JIAN HUANG
Ph.D. Ohio State

Professor | EECS
Director | Seelab
University of Tennessee

Co-Founder & CEO
Survature Inc.

Contact Info
Office/Lab: MK 323/534
Tel: 865-974-4398
Fax: 865-974-5483
huangj AT utk.edu

Postal Address
401 MinKao Building
1520 Middle Drive
University of Tennessee
Knoxville, TN37996

About

After earning a PhD in computer science, I started my academic career at the University of Tennessee as an assistant professor in 2001, became an associate professor in 2007 and a full professor in 2013. I co-founded Survature in 2013 based on an invention in behavior data analytics. Survature's data platform helps decision makers see what truly matter in complex human opinions.

My academic research is in the systems area of data analytics and visualization. Recently, focusing on how to deliver data-intensive analytics and visualization to thin front-ends such as laptop, mobile phone, and Hololens. I am also interested in applied research in data science and visual analytics. My research has been funded by NSF, DOE, DOI/NPS, Intel, and NASA. The following are a few examples of our recent research.

Tapestry was first published in 2017 and won best paper award at IEEE LDAV'17. It turns scientific visualization into microservices. From an architectural perspective, Tapestry breaks traditional monolithic pipelines into a novel decoupled pipeline. In result, Tapestry's efficient and transparent use of fine-grained job partitioning, parallelism, and containers, has made it easy to deliver scientific visualization to user-devices as large as the powerwalls and as small as the Hololens and smart phones. In all cases, instantaneously from cloud instances. Furthermore, Tapestry has introduced "scale of audience" as a new quality metric for data-intensive scientific visualization for the first time. Tapestry's github.io page contains live demos, explainer video, and github repo.

An example of our applied research is the GSM Species Mapper. That work’s data science pipeline starts from Discover Life in America’s ATBI inventory, models species presence in the biodiversity hotspot of the Great Smoky Mountains National Park using HPC resources at University of Tennessee, extracts features and creates overlays, and then makes dynamic visualizations of the interactions between the species and the environment available over the Internet. The analytics of the Species Mapper are used for bio-inventory management, education, and public engagement. That project is in close collaboration with Sarah Lowe at University of Tennessee’s School of Art.

Another work of ours started with anonymized records of more than 140,000 past students of University of Tennessee, and led to discoveries of how students actually progress through the university curricula. In many cases, the gaps between the reality and the assumptions made by administrators and faculty are gasping. Those analytics have fundamental implications on advising, student choices, and future curriculum design. For details of the methodology, please refer to our paper “Modeling and Visualizing Student Flow” in IEEE Transactions on Big Data. To see a live demo, please email me.

If you are interested in our work on analytics that revealed inverting roles between mainstream media and social media during the last presidential election, please contact Sally McMillan, Courtney Childers, and Stuart Brotman, at University of Tennessee's School of Advertising and Public Relations and School of Journalism and Electronic Media.

Our research packages released before 2013 are available through the following links: VCB (LGPL license, funded by NSF ACI, CNS and DOE ECPI), SQI (LGPL license, funded by DOE SciDAC and DOE ECPI), BIL (LGPL license, funded by DOE SciDAC), and Eden (BSD license, funded by NSF OCI).

