Hi, I am Yao Ming (明遥)

ML/NLP Researcher and Practitioner

I am currently working as a research scientist at the AI Group of Bloomberg. I develop machine learning systems with broad applications, including classifications of company, people, and topics for news, tweets, and research documents.

I received my PhD in Computer Science and Engineering at HKUST, where I worked with Prof. Huamin Qu and the VisLab. My thesis focus on visualization and explainable machine learning. I have been awarded the Hong Kong PhD Fellowship Scheme

Prior to HKUST, I received my B.S. in Civil Engineering with a minor in Economics from Tsinghua University in 2016. During my undergraduate, I found my interests in chorus, graphic design, and computer science.

Featured Research

Explainable Machine Learning

1. Interpretable & Explainable Deep Learining
Interpretable and Steerable Sequence Learning via Prototypes
Yao Ming, Panpan Xu, Huamin Qu, Liu Ren.
KDD '19Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019 (Accepted for Oral Presentation).
ProtoSteer: Steering Deep Sequence Model with Prototypes
Yao Ming, Panpan Xu, Furui Cheng, Huamin Qu, Liu Ren.
TVCGIEEE Transactions on Visualization and Computer Graphics, 2019.
Understanding Hidden Memories of Recurrent Neural Networks
Yao Ming, Shaozu Cao, Ruixiang Zhang, Zhen Li, Yuanzhe Chen, Yangqiu Song, Huamin Qu.
VISIEEE Visualization Conference (VAST), 2017.
2. ML Transparency & Explainable Machine Learning
RuleMatrix: Visualizing and Understanding Classifiers using Rules
Yao Ming, Huamin Qu, Enrico Bertini.
TVCGIEEE Transactions on Visualization and Computer Graphics, 2018.
DECE: decision explorer with counterfactual explanations for machine learning models
Furui Cheng, Yao Ming, Huamin Qu.
TVCGIEEE Transactions on Visualization and Computer Graphics, 2020.
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
Qianwen Wang, Yao Ming, Zhihua Jin, Qiaomu Shen, Dongyu Liu, Micah J. Smith, Kalyan Veeramachaneni, Huamin Qu.
CHIProceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2019.
A Survey on Visualization for Explainable Classifier
Yao Ming, Huamin Qu (Supervisor).
ManuascriptVisLab@HKUST, 2017.

Research / Work Experience

Apr 2020 - Present
Senior Research Scientist, AI Group
Bloomberg LPNY
Aug 2016 - Apr 2020
Postdoc Research Associate (2020.02 - 2020.04), PhD Student (2016.08-2019.12)
HKUST-WeChat Joint Lab on AI TechnologyHong Kong
Jun 2019 - Sep 2019
Research Intern (mentor: Dr. Hongxia Yang)
Alibaba Damo AcademyHangzhou, China
Jul 2018 - Dec 2018
Research Intern (mentor: Dr. Panpan Xu)
Robert Bosch LLCSunnyvale, CA
Jan 2018 - Jun 2018
Research Intern (mentor: Prof. Enrico Bertini), VIDA Lab
New York UniversityNY
Mar 2015 - Jul 2015
Research Assistant (mentor: Prof. Yong-Jin Liu), Dept. of Computer Science
Tsinghua UniversityBeijing, China

Honors and Awards

2019Best Short Paper Honorable Mention of IEEE VIS 2019
2019SENG Academic Award for PhD Students
2019KDD Student Travel Award
2018Yelp Dataset Challenge Round 10 Grand Prize Award
2016 - 2020Hong Kong PhD Fellowship (HKPF)
2016Outstanding Graduate of Beijing
2015Nomination of Tsinghua Top Talent Scholarship
2015National Endeavor Scholarship
2015Second Prize in the 1st National Geotechnical Engineering Contest
2014National Scholarship