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Junzhou Huang

Name

[Huang, Junzhou]
  • Associate Professor

Biography

Junzhou Huang is an Associate Professor in the Computer Science and Engineering department at the University of Texas at Arlington. He received the B.E. degree from Huazhong University of Science and Technology, Wuhan, China, the M.S. degree from the Institute of AutomationChinese Academy of Sciences, Beijing, China, and the Ph.D. degree in Computer Science at Rutgers, The State University of New Jersey. His major research interests include machine learning, computer vision and imaging informatics. He was selected as one of the 10 emerging leaders in multimedia and signal processing by the IBM T.J. Watson Research Center in 2010. His work won the MICCAI Young Scientist Award 2010, the FIMH Best Paper Award 2011, the MICCAI Young Scientist Award Finalist 2011, the STMI Best Paper Award 2012, the NIPS Best Reviewer Award 2013, the MICCAI Best Student Paper Award Finalist 2014 and the MICCAI Best Student Paper Award 2015. He received the NSF CAREER Award in 2016. He enjoys to develop efficient algorithms with nice theoretical guarantees to solve practical problems involved large scale data.

Professional Preparation

    • 2011 PhD in Computer ScienceRutgers University
    • 2003 MS in Pattern RecognitionInstitute of Automation, Chinese Academy of Science
    • 1996 BS in AutomationHuazhong University of Science and Technology

Appointments

    • Sept 2016 to Present Associate Professor
      UT Arlingon
    • Sept 2011 to Aug 2016 Assist Professor
      University of Texas at Arlington

Awards and Honors

    • Aug  2016 NSF CAREER Award sponsored by National Science FoundationNSF
      Achievements:

      NSF CAREER Award, National Science Foundation, 2016. 

    • Oct  2015 Best Student Paper Award sponsored by MICCAI
    • Sep  2014 Best Student Paper Award Finalist sponsored by MICCAI
    • Dec  2013 Best Reviewer Award sponsored by NIPS
    • Oct  2012 Best Paper Award sponsored by STMI
    • Sep  2011 Young Scientist Award Finalist sponsored by MICCAI
    • May  2011 • Best Paper Award sponsored by FIMH
    • Oct  2010 Emerging Leaders in Multimedia and Signal Processing sponsored by IBM Watson
    • Sep  2010 • Young Scientist Award sponsored by MICCAI

News Articles

    • Sept 2016 UTA engineering researcher to develop tools to better analyze complex patient data

      A UTA researcher is developing computing tools that will employ multiple methods of accessing and analyzing very large, complex patient data. This research could ultimately allow scientists and doctors to make better clinical predictions and work toward cures for diseases. The National Science Foundation has awarded a five-year, $535,763 Faculty Early Career Development, or CAREER, grant to Junzhou Huang, an assistant professor in the Computer Science and Engineering Department, to discover a process by which image-omics data can be combined into files that are small enough that current computing technology will allow scientists to better predict how long a patient will live and how best to treat that patient. 

    • Oct 2014 UT-Arlington big data analytics could yield better treatment for pain management

      A University of Texas (UT) at Arlington multidisciplinary team is optimizing and integrating volumes of data in a National Science Foundation research project to help physicians make better, more informed decisions about treating patients' pain.

    • Oct 2014 Data mining for materials made easier? Talk about 21st century gold

      In 2011, President Obama introduced Materials Genome Initiative—a charge to discover, manufacture, and deploy those materials better, faster, and cheaper, thereby advancing and strengthening America’s manufacturing sector and the nation’s economic competitiveness around the globe. But despite a commitment of $250 million and three years of progress, finding the right materials is still a lengthy and expensive process. Would the ability to pinpoint them more easily and accurately enable manufacturers to get their products to market quicker?

      Junzhou Huang, assistant professor of computer science and engineering at the University of Texas at Arlington, thinks so. The National Science Foundation must think so, too, since it awarded Huang a $250,000 grant to help design “scalable algorithms and a computational framework that can search unprecedented volumes of data detailing the complete set of genes present in numerous materials.”

