Ted Xiao

JSRL is a meta-algorithm that uses a pre-existing guide-policy along with a learned exploration policy to quickly explore and solve new tasks.

By using the guide-policy to form a curriculum of starting states for the exploration-policy, we are able to efficiently improve performance on a set of simulated robotic tasks.

In this paper, our aim is to test the scalability of prior IL + RL algorithms and devise a system based on detailed empirical experimentation that combines existing components in the most effective and scalable way.

Our complete method, which we call AW-Opt, combines elements of advantage-weighted regression and QT-Opt, providing a unified approach for integrating demonstrations and offline data for robotic manipulation.

Presented at the Conference on Robot Learning, 2021.

This project proposes learning on top of unlabeled teleoperated human play data as a way to scale up multi-task skill learning

We introduce Play-LMP, a self-supervised method that learns to organize play behaviors in a latent space and then reuse them at test time to achieve specific goals.

Presented at the Conference on Robot Learning, 2019.

This literature review surveys existing work in quadrotor control at a broad level, and then examines two specific approaches in real-time control scenarios: learning-based model predictive control (LBMPC) and reachability-based safe learning.

Real-time safety-constrained scenarios encapsulate challenges that extend to many other research areas.

I founded a student-run non-profit machine learning organization focusing on workshops, industry projects, and research.

I grew the organization to more than 80 undergraduate and graduate students in 18 months.

I served as Vice President in Fall 2015. I worked with clients, determined strategic project directions, and lead consultants.

Projects I worked on: Valve, National Basketball Assocation, Twitch.tv, Warby Parker

In less than 36 hours, we built a parser and tokenizer to create a programming language out of Tweets.

As a Technology Advisor, I was part of the founding team and saw the organization grow and mature. I designed DiversaTech's website that has been used since Spring 2016.

SayCan combines the reasoning and planning capabilities of large language models with grounding through affordance estimation.

The robot can act as the language model’s “hands and eyes,” while the language model supplies high-level semantic knowledge about the task

We propose the objective of learning a functional understanding of the environment by learning to reach any goal state in a given dataset.

We employ goal-conditioned Q-learning with hindsight relabeling and develop several techniques that enable training in a particularly challenging offline setting.

We also show that our method can learn to reach long-horizon goals across multiple episodes through goal chaining, and learn rich representations that can help with downstream tasks through pre-training or auxiliary objectives.

This textbook is used for several university AI Safety courses, and includes contributions from field leaders such as Ian Goodfellow, Max Tegmark, and Ian Goodfellow.

The Adversarial Machine Learning chapter provides a technical tutorial on adversarial attacks and defense for deep neural networks.

Term Paper for CS294-112 Deep Reinforcement Learning, Spring 2017

This project uses Generative Adversarial Networks to learn dynamics models used for Tree Search methods with Deep Value Networks.

Term Paper for CS281A Statistical Learning Theory, Fall 2016

We leverage expectation-maximization, graphical methods, and Recurrent Neural Networks to achieve state-of-the-art results in building baseline power prediction.

I implemented the motion planning module for a Pioneer robot for an experiment investigating human-friendly task planning algorithms.

I created an MVP for a safety and navigation application.

We won multiple pitch competitions, culminating in presenting at IBM Interconnect 2016 in Las Vegas.

A guessing game inspired by GeoGuessr, personalized for UC Berkeley.

It was the top post on the UC Berkeley subreddit and saw 8GB of traffic in 48 hours.

Job Description

I designed the Asian American Association's website that was used between Spring 2015 and Spring 2016.