Myungha Jang
Portrait of Myungha Jang

Myungha Jang

Research Engineer at Netflix

Member AI Evals & Understanding · LLM-based user simulation

I’m a Research Engineer at Netflix, where I work on LLM-based user simulation on the Member AI Evals and Understanding team. Previously, I was a Senior Machine Learning Engineer at Pinterest (2023–2025) and a Senior Research Scientist at Meta (2019–2023). I earned my Ph.D. in Computer Science, with a focus on information retrieval, from UMass Amherst under Prof. James Allan in the Center for Intelligent Information Retrieval (CIIR), where I worked on detecting, modeling, and explaining controversy on the Web.

News

  1. I participated as a panelist in the Women in AI Career Workshop 2026 at Ewha Womans University, supported by the Google ExploreCSR Workshop Series.

  2. I gave an invited talk, “Towards AI-enhanced Engineers,” at the Changbal Tech Summit 2025.

  3. I gave a talk on modern recommendation systems at Yonsei University, Sungkyunkwan University (SKKU), and Naver.

  4. I joined Netflix as a Research Engineer on the Member AI Evals and Understanding team, working on LLM-based user simulation.

  5. Our paper “Evidentiality-aware Retrieval for Overcoming Abstractiveness in Open-Domain Question Answering,” a collaboration with the Data & Language Intelligence Lab at Yonsei University, was accepted to Findings of EACL 2024.

Earlier news

  1. I started a new position at Pinterest as a Machine Learning Engineer, working to improve the relevance of related-pins feed recommendations.

  2. I served on a panel on trends in AI research and careers in Silicon Valley at the AIAI 2021 workshop.

  3. I gave invited career talks at Sungshin Women’s University, Ewha Womans University, and Yonsei University.

  4. Our U.S. patent, “Methods for automated controversy detection of content,” was granted (US 10,949,620 B2).

  5. Our paper “Explaining Text Matching on Neural Natural Language Inference” was published in ACM TOIS.

  6. I served on the program committee of the 3rd International Workshop on Mining Actionable Insights from Social Networks (MAISoN) 2019, co-located with ICTIR 2019 in Santa Clara, CA.

  7. I started at Facebook (now Meta).

  8. I successfully defended my Ph.D. thesis, which is available online here.

  9. Our short paper “Explaining Controversy on Social Media via Stance Summarization” was accepted to SIGIR 2018.

Experience

Industry

  1. Jan 2025 – Present

    Senior Research Engineer · Netflix

    Member AI Evals and Understanding. Working on LLM-based user simulation.

  2. Aug 2023 – Jan 2025

    Senior Machine Learning Engineer · Pinterest

    Improved the relevance of related-pins feed recommendations.

    ML Tech Lead, Aug 2024 – Jan 2025.

  3. 2019 – 2023

    Senior Research Scientist · Meta (formerly Facebook)

    Research Scientist 2019–2022, promoted to Senior Research Scientist in 2022.

  4. Jun – Aug 2017

    Machine Learning Software Engineer Intern · Facebook, CA

  5. May – Aug 2015

    Research Intern · IBM T.J. Watson Research Center, NY

    Worked with Kenneth W. Church.

Academia

  1. 2013 – 2019

    Research Assistant · Center for Intelligent Information Retrieval, UMass Amherst

  2. 2011 – 2012

    Research Assistant · Data Intelligence Lab, POSTECH

  3. 2008 – 2010

    Undergraduate Research Intern · Bioinformatics Lab, Ewha Womans University

Selected Publications

A selection of my work. The full list is on Google Scholar.

2024

2021

2020

2019

2018

2017

2016

Education

  1. 2013 – 2019

    Ph.D., Computer Science · University of Massachusetts Amherst

    Advised by Prof. James Allan

  2. 2011 – 2012

    M.S., Computer Science · POSTECH, South Korea

    Advised by Prof. Seung-won Hwang. Early graduation.

  3. 2006 – 2011

    B.S., Computer Science · Ewha Womans University, South Korea

    Graduated Magna Cum Laude.

Beyond work

So Dabang

I occasionally write in my Korean blog.

YouTube

I’m an aspiring YouTuber, though it’s not always easy to find time to make new videos when work gets busy.

How to pronounce my name

Think of it as saying [Mee-young-ha] fast. Here’s my tutorial video.