both papers below started when Apurba took Stanford’s CS329H, Machine Learning from Human Preferences.

Paper · arXiv, October 2026

Similar models, broken odds

Chatbot Arena ranks language models by giving each one a single score. Classical choice theory predicts where that breaks down: people should tell near-copies apart more decisively than their scores imply. This project tests that prediction on public Arena votes, using model lineage (versions of one model, sizes of one generation, models from one lab) as the measure of similarity, and checks it with language-model judges and independent human-rating datasets. A small fix to the scoring model predicts held-out votes better than the standard one.

Read the paper on arXiv

Paper · arXiv, October 2026

Same person, different advice

AI financial advisers set a client's stock allocation largely from one question about risk tolerance, but people answer that question differently when asked again. This project measures both halves: how much the answer moves on a retest, using public survey panels, and how much seven LLM advisers' advice moves when only that answer changes. It also tests fixes, such as telling the model the answer is noisy or asking a few more questions.

Read the paper on arXiv