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Current Teaching Courses
Information Visualization (Spring 2020)
Scientific Visualization (Fall 2019)
Visualization Software
Software Website: Open-source software we developed for visual analytics of urban data: TrajAnalytics, NeighborVis, and GeoVisuals.
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Recent Tutorials and Talks
IEEE VIS Tutorial  on  Urban Trajectory Visualization at IEEE Visualization Conferences, Oct., 2018, Berlin, Germany
ODSC Tutorial  on Population Trajectory Visualization at Open Data Science Conference, Apr., 2019, Boston
IEEE ITSC Workshop  on Urban Data Visualization at IEEE Intelligent Transportation Systems Conferences, Oct., 2019, Auckland, New Zealand
TRB Visualization Talk  on Web-based Visual Analytics of Urban Trajectory Data at International Transportation Symposium, Nov., 2019, Washington DC


Short Bio:

Ye Zhao is a professor in the Department of Computer Science at the Kent State University, Ohio, USA. He has been working on computer graphics and visualization for more than 20 years. His current research projects include visual analytics systems and software, data visualization, deep learning visualization, physically based modeling, and GPU computing, etc. He has published numerous refereed technical papers, many of which are on top-rated venues including IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Intelligent Transportation Systems, and ACM Transactions of Graphics. He has served in many program committees in the field of graphics and visualization including IEEE SciVis and VAST conferences. He has also reviewed hundreds of papers for journals and conferences in graphics, visualization, computational fluid dynamics, image processing, and high performance computing, as well as served in multiple NSF panels. His work has been supported with more than $1.7 million by research grants from NSF, Ohio Board of Agents, etc. Supported by NSF, several open source software has been developed for domain researchers to conduct visual analytics tasks including TrajAnalytics, NeighborVis, and GeoVisuals. Seven doctoral students and many master students have been graduated under his supervision. Four of them received the University Fellowship, the most outstanding scholarship at KSU. His students have been working as professors or entering prestigious companies such as Google, Lockheed Martin, LinkedIn, etc. Ye Zhao received Google Faculty Research Award in 2011.  In 2017, he is awarded as one of the best reviewers of IEEE Transactions on Visualization and Computer Graphics.

Ye Zhao received his PhD degree in computer science from the Stony Brook University, State University of New York in 2006. He held B.S. and M.S. degrees in computer science from the Tsinghua University China in 1997 and 2000.

Research Interests:

Visual Analytics and Information Visualization
    • Visual Analytics for Smart City and Intelligent Transportation   
    • Multi-Type Data Visualization
    • Deep Learning Visualization
    • Visualization Systems and Software
Physically Based Modeling
    • Computational Fluid Flow Simulation
    • Medical Image Processing
    • GPU-based PDE Solver
    • Turbulent Flow Modeling

Recent Funds:

National Science Foundation Grant OAC-1739491, PI, GeoVisuals Software: Capturing, Managing, and Utilizing GeoSpatial Multimedia Data for Collaborative Field Research

National Science Foundation Grant CNS-1637242, PI, S&CC: Support Community-Scale Study by Visual Analytics of Human Mobility and Opinion Data from Social Media Data

National Science Foundation Grant ACI-1535031, PI, TrajAnalytics: A Cloud-Based Visual Analytics Software System to Advance Transportation Studies Using Emerging Urban Trajectory Data.

National Science Foundation Grant IIS-1352927, PI, Visualizing event dynamics with narrative animation.

National Science Foundation Grant IIS-0916131, PI, Real-time simulation system of turbulent fluids.

DOE Brookhaven Science Associates Grant, Subaward PI, Using Visualization for Explainable Machine Learning

DOE Brookhaven Science Associates Grant
, Subaward PI, Full Stack Development for Scientific Data Analysis and Visualization

Ohio Board of Agents (OBR) grant, PI, Visual analytics science and technology of Translational Biomedical Sciences.

Google Faculty Research Awards, Visualizing High Dimensional Categorical Datasets
 

Research Group Members:

David Sheets (PhD Candidate)

Chao Ma (PhD Candidate)

Suphanut Jamonnak (PhD Candidate)

Md Amiruzzaman (PhD Candidate)

Xinyi Huang (PhD Candidate)

Deepshikha Bhadi (PhD Student)

Tsung Heng Wu (MS Student)

Previous Group Members:

Ph.D.:

Shamal Al-Dohuki (Ph.D., 2019), Assistant Professor, University of Duhok, KRG

Dissertation: Interactive Visual Querying and Analysis for Urban Trajectory Data

Farah Kamw (Ph.D., 2019), Assistant Professor, Concordia University Ann Arbor, Michigan

Dissertation: “Utilizing Big Trajectory Data for Urban Visual Analytics and Accessibility Studies

Zhiqiang Wang (Ph.D., 2017), Gamma Technologies Inc., Illinois

Dissertation: “Studying Computational Methods for Biomedical Geometry Extraction and Patient Specific Hemodynamics

Xiaoke Huang (Ph.D., 2016), LinkedIn Inc., California

Dissertation: “Using Graph Modeling in Several Visual Aanalytics Tasks

Fan Chen (Ph.D., 2015), Google Inc., California

Dissertation: “Enhancing Fluid Modeling with Turbulence and Acceleration

Zhi Yuan (Ph.D., 2013), Gamma Technologies Inc., Illinois

Dissertation: Fluid Modeling with Stochastic and Structural Features  

Jamal Alsakran (Ph.D., 2012), Associate Professor, Higher Colleges of Technology, UAE

Dissertation: “Supporting Interactive Visual Analytics for High Dimensional Data Exploration ”

M.S.:

Ding Chu (M.S., 2015), GraphSQL, California

Chao Ma (M.S., 2015), Kent State University (PhD)

Ryan ONeill (M.S., 2014), Georgia Tech Research Institute

Yingyu Wu (M.S., 2014), Ebay Inc.

Lijia Li (M.S., 2014)

Sean Reber (M.S., 2013), Explorys, Ohio

Jackson Cheenath (M.S., 2013), Motorola Solutions, Illinois

Hiroki Morimoto (M.S., 2010), SQUARE ENIX Japan

Aaron Hagan (M.S., 2009), Lockheed Martin, Texas


Last modified on 12/3/2019