Ph.D., Research Scientist at Facebook
I am a Research Scientist at Facebook. 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 always easy to find time to create new videos.
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 Controversy Search with Contention, Language, and Time
Myungha Jang, Dissertation Proposal, College of Information and Computer Sciences, University of Massachusetts Amherst. May, 2018.
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
Explaining Text Matching on Neural Natural Language Inference
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