    • Oct 2014 Big data analytics could yield better treatment for pain management

      A UT Arlington multi-disciplinary team is optimizing and integrating volumes of data in a National Science Foundation research project to help physicians make better, more informed decisions about treating patients’ pain. Jay Rosenberger, an associate professor in the Industrial, Manufacturing and Systems Engineering Department, is leading the team, which will work for three years on the $374,998 NSF grant titled: “Statistics-based Optimization Methods for Adaptive Interdisciplinary Pain Management.” The team includes Distinguished Professor Robert Gatchel of Psychology, Professor Mike Manry of Electrical Engineering, Assistant Professor Junzhou Huang of Computer Science & Engineering, and Rosenberger’s IMSE colleagues Professor Victoria Chen and Assistant Professor Li Zeng. 

    • Sept 2014 UT Arlington Scientist Awarded $250,000 Grant To Develop Scalable Genomic Materials Data-Mining Framework

      UT Arlington computer and data scientist Junzhou Huang, an assistant professor at UTA’s Computer Science & Engineering Department, has been awarded a $250,000 National Science Foundation grant to develop a scalable data-mining framework designed help manufacturers quickly discover desired materials for building their products.

      Dr. Huang, who has expertise in the big data and statistical learning fields, will design scalable algorithms and a computational framework that can search unprecedented volumes of data detailing the complete set of genes present in numerous materials. The innovation may aid manufacturers in building better, longer-lasting cell phones, satellites or aircraft parts, he notes in a UTA release. The project is part of the national Materials Genome Initiative, to discover, manufacture and deploy advanced materials faster, more cheaply, and more efficiently than current technology allows.

    • Sept 2014 Genomic data-mining framework will help manufacturers efficiently discover desired materials

      A UT Arlington computer and data scientist has won a $250,000 National Science Foundation grant to develop a scalable data-mining framework that will help manufacturers quickly discover desired materials for building their products. Junzhou Huang, an assistant professor of Computer Science & Engineering with an expertise in big data and statistical learning, will design scalable algorithms and a computational framework that can search unprecedented volumes of data detailing the complete set of genes present in numerous materials. The innovation may aid manufacturers in building better, longer-lasting cell phones, satellites or aircraft parts, Huang said. - See more at: http://www.uta.edu/news/releases/2014/09/junzhouhuang-genome-datamining.php#sthash.Zhlvy9DE.dpuf

Research and Expertise

  • Machine Learning, Computer Vision and Medical Imaging Informatics

    Sparse Learning, Deep Learning, Sparse Imaging, Compressed Sensing, Multi-modal Data Integration, Large Scale Machine Learning

Publications

      Journal Article Published
      • Ruogu Fang, Haodi Jiang, Junzhou Huang, "Tissue-Specific Sparse Deconvolution for Brain CT Perfusion", Computerized Medical Imaging and Graphics, Accepted.

        {Journal Article }
      Published
      • Jinghao Zhou, Zhennan Yan, Giovanni Lasio, Junzhou Huang, Baoshe Zhang, Navesh Sharma, Karl Prado, Warren D’Souza, "Automated Compromised right Lung Segmentation Method Using a Robust Atlas-based Active Volume Model with Sparse Shape Composition Prior in CT", Computerized Medical Imaging and Graphics, Accepted.

        {Journal Article }
      Published
      • Chen Chen, Yeqing Li, Wei Liu and Junzhou Huang, "SIRF: Simultaneous Satellite Image Registration and Fusion in A Unified Framework", IEEE Transactions on Imaging Processing, Accepted.

        {Journal Article }

      Conference Proceeding Published
      • Cheng Deng, Zongting Lv , Wei Liu, Junzhou Huang, Dacheng Tao, Xinbo Gao, "Multi-View Matrix Decomposition: A New Scheme for Exploring Discriminative Information", In Proc. of International Joint Conference on Artificial Intelligence, IJCAI'15, Buenos Aires, Argentina, July 2015.

        {Conference Proceeding }

      Journal Article 2015
      • Lin Zhong, Qingshan Liu, Peng Yang, Junzhou Huang and Dimitris Metaxas, "Learning Multi-scale Active Facial Patches for Expression Analysis", IEEE Transaction on Cybernetics, Volume 45, Number 8, pp.1499-1510, August 2015.

        {Journal Article }
      2015
      • Xi Peng, Junzhou Huang, Qiong Hu, Shaoting Zhang, Ahmed Elgammal and Dimitris Metaxas, "From Circle to 3-Sphere: Head Pose Estimation by Instance Parameterization", Computer Vision and Image Understanding, Volume 136, pp.92-102, July 2015.

