This document provides biographical and professional details about Jun Ma. It outlines his education including a Ph.D. in Computer Science from Michigan Technological University, publications in refereed journals and conferences, experience reviewing papers, conference participation, awards, memberships, and work experience as a Senior System Engineer at Qualcomm Technologies where he designs and optimizes GPU architecture.

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