1. Jun Ma
5235 Fiore Terrace, Apt. 204, San Diego, CA, 92122
Email: junm@mtu.edu
Mobile: 906-370-7748
Web: http://www.cs.mtu.edu/~junm
Professional Preparation
Ph.D. Student in Computer Science August 2009-December 2014
Michigan Technological University, Houghton, MI GPA: 4.0/4.0
Master of Science in Computer Science August 2007-May 2009
Michigan Technological University, Houghton, MI GPA: 4.0/4.0
Bachelor of Science in Computer Science August 2002-July 2006
Xi Dian University, Xi’an, Shaanxi, China GPA: 3.84/4.0
Publications
Refereed Journal Papers:
Chaoli Wang, John P. Reese, Huan Zhang, Jun Tao, Yi Gu, Jun Ma, and Robert J. Nemiroff,
“Similarity-Based Visualization of Large Image Collections”, Information Visualization,
14(3):183-203, Jul 2015.
Jun Ma, Chaoli Wang, Ching-Kuang Shene, and Jingfeng Jiang, “A Graph-Based Interface for
Visual Analytics of 3D Streamlines and Pathlines”, IEEE Transactions on Visualization and
Computer Graphics, 20(8):1127-1140, Aug 2014.
Jun Tao, Jun Ma, Chaoli Wang, and Ching-Kuang Shene, “A Unified Approach to Streamline
Selection and Viewpoint Selection for 3D Flow Visualization”, IEEE Transactions on
Visualization and Computer Graphics, 19(3): 393-406, Mar 2013.
Jun Tao, Jun Ma, Melissa Keranen, Jean Mayo, and Ching-Kuang Shene, “DESvisual: A
Visualization Tool for the DES Cipher”, Journal of Computing Sciences in Colleges, 27(1): 81-
89, 2011.
Refereed Conference Papers:
Man Wang, Jun Tao, Jun Ma, and Chaoli Wang, “A Visualization Tool for Teaching and
Understanding Flow Field Concepts”, Proceedings of IS&T Conference on Visualization and
Data Analysis, San Francisco, CA, Feb 2016.
Can Li, Jun Ma, Jun Tao, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang,
“VIGvisual: A Visualization Tool for the Vigenère Cipher”, Proceedings of ACM Conference on
Innovation and Technology in Computer Science Education, Vilnius, Lithuania, pages 129-134,
Jul 2015.
Jun Ma, Jun Tao, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang,
“SHAvisual: A Visualization Tool for Secure Hash Algorithm”, Proceedings of American
Society for Engineering Education Annual Conference, Seattle, WA, Jun 2015.
Yi Gu, Chaoli Wang, Jun Ma, David L. Kao, and Robert J. Nemiroff, “iGraph: Scalable Visual
Analytics of Big Image and Text Collections”, Proceedings of IS&T/SPIE Conference on
Visualization and Data Analysis, San Francisco, CA, Feb 2015. [Best Paper Award]
Jun Ma, James Walker, Chaoli Wang, Scott A. Kuhl, and Ching-Kuang Shene, “FlowTour: An
Automatic Guide for Exploring Internal Flow Features”, Proceedings of IEEE Pacific
Visualization Symposium, Yokohama, Japan, pages 25-32, Mar 2014.
Jun Tao, Jun Ma, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang,
“RSAvisual: A Visualization Tool for the RSA Cipher”, Proceedings of ACM Technical
Symposium on Computer Science Education, Atlanta, GA, pages 635-640, Mar 2014.
Jun Ma, Chaoli Wang, and Ching-Kuang Shene, “FlowGraph: A Compound Hierarchical Graph
for Flow Field Exploration”, Proceedings of IEEE Pacific Visualization Symposium 2013,
2. Sydney, Australia, pages 233-240, Feb 2013. [Honorable Mention]
Jun Ma, Chaoli Wang, and Ching-Kuang Shene, “Coherent View-Dependent Streamline
Selection for Importance-Driven Flow Visualization”, Proceedings of IS&T/SPIE Conference on
Visualization and Data Analysis 2013, Burlingame, CA, Feb 2013.
Jun Tao, Jun Ma, Melissa Keranen, Jean Mayo, and Ching-Kuang Shene, “ECvisual: A
Visualization Tool for Elliptic Curve Based Ciphers”, Proceedings of ACM Technical
Symposium on Computer Science Education, Raleigh, NC, pages 571-576, Feb 2012.
Papers under revision
Jun Ma, Can Li, Chaoli Wang, and Ching-Kuang Shene, “Moving with the Flow: An Automatic
Tour of Unsteady Flow Fields”.
Jun Ma, Jun Tao, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang,
“AESvisual: A visualization Tool for AES Cipher”.