        {Journal Article }
      2015
      • Xiang Yu, Shaoting Zhang, Zhenan Yan, Fei Yang, Junzhou Huang, Norah Dunbar, Matthew Jensen, Judee K. Burgoon and Dimitris N. Metaxas, "Is Interactional Dissynchrony a Clue to Deception? Insights from Automated Analysis of Nonverbal Visual Cues", IEEE Transactions on Cybernetics, Volume 45, Issue 3, pp. 506-520, March 2015.

        {Journal Article }

      Conference Proceeding 2015
      • Jiawen Yao, Dheeraj Ganti, Xin Luo, Guanghua Xiao, Yang Xie, Shirley Yan and Junzhou Huang, "Computer-assisted Diagnosis of Lung Cancer Using Quantitative Topology Features", 6th International Workshop on Machine Learning in Medical Imaging, MLMI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Zheng Xu, Junzhou Huang, "Efficient Lung Cancer Cell Detection with Deep Convolution Neural Network", 1st International Workshop on Patch-based Techniques in Medical Imaging, PMI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Hao Pan, Zheng Xu, Junzhou Huang, "An Effective Approach for Robust Lung Cancer Cell Detection", 1st International Workshop on Patch-based Techniques in Medical Imaging, PMI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Ruoyu Li, Junzhou Huang, "Fast Regions-of-Interest Detection in Whole Slide Histopathology Images", 1st International Workshop on Patch-based Techniques in Medical Imaging, PMI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Ruogu Fang, Ming Ni, Junzhou Huang, Qianmu Li, Tao Li, "A Efficient 4D Non-Local Tensor Total-Variation for Low-Dose CT Perfusion Deconvolution", MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, MCV'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Zheng Xu, Yeqing Li, Leon Axel, Junzhou Huang, "Efficient Preconditioning in Joint Total Variation Regularized Parallel MRI Reconstruction", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Ruoyu Li, Yeqing Li, Ruogu Fang, Shaoting Zhang, Hao Pan, Junzhou Huang, "Fast Preconditioning for Accelerated Multi-Contrast MRI Reconstruction", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Menglin Jiang, Shaoting Zhang, Junzhou Huang, Dimitris Metaxas, "Joint Kernel-Based Supervised Hashing for Scalable Histopathological Image Analysis", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Jiawen Yao, Zheng Xu, Xiaolei Huang, Junzhou Huang, "Accelerated Dynamic MRI Reconstruction with Total Variation and Nuclear Norm Regularization", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015.

        {Conference Proceeding }
      2015
      • Yeqing Li*, Chen Chen*, Fei Yang and Junzhou Huang, "Deep Sparse Representation for Robust Image Registration", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'15, Boston, USA, June 2015.

        {Conference Proceeding }
      2015
      • Ruogu Fang, Junzhou Huang, Wen-Ming Luh, "A Spatio-Temporal Low-rank Total Variation Approach for Denoising Arterial Spin Labeling MRI Data", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'15, Brooklyn Bridge, NY, USA, April 2015.

        {Conference Proceeding }
      2015
      • Chen Chen, Venkaiah Chowdary Kavuri, Xinlong Wang, Ruoyu Li, Hanli Liu, Junzhou Huang, "Multi-frequency di use optical tomography for cancer detection", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'15, Brooklyn Bridge, NY, USA, April 2015.

        {Conference Proceeding }
      2015
      • Yeqing Li, Chen Chen, Jinghao Zhou, Junzhou Huang, "Robust Image Registration in the Gradient Domain", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'15, Brooklyn Bridge, NY, USA, April 2015.

        {Conference Proceeding }
      2015
      • Xi Peng, Junzhou Huang, Qiong Hu, Shaoting Zhang, Dimitris Metaxas, "Three-Dimensional Head Pose Estimation in-the-Wild", InProc. the 11th IEEE International Conference on Automatic Face and Gesture Recognition, FG'15, Ljubljana, Slovenia, May 2015.

