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@ctcusc @clvrai @DeepSymphony @penn-pal-lab
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edwhu/README.md

Hi, I'm Edward. Currently, I'm interested in developing data-driven methods that interact, explore, and learn from the world. My research investigates deep reinforcement learning, perception, and robotics

🤖  Research Artifacts

Here are the codebases of my research projects so far.
scaffolder Privileged Sensing Scaffolds RL (ICLR'24 Spotlight)
planning goals for exploration Planning Goals for Exploration (ICLR'23 Spotlight)
interactive reward functions Training Robots to Evaluate Robots (CoRL'22 Best Paper Award)
robot aware control Know Thyself: Transferable Visual Control Policies Through Robot-Awareness (ICLR'22)

Nerd stuff

I like studying codebases that are elegantly written and do cool things. Some topics that I found interesting lately: dataloading at scale, Jax renderer, Jax Monte-Carlo Tree Search library.
Some of my side projects:
gpt2 slackbot Chatting with GPT2 in slack
optical illusion A cool optical illusion

Something to think about as an ML researcher.

What is your way? I think researchers start out very pure hearted, but can easily end up misled and lost. The incentives of the modern research community, particularly ML, are misaligned with doing good science. To employ an analogy, ML is currently like a hackathon. You are incentivized to put together an MVP that works just enough to pass the appraisal of the judges. You feel obligated to use the shiny new "X" because it will garner public attention. Companies with free t-shirts and kickbacks swarm around you.

Yes, some of these things are unavoidable. But if you blindly follow the noise, you may end up in the eye of the storm - at a standstill, with no exit in sight.

Ant Death Spiral

Don't be distracted by the noise, and find out your truth.

Pinned

  1. clvrai/furniture clvrai/furniture Public

    IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks

    Python 488 56

  2. penn-pal-lab/peg penn-pal-lab/peg Public

    Code for "Planning Goals for Exploration", ICLR2023 Spotlight. An unsupervised RL agent for hard exploration tasks.

    Python 65 3

  3. penn-pal-lab/interactive_reward_functions penn-pal-lab/interactive_reward_functions Public

    Code release for "Training Robots to Evaluate Robots" (CoRL'22, Best Paper Award)

    Python 18 1

  4. penn-pal-lab/scaffolder penn-pal-lab/scaffolder Public

    Official codebase for "Privileged Sensing Scaffolds Reinforcement Learning", contains the Scaffolder algorithm and Sensory Scaffolding Suite.

    Python 8