Presentations
Oral presentation for the paper “Coherent View-Dependent Streamline Selection for Importance-
Driven Flow Visualization”, in IS&T/SPIE Conference on Visualization and Data Analysis 2013,
Burlingame, CA, February 2013.
Presentation for introduction to the GPU and CUDA in the course: “Concurrent Computing” in
2013.
Poster “Streamline Selection and Viewpoint Selection via Information Channel” introduction and
presentation in IEEE VisWeek Visualization Posters 2011, Providence, RI, Oct 2011.
Paper Review Experience
Reviewer of journal IEEE Visualization and Computer Graphics (TVCG) since 2015.
Reviewer of journal Computer & Graphics (CG) since 2015.
Reviewer of journal Flow Control, Measurement & Visualization (FCMV) since 2015.
Reviewer of journal Information Visualization (IV) since 2015.
Reviewer of journal European Journal of Advances in Engineering and Technology (EJAET).
Reviewer of High Performance Computing China (HPC China) 2015.
Sub-reviewer of IEEE Pacific Visualization Symposium (PacificVis) 2013 and 2014.
Reviewer of journal ACM Computing Reviews since 2013.
Sub-reviewer of Annual Conference of the European Association for Computer Graphics
(EuroGraphics) 2013 and 2014.
Sub-reviewer of Eurographics/IEEE VGTC Conference on Visualization (EuroVis) 2014.
Sub-reviewer of ACM SIGGRAPH 2013.
Sub-reviewer of IEEE (Scientific) Visualization Conference (VisWeek) 2012 and 2013.
Reviewer for International Joint Conference on Computer Vision, Imaging and Computer
Graphics Theory and Applications (IVAPP/VISIGRAPP) 2012, 2013 and 2014(subreviewer).
Sub-reviewer of Pacific Conference on Computer Graphics and Applications (PacificGraphics)
2012.
Reviewer of IEEE Visualization and Graphics Technical Committee (VGTC) since 2012.
Reviewed papers (21 totally): 2 in ACM Computing Reviews, 1 in EJAET, 1 in HPC China 2015,
5 in PacificVis 2013/2014, 3 in IVAPP/VISIGRAPP 2012/2013/2014, 2 in EuroGraphics
2013/2014, 1 in EuroVis 2014, 1 in ACM SIGGRAPH 2013, 4 in VisWeek 2012/2013, 1 in
PacificGraphics 2012.
Conference Participation
ACM Special Interest Group on Graphics and Interactive Techniques (SIGGRAPH) 2015, Los
Angeles, CA, August, 2015
3. Invited as a Session Chair in the ACM Special Interest Group on Computer Science Education
(SIGCSE) 2015, Kansas City, MO, March 2015 (absent due to injuring).
IS&T/SPIE Conference on Visualization and Data Analysis 2013, Burlingame, CA, February
2013.
IEEE VisWeek 2011, Providence, RI, Oct 2011.
Awards
Qualcomm Qualstar Diamond Award 2015
Finishing Fellowship in Michigan Technological University (First student in Department of
Computer Science) 2014
President of iPhone Developer Club in Michigan Technological University 2010-2011
Research Assistant Scholarship in Michigan Technological University 2010-2014
Teaching Assistant Scholarship in Michigan Technological University 2007-2010
First Grade Scholarship in Xi Dian University 2005
Two times for Excellent Student Prize in Xi Dian University 2004, 2005
Second Grade Scholarship in Xi Dian University 2004
Memberships
A professional member of Association for Computing Machinery (ACM) 2015-present
A member of Institute of Electrical and Electronics Engineers (IEEE) 2010-present
A member of Upsilon Pi Epsilon (UPE) Association 2008-present
Work Experience Qualcomm Technologies, Inc., San Diego, CA 2015-present
Senior system engineer (researcher) on modern GPU design, development and optimization
Worked on designing and optimizing the next generation GPU using high level modeling
(HLM), a software based GPU architecture simulation framework.
Specifically involved in designing advanced algorithms to optimize the Fixed Function module
of the graphics pipeline in GPU.
Developed a novel visualization system to effectively show the comparison results for a large
number of images and won a Qualstar Diamond Award in the first three months in Qualcomm.
Research Experience Michigan Technological University, Houghton, MI 2010-2014
Generating an automatic tour for exploring internal features of 3D unsteady flow fields
Technique leader of the project and took charge of algorithm design and implementation using
C++ and Qt.
Treated the problem as an energy minimization problem and used the linear system and dynamic
programming to obtain the optimal traversal path.
Designed a CUDA+OpenGL algorithm which allows GPU to directly access and modify the
graphics memory such as vertex buffer object (VBO) without the CPU interruption to support
real-time animation.