        {Conference Proceeding }
      2015

      Conference Proceeding 2013
      • Xiang Yu, Shaoting Zhang, Zhennan Yan, Fei Yang, Junzhou Huang, Norah Dunbar, Matthew Jensen, Judee K. Burgoon and Dimitris N. Metaxas, "Is Interactional Dissynchrony a Clue to Deception: Insights from Automated Analysis of Nonverbal Visual Cues", In Proc. of the 46th Hawaii International Conference on System Sciences, HICSS'13, Wailea, HI, USA, January 2013.
        {Conference Proceeding }
      2013
      • Xiang Yu, Fei Yang, Junzhou Huang and Dimitris Metaxas, "Explicit Occlusion Detection based Deformable Fitting for Facial Landmark Localization", In Proc. of the IEEE International Conference on Automatic Face and Gesture Recognition, FG'13, Shanghai, China, April 2013
        {Conference Proceeding }
      2013
      • Lin Zhong, Shaoting Zhang, Mingchen Gao, Junzhou Huang, Zhen Qian, Dimitris Metaxas and Leon Axel, "Papillary Muscles Analysis from High Resolution CT using Spatial-Temporal Skeleton Extraction", In Proc. of the IEEE International Symposium on Biomedical Imaging, ISBI'13, San Francisco, CA, USA, April 2013
        {Conference Proceeding }
      2013
      • Yang Yu, Shaoting Zhang, Junzhou Huang, Dimitris Metaxas and Leon Axel, "Sparse Deformable Models with Application to Cardiac Motion Analysis", In Proc. of the 23rd biennial International Conference on Information Processing in Medical Imaging, IPMI'13, Asilomar, CA, June 2013.
        {Conference Proceeding }
      2013 2013 2013 2013

      Journal Article 2013
      • Shaoting Zhang, Yiqiang Zhan, Xinyi Cui, Mingchen Gao, Junzhou Huang, Dimitris Metaxas, "3D Anatomical Shape Atlas Construction using Mesh Quality Preserved Deformable Models",  Computer Vision and Image Understanding, Volume 117, Issue 9, pp. 1061-1071, September 2013.

        {Journal Article }
      2013
      • Baiyang Liu, Junzhou Huang, Casimir Kulikowski, Lin Yang, “Robust Visual Tracking Using Local Sparse Appearance Model and K-Selection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 35, Issue 12, pp. 2968-2981, December 2013.

        {Journal Article }

      Conference Proceeding 2012
      • Xinyi Cui, Shaoting Zhang, Yiqiang Zhan, Mingchen Gao, Junzhou Huang and Dimitris Metaxas, "3D Anatomical Shape Atlas Construction using Mesh Quality Preserved Deformable Models", In MICCAI Workshop on Mesh Processing in Medical Image Analysis, MeshMed'12, Nice, France, October 2012.
        {Conference Proceeding }
      2012
      • Yang Yu, Shaoting Zhang, Junzhou Huang and Dimitris Metaxas and Leon Axel, "Sparse Deformable Models with Applications to Mouse LV Motion Analysis using Tagged MRI", In MICCAI Workshop on Sparsity Techniques in Medical Imaging, STMI'12, Nice, France, October 2012.
        {Conference Proceeding }
      2012
      • Chen Chen, Junzhou Huang and Leon Axel, "Accelerated Parallel Magnetic Resonance Imaging with Joint Gradient and Wavelet Sparsity", In MICCAI Workshop onSparsity Techniques in Medical Imaging, STMI'12, Nice, France, October 2012
        {Conference Proceeding }
      2012
      • Chen Chen, Junzhou Huang, "The Benet of Tree Sparsity in Accelerated MRI", In MICCAI Workshop on Sparsity Techniques in Medical Imaging, STMI'12, Nice, France, October 2012.
        {Conference Proceeding }
      2012
      • Xinyi Cui, Shaoting Zhang, Junzhou Huang, Xiaolei Huang and Dimitris Metaxas, Leon Axel, “Left Endocardium Segmentation using Spatio-temporal Metamorphs”. In Proc. of the IEEE International Symposium on Biomedical Imaging, ISBI’12, Barcelona, Spain, May 2012.
        {Conference Proceeding }
      2012
      • Junzhou Huang and Fei Yang, “Compressed Magnetic Resonace Imaging Based on Wavelet Sparsity and Nonlocal Total Variation”. In Proc. of the IEEE International Symposium on Biomedical Imaging, ISBI’12, Barcelona, Spain, May 2012.
        {Conference Proceeding }
      2012
      • Lin Zhong, Qingshan Liu, Peng Yang, Bo Liu, Junzhou Huang and Dimitris Metaxas, “Learning Active Facial Patches for Expression Analysis”. In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR’12, Providence, Rhode Island, USA, June 2011.
        {Conference Proceeding }
      2012
      • Fei Yang, Xiang Yu, Junzhou Huang, Peng Yang, Dimitris Metaxas, “Robust Eyelid Tracking for Fatigue Detection”, IEEE International Conference on Image Processing, ICIP’12, Orlando, Florida, USA, September 2012.
        {Conference Proceeding }
      2012
      • Fei Yang, Junzhou Huang, Xiang Yu, Dimitris Metaxas, “Robust Face Tracking with a Consumer Depth Camera”, IEEE International Conference on Image Processing, ICIP’12, Orlando, Florida, USA, September 2012.
        {Conference Proceeding }
      2012
      • Xinyi Cui, Junzhou Huang, Shaoting Zhang and Dimitris Metaxas, “Background Subtraction using Group Sparsity and Low Rank Constraint”, In Proc. of the 12th European Conference on Computer Vision, ECCV’12, Firenze, Italy, October 2012.
        {Conference Proceeding }
      2012
      • Mingchen Gao, Junzhou Huang, Xiaolei Huang, Shaoting Zhang, Dimitris Metaxas, “Simplified Labeling Process for Medical Image Segmentation”, In Proc. of the 15th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI’12, Nice, France, October 2012.
        {Conference Proceeding }
      2012
      • Junzhou Huang, Chen Chen, Leon Axel, “Fast Multi-contrast MRI Reconstruction”, In Proc. of the 15th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI’12, Nice, France, October 2012.
        {Conference Proceeding }
      2012
      • Chen Chen, Junzhou Huang, "Compressive Sensing MRI with Wavelet Tree Sparsity", In Proc. of the 26th Annual Conference on Neural Information Processing Systems, NIPS'12, Lake Tahoe, Nevada, USA, December 2012.
        {Conference Proceeding }

