• Hi!
    I'm Kathy

    Machine learning, computer scientist.

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About Me

Who Am I?

Hi, I'm Kathy Jang. I just finished my Ph.D. in the department of EECS and Berkeley Artificial Intelligence Research Lab at U.C. Berkeley, and will be joining Waymo as a Research Scientist in the summer. My main academic interests are in applied machine learning, reinforcement learning, and control. I'm interested in the development of intelligent systems and reducing the overhead in transferring intelligent systems from their home in the digital world to the physical world (i.e. policy transfer). In future work, I'm eager to apply these principles to broader challenges across domains like natural language processing. With my background, my aim is to see the direct impact of my efforts by contributing to innovative AI research and solutions.

Outside of research, I live to travel and experience new things; when I'm back home in Berkeley doing research, I like to live like I'm traveling: meeting new friends, spontaneous outings, daring to try new foods and experiences, taking the time to appreciate art, all the small things! I am a people's person, love to hear stories, exchange ideas, and make things happen.

If you're interested in chatting with me about me about my research, let's talk! Please email me at kathyjang [at] berkeley [dot] edu.

Experience

Work Experience

Scientific Engineering Associate at Lawrence Berkeley National Laboratory Jan 2019 - Aug 2019

Advised by Professors Thomas Kirchstetter and Alexandre Bayen, I am working at Lawrence Berkeley National Laboratory conducting resarch in UC Berkeley's Mobile Sensing Lab. Groups I am involved include Berkeley Artificial Intelligence Research Lab (BAIR) and California Partners for Advanced Transportation Technology (PATH). This is a continuation of my previous work, but with a focus on energy and environmental analysis.

For more information, please view the Research section

Research Fellow at the Recurse Center Jan 2019 - Mar 2019

I continued my work on traffic optimization and policy transfer at Berkeley at the Recurse Center (RC). RC is a self-directed programmer retreat with one of the highest concentrations of passionate, curious, interesting people I have had the privilege to work with. I would encourage anyone with an itch to create and collaborate to explore RC.

ML Researcher at UC Berkeley Jun 2018 - Jan 2019

Advised by Professor Alexandre Bayen, I am working in Berkeley's Mobile Sensing Lab. Groups I am involved include Berkeley Artificial Intelligence Research Lab (BAIR) and California Partners for Advanced Transportation Technology (PATH). My research is focused on the application of deep reinforcement learning to traffic control and policy transfer.

For more information, please view the Research section

UG Research Assistant at UC Berkeley August 2017 - May 2018

Working in Professor Alexandre Bayen's Mobile Sensing Lab, I developed an open-source library for traffic flow optimization which you can read about here. I developed policies for traffic control over traffic grids using deep reinforcement learning which is shown to improve traffic conditions. I researched the impact a small percentage of autonomous vehicles running with RL-learned controllers can have on road systems.

ML Intern at Intel May 2017 - August 2018

Drove cloud solutions for cloud service providers Baidu and Salesforce to achieve full data center automation. Analyzed customer data and simulated data to develop trained machine learning models for SSD and DIMM failure prediction in Python, using correlation and Markov models.

Software-Defined Infrastructure at Intel May 2016 - August 2017

Adding features, authoring plugins, debugging issues, opti- mizing for Snap, an open source telemetry framework. Led team in programming a Snap use case from scratch, which is featured at vimeo.com/189179198. Configured VM networking, used API, conducted end-to-end testing. Immersion in layers of the data center stack, including ex- posure to containers, virtualization, scheduling

Technical Intern at Specialized Bicycles June 2015-2016

Wrote an internal web page with JavaScript, HTML, and CSS; used to display customer information for their b2b branch. Wrote scripts to database customer information to be dis- played on said web page

Research

What I do

The research I'm interested in lies in the realm of developing intelligent, ethical systems via machine learning. I currently work in UC Berkeley's Mobile Sensing Lab, a subset of Berkeley Artificial Intelligence Research Lab (BAIR), and am a staff researcher in California Partners for Advanced Transportation Technology (PATH).

Conference Publications

Benchmarks for reinforcement learning in mixed-autonomy traffic. Eugene Vinitsky, Aboudy Kreidieh, Lu Le Flem, Nishant Kheterpal, Kathy Jang, Cathy Wu, Fangyu Wu, Richard Liaw, Eric Liang, Alexandre Bayen. Benchmarks for reinforcement learning in mixed-autonomy traffic. Conference on Robot Learning (CoRL) 2018

Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles. Kathy Jang, Logan Beaver, Behdad Chalaki, Ben Remer, Eugene Vinitsky, Andreas Malikopoulous, Alexandre Bayen. International Conference on Cyber-Physical Systems (ICCPS) 2019.