Designed a smart out-of-core data loading and merging technique for efficient large-scale data
processing.
Collaborated with a domain expert to verify the effectiveness of the work.
Mentored a junior Ph.D. student.
FlowVisual for understanding 3D flow field on iPad
Built the framework of the project using Objective C and C++.
Implemented the rendering part using GLSL and OPENGL ES.
Mentored a junior Ph.D. student.
4. Cryptography visualization tools development
Individually designed the two cryptography tools (AESvisual and SHAvisual) and involved in
the development of a set of visualization tools (www.cs.mtu.edu/~shene/NSF-4/index.html).
Mentored a junior Ph.D. student.
Conducted several user studies to verify the effectiveness of the tools.
4D FlowGraph to explore the 3D unsteady vector field evolution over time
Technique leader and the sole developer of the project.
Constructed a 2D hierarchical compound graph to encode the relationship between field lines
and the spatiotemporal regions of unsteady (time-varying) flow fields.
Designed GPU high performance computing algorithm to enable real-time user interaction by
considering GPU warp size, bank conflict, on-chip memory usage and streaming processor
(SP) resource balance.
Collaborated with a domain expert to verify the effectiveness of the work.
Similarity-based visualization of large image collections on high-resolution tiled display wall
Built a framework to support high-resolution visualization on a tiled display wall based on the
open source library Chromium.
iGraph, a scalable approach to visual analysis of large image and text collections
Designed a computer cluster framework to effectively visualize and manipulate large image
and text collections using a CPU/GPU hybrid approach based on MPI and GPU high
performance computing.
Proposed a novel resource distribution algorithm for efficiently balancing workload among
nodes in the distributed system.
Designed a distributed rendering system to support the high-resolution rendering on a tiled
display wall using the socket programming (UDP) and advanced GPU rendering techniques
FlowTour: an automatic guide for exploring internal steady flow features
Technique leader and sole developer using C++, OpenGL, CUDA and Qt.
Used the Shannon entropy to define the region importance and the mutual information to
evaluate the viewpoint quality.
Designed a GPU high performance computing algorithm to optimize the performance of GPU
modules and significantly improved the efficiency of system.
FlowGraph, a 2D visual compound hierarchical graph for exploring 3D flow fields
Technique leader and sole developer for algorithm design and implementation.
Proposed a hierarchical compound 2D graph representation for effective 3D flow field
exploration in an occlusion-free manner by mapping 3D streamlines and flow field regions into
graph nodes.
Implemented a force-directed algorithm to arrange the graph layout.
Designed a GPU high performance algorithm to support the real-time user interaction.
Interactive 3D streamline selection and visualization in a view-dependent manner
Technique leader and the sole developer of the project.
Invented a new measurement “streamline shape characteristics” to measure how stereoscopic
streamlines are under different viewpoints.
Defined the streamline intrinsic views under which streamlines can be observed in a least
ambiguous way based on the computed streamline scores under different viewpoints.
A unified information-theoretic framework for streamline and viewpoint selection
5. Technique leader to take charge of algorithm design and implementations using C++, OpenGL,
Qt and CUDA.
Leveraged two interrelated information channels to solve streamline and viewpoint selections
simultaneously.
Leveraged mutual information to measure the importance for streamlines and viewpoints.
Designed a GPU high performance computing algorithm to efficiently process the massive
computation and improved the efficiency over 2000 times over the CPU processing.
GPU-based vector field visualization for big data
Technique leader and the sole developer of the project.
Designed a GPU high performance computing algorithm to accelerate massive computation by
efficiently controlling workload and communication among GPU threads.
Designed an out-of-core memory fetching strategy for loading big data.
Computer Graphics Projects
Developed a program to demonstrate the problems/errors in OpenGL.
Implemented three rendering algorithms “radiosity”, “ray tracing” and “photon mapping”.
Research Fundings
All research work are supported by the following research fundings:
National Science Foundation (NSF) grants including IIS-1017935, IIS-1319363, IIS-1456763,
IIS-1455886, CNS-1229297, DUE-1140512, DUE-1245310. 2011-2014
Michigan Tech REF-RS Grant. 2010-2012
Teaching Assistant Experience Michigan Technological University, Houghton, MI
Grader of CS4421 “Database Systems” and CS3331 “Concurrent Computing”. 2012 spring
Lab teaching assistant of CS1221 “Introduction to Java”. 2009 fall-2010 spring
Grader of CS3311 “Formal Models of Computation” and CS4321 “Introduction to Algorithms”.
2008 spring-2009 spring
Grader of CS3911 “Introduction to Numerical Methods”. 2007 fall