Selected Publications

  1. Mohammad Raji, Alok Hota, Tanner Hobson, and Jian Huang, "Scientific Visualization as a Microservice", IEEE Transactions on Visualization and Computer Graphics, 2018 (accepted, preprint DOI: 10.1109/TVCG.2018.2879672).
  2. Mohammad Raji, John Duggan, Blaise DeCotes, Jian Huang, and Brad Vander Zanden, "Modeling and Visualizing Student Flow", IEEE Transactions on Big Data, 2018 (accepted, preprint DOI: 10.1109/TBDATA.2018.2840986).
  3. Tahir Mahmood, Erik Butler, Nicholas Davis, Jian Huang, Aidong Lu, "Building Multiple Coordinated Spaces for Effective Immersive Analytics through Distributed Cognition", Proc. of Intl. Symp. on Big Data Visual and Immersive Analytics (BDVA’18), Konstanz, Germany, October 2018.
  4. Sally McMillan, Courtney Childers, Stuart Brotman, Jinhee Lee, Natalie Bogda, and Jian Huang, "Political Campaigning Meets Digital Engagement: Old Failures and New Triumphs", Association for Education in Journalism and Mass Communication Annual Conference (AEJMC'18), Washington DC, August 2018.
  5. Mohammad Raji, Alok Hota, and Jian Huang, "Scalable Web-Embedded Volume Rendering", Proc. of IEEE Symp. on Large Data Analysis & Visualization (LDAV'17), pp. 45-54, Phoenix, AZ, October 2017. (LDAV'17 Best Paper Award)
  6. Amy Szczepanski, Troy Baer, Yashema Mack, Jian Huang and Sean Ahern, "Data Analysis and Visualization in High-Performance Computing", IEEE Computer, 46(5), pp. 84-92, 2013. url
  7. Wesley Kendall, Jian Huang and Tom Peterka, "Geometric Quantification of Features in Large Flow Fields", IEEE Computer Graphics and Applications (Special Issue on Extreme Scale Analytics), 32(4), pp. 50-59, 2012. pdf
  8. Wesley Kendall, Jingyuan Wang, Melissa Allen, Tom Peterka, Jian Huang, and David Erickson, "Simplified Parallel Domain Traversal", Proc. of SC'11, pp. 10:1-10:11, November 2011, Seattle, WA. (SC'11 Best Student Paper Award) pdf
  9. Ken Moreland, Wesley Kendall, Tom Peterka, and Jian Huang, "An Image Compositing Solution at Scale", Proc. of SC'11, pp. 25:1-25:10, November 2011, Seattle, WA. pdf
  10. C. Ryan Johnson and Jian Huang, "Distribution Driven Visualization of Volume Data", IEEE Transactions on Visualization and Computer Graphics, 15(5), pp. 734-746, 2009. pdf

Please refer to this page for a complete list of my publications.

Courses and Tutorials

CS360 Systems Programming

Fall 18, Fall 04-07, Spring 08-09, Fall 09-11, 13-17.

CS456 Computer Graphics

Spring 19, Spring 11-12, 14, 16-18.

CS302 Fundamental Algorithms

Spring 03-04.

CS361 Operating System

Spring 12.

CS494/594 Networked Games

Spring 07, Fall 09.

CS594 Visualization & Adv. Computer Graphics

Spring 02.

CS494/594 Computer Graphics

Spring 05-06, Fall 01-03, 08. (became CS456)

HPC for General Data Analysis and Visualization

Notes @ NSF NIMBioS/RDAV Joint Tutorial'11

Multivariate Temporal Features in Scientific Data

Notes @ IEEE VisWeek'09.

Parallel Visualization - An Introduction

Notes @ 09 Peking Univ. Vis Summer School.

Remote Visualization - A Survey

Notes @ 09 Peking Univ. Vis Summer School.

Professional Service

Program Committee, IEEE Visualization Conference, 2008-2010, 2014-2016, 2019-2020

Subject Area Editor, Journal of Computer Science and Technology, 2012-2019

Program Committee, SC Conference, 2013

Proposal Panelist, American Association for Advancement of Science, 2010, 2013

Program Committee, DMESS Workshop, Intl Conf. on Computational Sciences, 2011-2014

Program Committee, IEEE Symp. on Large-Scale Data Analysis & Visualization, 2011

Program Committee, Intl Conference on CAD & Graphics, 2011

Program Committee, IEEE Pacific Visualization Symposium, 2009-2011

Proposal Panelist, DOE Office of Science, 2007, 2009-2011

Proposal Panelist, National Science Foundation, 2008, 2010, 2011

Proposal Reviewer, G8 Research Councils, 2010

Program Committee, Eurographics Symp. on Parallel Graphics & Visualization, 2004, 2006, 2008

Conference Committee, IEEE Visualization Conference, 2005 and 2006

Program Committee, International Workshop on Volume Graphics, 2005

Jian Huang / EECS /UTK / revised 02/2019