Silverstone, 1:4 · attempt 1 · 0 m · 0 samples · loss — · · arrows or wasd to drive

Aniket Mittal

Aniket at dinner, smiling through hot pot steam

I’m a 3rd year undergraduate EECS & Business student through the Management, Entrepreneurship & Technology program at UC Berkeley.

I am broadly interested in machine learning. I’ve previously interned at NASA, Visa and Intel broadly building and researching application-specific deep learning models and agents. In my free time, I love to watch F1 and football, learn to play golf and watch car reels.

Above: The F1 car above is driven by a small neural network that trains by imitation learning (DAgger) in your browser, with a physics-based controller as the teacher. Each tab is a replica of a real F1 circuit so you can see the car take on different obstacles as you learn more about me. You can also race the current checkpoint of the model, or switch the graphics to ASCII.

aniket_mittal [at] berkeley [dot] edu
  1. Roboball

    2026

    Real-time ROS2 perception-and-control system driving a UR7e arm to track and repeatedly bounce a ball, from camera calibration and ball detection to trajectory prediction and PID control over MoveIt IK.

  2. CrossOdds

    2026

    Real-time arbitrage scanner for prediction markets. Finds guaranteed-profit opportunities across Kalshi and Polymarket using AI-powered market matching.

  3. ImageVision

    2025

    AI photo editor that combines SDXL, CLIP, ControlNet, SAM and FBA Matting into a single pipeline. Edit images and ask questions about them in natural language.

  4. FireSight

    2023

    Deep learning system that predicts wildfire spread from 12-channel environmental data and generates escape-route insights. Preprint on EarthArXiv.

More on GitHub.

  1. Contract Machine Learning Engineer · AWS

    Oct 2026 – Present · Berkeley, CA

    Annapurna Labs – Developing an RL framework to train LLM agents for RTL debugging and optimization.

  2. Software Engineering Intern · Visa

    Jun – Aug 2026 · Austin, TX

    Embedded Payments Platform – Built a deep learning based forecasting service for vendor payments.

  3. Applied AI/ML Intern · Intel

    Apr – Jun 2026 · Santa Clara, CA

    Data Center & AI Group – Designed agentic workflows for IP development and formal verification.

  4. ML Engineering Intern · NASA

    Jun – Aug 2025 · Mountain View, CA

    Data Sciences Group – Developed explainable ML techniques for exoplanet detection in Kepler and TESS signals.

    NASA Science · NASA AI Model That Found 370 Exoplanets Now Digs Into TESS Data

  5. Student Researcher · San José State University

    Feb 2023 – Aug 2024 · San Jose, CA

    Xuanhong An Group – Researched adjoint-based optimization for CFD simulations of fish-like swimming.

    APS DFD 2023 · Swimming Fast Versus Swimming Efficiently

  6. ML Engineering Intern · NASA

    May 2023 – May 2024 · Mountain View, CA

    Data Sciences Group – Trained deep learning models for cosmic ray detection for the James Webb Space Telescope.

    2024 NASA Ames Center Innovation Fund (CIF) Grant · Fast and Accurate Detection of Cosmic Ray Contamination in JWST Data

  7. Student Researcher · Stanford University

    Jun 2022 – Mar 2023 · Stanford, CA

    Farhat Research Group – Designed CFD meshes for optimizing airfoil designs.

    Center for Turbulence Research – Wrote CFD optimization code for nozzle flow in propulsion engines.

You can often find me doing or watching one of these in my free time.

The fastest route is email. I reply to most things within a day.