Assistant Professor
Computer Science & Engineering
Texas A&M University
Email: hu at cse dot tamu dot edu
Google Scholar Page

Howdy!

I am an Assistant Professor in Computer Science and Engineering at Texas A&M University starting from Fall 2015, and am also a member of the Center for Remote Health Technologies and Systems and the Center for the Study of Digital Libraries. I am currently directing the DATA (Data Analytics at Texas A&M) Lab.

At the DATA Lab, we strive to develop data mining and machine learning algorithms with theoretical properties to better discover actionable patterns from large-scale, networked, dynamic and sparse data. Our research is directly motivated by, and contributes to, applications in social informatics, health informatics and information security. Our work has been featured in Various News Media, such as MIT Tech Review, ACM TechNews, New Scientist, Fast Company, Economic Times. Our research is generously supported by federal agencies such as DARPA and NSF, and industrial sponsors such as Apple, Alibaba and Ingersoll Rand.

[Open Positions] We are recruiting PhD students, undergraduate students, and visiting scholars/students. Here you can find the job description. Please feel free to drop me an email with your CV.

News and Highlights

[08/2018]: I will serve as the Social Networking Chair for the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)
[07/2018]: Grateful to receive an NSF SaTC grant, as the PI, to support our research on adversarial machine learning!
[06/2018]: Grateful to receive a grant from the W.M. Keck Foundation, as the co-PI, to support our research on smart and connected communities!
[06/2018]: Posted the pre-releasedd version of the automated machine learning package Auto-Keras. Check the Preprint here.
[06/2018]: Started serving as associate editor for ACM Transactions on Intelligent Systems and Technology (ACM TIST).
[06/2018]: Released the neural collaborative filtering package by the official TensorFlow team.
[05/2018]: Three papers on Interpretable Machine Learning accepted by KDD 2018. Congratulations Ninghao and Mengnan!
[03/2018]: Grateful to be named as a TEES Young Faculty Fellow!
[02/2018]: Grateful to receive NSF CAREER Award!
[10/2017]: Released the Data & Code of our recent work on data-driven network embedding.
More

Selected Honors and Awards

  • NSF CAREER Award, 2018
  • TEES Young Faculty Fellow, Texas A&M Engineering Experiment Station, 2018
  • Engineering Genesis Award, Texas A&M Engineering Experiment Station, 2017
  • PEPI Award, NSF South BD Hub, 2016
  • Best Paper Award, IJCAI BOOM Workshop, 2016
  • Outstanding Graduate Student Award, Ira A. Fulton Schools of Engineering, Arizona State University, 2015
  • Atluri Award, Phoenix Section Student Scholarship, IEEE Foundation, 2015
  • Faculty Emeriti Fellowship, Arizona State University, 2014
  • President's Award for Innovation, Arizona State University, 2014
  • Best Paper Shortlist, WSDM 2013

Background

I received my PhD from Arizona State University under the supervision of Dr. Huan Liu. I received my Master and Bachelor degrees from Beihang University. Before my current position, I worked as a postdoctoral researcher at Arizona State University and Phoenix Veteran Affairs Health Care System, a research intern at Microsoft Research, and a visiting student at National University of Singapore with Dr. Tat-Seng Chua.