      Journal Article 2012
      • Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang, Dimitris Metaxas and Xiang Zhou, "Towards Robust and Effective Shape Modeling: Sparse Shape Composition",  Medical Image Analysis, Volume 16, Issue 1, pp. 265-277, January 2012.
        {Journal Article }
      2012
      • Shaoting Zhang, Junzhou Huang, Hongsheng Li and Dimitris Metaxas, “Automatic Image Annotation and Retrieval Using Group Sparsity”. IEEE Transactions on Systems, Man, and Cybernetics: Part B. Volume 42, Issue 3, pp. 838-849, 2012.
        {Journal Article }

      Conference Proceeding 2011
      • Fei Yang, Junzhou Huang, Peng Yang, Dimitris Metaxas, "Eye Localization through Multiscale Sparse Dictionaries", In Proc. the 9th Conference on Automatic Face and Gesture Recognition, FG' 11, Santa Barbara, California, USA, March 2011.
        {Conference Proceeding }
      2011
      • Baiyang Liu, Junzhou Huang, Casimir Kulikowski, Lin Yang, "Robust Tracking Using Local Sparse Appearance Model and K-Selection", In Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, CVPR'11, Colorado Springs, Colorado, USA, June, 2011. Oral presentation.
        {Conference Proceeding }
      2011
      • Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang, Dimitris Metaxas and Xiang Zhou, "Sparse Shape Composition: A New Framework for Shape Prior Modeling", In Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, CVPR'11, Colorado Springs, Colorado, USA, June, 2011.
        {Conference Proceeding }
      2011
      • Mingchen Gao, Junzhou Huang, Shaoting Zhang, Zhen Qian, Szilard Voros, Dimitri Metaxas, Leon Axel, "4D Cardiac Reconstruction Using High Resolution CT Images", The Sixth International Conference on Functional Imaging and Modeling of the Heart, FIMH'11, New York, USA, May 2011. Oral presentation. Best Paper Award.
        {Conference Proceeding }
      2011
      • Hongsheng Li, Junzhou Huang, Shaoting Zhang, and Xiaolei Huang, "Optimal Object Matching via Convexification and Composition", accepted by 13th International Conference on Computer Vision, ICCV'11, Barcelona, Spain, November 6-13, 2011.
        {Conference Proceeding }
      2011
      • Tian Shen, Xiaoleo Huang, Hongsheng Li, Edward Kim, Shaoting Zhang, and Junzhou Huang, "A 3D Laplacian-Driven Parametric Deformable Model", accepted by 13th International Conference on Computer Vision, ICCV'11, Barcelona, Spain, November 6-13, 2011.
        {Conference Proceeding }
      2011
      • Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang, Dimitris Metaxas and Xiang Zhou, "Deformable Segmentation via Sparse Shape Composition: Towards the Robustness to Weak Appearance Cues", accepted by 14th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'11, Toronto, Canada, September 18-22, 2011. Runner Up for MICCAI Young Scientist Award.
        {Conference Proceeding }
      2011
      • Shaoting Zhang, Junzhou Huang, Mustafa Uzunbas, Tian Shen, Foteini Delis, Xiaolei Huang, Nora Volkow, Panayotis Thanos and Dimitris N. Metaxas, "3D Segmentation of Rodent Brain Structures Using Hierarchical Shape Priors and Deformable Models", accepted by 14th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'11, Toronto, Canada, September 18-22, 2011.
