portrait A photo of me standing next to the Jet during build week 2019. The Jet is an autononomous, jet-powered, hovering drone. I built its computer vision system, which is used to supply zeroth order pose observations.

I am a software engineer based in Pittsburgh. I am interested in machine learning, robotics, computer graphics, and in some things that do not involve computers.

Contact me at ijdykeman@gmail.com .

Selected Professional Experience

Main Street Autonomy, since 2019

In 2019, I started Main Street Autonomy with a group of former self-driving engineers. We provide high-quality autonomy software to companies building robots.

Uber ATG, 2017-2019

I worked as a software engineer on the perception system for Uber’s autonomous vehicle.

  • Implemented improvements to the car’s core deep-learning-based, multi-sensor object detector
    • See my team’s publication on lasernet
  • Implemented visualization tools and process automation for the learning pipeline
  • As an intern in summer 2017, I implemented an experimental lidar-based object detection model

Tableau, Summer 2016

I worked with Tableau’s research team in Palo Alto on Evizeon, Tableau’s experimental natual langauge interface for data visualization.

Selected Projects

  • Deep learning
    • Researched prediction of hurricane damage using deep learning (article)
      • Used LIDAR terrain maps and convolutional neural networks to evaluate individual homes’ probability of being damaged under given hurricane wind conditions
      • Created a model which improves substantially (+.3 AUC) on the state of the art for single home level damage probability estimation
      • 3rd place Engineering project at Rice Undergraduate Research Symposium
    • Researched learning dictionary definitions from raw text (blog post)
      • Implemented a variational autoencoder with novel output modality of raw embedding vectors to write dictionary-style definitions of unseen words
      • The model produces definitions for words it has only seen in context, such as “smuggling: transferring in illicit items (especially food goods)”
    • Demonstrated that “deep image priors” can be used as a regularizer for direct image alignment (blog post)
    • Wrote a popular tutorial on conditional variational autoencoders
  • Computer vision
    • For PrepMatters, a test-prep company, I built a system for extracting data from user-provided document images. This let them score multiple-choice tests remotely without relying on expensive Scantron machines or expensive Scantron-provided answer sheets.
    • For Augary, LLC, I trained a random forest-based detector for cars and road signs on a mobile phone platform. I also built a lane detector for estimating how well-centered in the lane the driver is.
  • Graphics
    • Generate Worlds
      • An interactive world generator based on an accelerated constraint-solving algorithm.
      • Includes a custom deferred shading pipeline with shadow-mapped point lights
    • Brimming Sea
      • A real-time strategy game where the player can direct agents to build, gather resources, and fight
      • Agents use cooperative planning to build player-defined structures
      • Built with a custom engine using DirectX.
    • For Augary, LLC, I adapted expensive geometric routines to the GPU for mobile applications.


Rice University, BS in Computer Science