Myungha Jang

Ph.D., Research Scientist at Facebook Meta


I am a Research Scientist at Facebook Meta. Prior to joining Facebook, I earned my PhD in Computer Science, with a focus in Information Retrieval, from UMass Amherst working with James Allan in the Center for Intelligent Information Retrieval (CIIR). During my PhD, I worked on detecting, modeling, and explaining controversy on the Web. Here is a copy of my CV and Google Scholar.

I occasionally write things in my Korean blog So Dabang. I'm also an asipiring Youtuber, though it's not always easy to find time to create new videos when I get busy with work.

How to pronounce my name: You can think of it as pronouncing [Mee-young-ha] fast. Check out my my tutorial video .

Conference, Workshop and Thesis

  • Probablistic Models for Identifying and Explaining Controversy
    Myungha Jang, Doctoral Dissertation, College of Information and Computer Sciences, University of Massachusetts Amherst. May, 2019.

  • Explaining Controversy on Social Media via Stance Summarization Controversy
    Myungha Jang and James Allan, SIGIR 2018

  • Visualizing Polarity-based Stances of News Websites News IR
    Masaharu Yoshioka, Myungha Jang, James Allan and Noriko Kando, NewsIR Workshop at ECIR 20188

  • Improving Document Clustering by Eliminating Unnatural Language Data Mining
    Myungha Jang, Jinho D. Choi, and James Allan, W-NUT 2017 at EMNLP Dataset and Tool

  • Modeling Controversy Within Populations Controversy
    Myungha Jang , Shiri Dori-Hacohen, and James Allan, ICTIR 2017 Demo and Dataset Slides
  • Probabilistic Approaches to Controversy Detection Controversy
    Myungha Jang , John Foley, Shiri Dori-Hacohen, and James Allan, CIKM 2016
  • Improving Automated Controversy Detection on the Web Controversy  Poster
    Myungha Jang, James Allan, SIGIR 2016.
  • Alleviating the Sparsity in Collaborative Filtering using Crowdsourcing Crowdsourcing
    Jongwuk Lee, Myungha Jang, Dongwon Lee, Won-Seok Hwang, Jiwon Hong, Sang-Wook Kim, CrowdRec 2013
  • Predictive Mining of Comparable Entities on the Web Web mining
    Myungha Jang, Jin-woo Park, Seung-won Hwang, AAAI 2012
  • Toward Automatically Drawn Metabolic Pathway Atlas with Peripheral Node Abstraction Algorithm Bioinformatics
    Myungha Jang, Arang Rhie, Hyun-Seok Park, BIBM 2010
  • Trace of Evolutionary Evidence by Analyzing Clustering Information of Metabolic Pathways in Eukaryotes Bioinformatics
    Arang Rhie, Myungha Jang, Hyun-Seok Park, BIBM 2010
  • A Statistical Analysis of Relation Degree of Compound Pair on Online Biological Pathway Databases Bioinformatics
    Myungha Jang, Arang Rhie, Joyce Jiyoung Whang, Sanduk Yang, Hyun-Seok Park, ACM ICUIMC 2009

  • Journals

  • Explaining Text Matching on Neural Natural Language Inference NLI
    Youngwoo Kim, Myungha Jang, James Allan, ACM Transactions on Information Systems (TOIS), Sep 2020
  • An Interpretation of Biological Metabolites and their Reactions Based on Relation Degree of Compound Pairs in KEGG XML Files Bioinformatics
    Myungha Jang, Joyce Jiyoung Whang, Coleen S. Lewis, and Hyun S. Park, Journal of Software, vol 5:2, pages 187-194, Feb 2010
  • Java DOM parsers to convert KGML into SBML and BioPAX common exchange formats Bioinformatics
    Kyung-Eun Lee, Myungha Jang, Arang Rhie, Chin Ting Thong, San-Duk Yang, Hyun-Seok Park, Genomics & Informatics Vol. 8(2) 94-96, June 2010
  • Parsing KEGG XML Files to Find Shared and Duplicate Compounds Contained in Metabolic Pathway Maps: A Graph-Theoretical Perspective Bioinformatics
    Sung-Hui Kang, Myungha Jang, Joyce Jiyoung Whang, and Hyun-Seok Park, Genomics & Informatics, vol. 6:3, pages 147–152, September 2008