        {Conference Proceeding }
      2011
      • Shaoting Zhang, Mustafa Uzunbas, Zhennan Yan, Mingchen Gao, Junzhou Huang, Dimitri Metaxas, Leon Axel, "Construction of Left Ventricle 3D Shape Atlas from Cardiac MRI", The Sixth International Conference on Functional Imaging and Modeling of the Heart, FIMH'11, New York, USA, May 2011.
        {Conference Proceeding }
      2011
      • Yang Yu, Junzhou Huang, Shaoting Zhang, Christophe Restif, Xiaolei Huang, Dimitris Metaxas, "Group Sparsity Based Classification for Cervigram Segmentation", In IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro, ISBI’11, Chicago, Illinois, USA, March 2011.
        {Conference Proceeding }
      2011
      • Shaoting Zhang, Junzhou Huang, Mustafa Uzunbas, Tian Shen, Foteini Delis, Xiaolei Huang, Nora Volkow, Panayotis Thanos, Dimitris Metaxas, "3D Segmentation of Rodent Brain Structures Using Active Volume Model With Shape Priors", In IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro, ISBI’11, Chicago, Illinois, USA, March 2011. Oral presentation.
        {Conference Proceeding }
      2011
      • Fei Yang, Junzhou Huang, Dimitris Metaxas, "Sparse Shape Registration for Occluded Facial Feature Localization", In Proc. of the 9th Conference on Automatic Face and Gesture Recognition, FG'11, Santa Barbara, California, USA, March 2011.
        {Conference Proceeding }
      2011

      Journal Article 2011
      • Junzhou Huang, Shaoting Zhang, Hongsheng Li, Dimitris Metaxas, ”Composite Splitting Algorithms for Convex Optimization”, Computer Vision and Image Understanding,Volume 115, Issue 12, page 1610-1622, December 2011.
        {Journal Article }
      2011
      • Junzhou Huang, Shaoting Zhang, Dimitris Metaxas, ”Efficient MR Image Reconstruction for Compressed MR Imaging”, Medical Image Analysis, Volume 15, Issue 5, pp. 670-679, October 2011.
        {Journal Article }
      2011
      • Shaoting Zhang, Junzhou Huang and Dimitris Metaxas, "Robust Mesh Editing Using Laplacian Coordinates", Graphical Models, Volume 73, Issue 1, pp.10-19, January, 2011.
        {Journal Article }
      2011
      • Junzhou Huang, Tong Zhang and Dimitris Metaxas, “Learning with Structured Sparsity”, Journal of Machine Learning Research, Volume 12, pp.3371-3412, 2011.
        {Journal Article }

      Conference Proceeding 2010
      • Shaoting Zhang, Junzhou Huang,Yuchi Huang, Yang Yu, Hongsheng Li, Dimitris Metaxas, "Automatic Image Annotation Using Group Sparsity", In Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, CVPR'10, San Francisco, USA, June 2010. Oral presentation.
        {Conference Proceeding }
      2010
      • Baiyang Liu, Lin Yang, Junzhou Huang, Peter Meer, Leiguang Gong, Casimir Kulikowski, ”Robust and Fast Collaborative Tracking with Two Stage Sparse Optimization”, In Proc. of the 11th European Conference on Computer Vision, ECCV'10, Crete, Greece, September, 2010.
        {Conference Proceeding }
      2010
      • Shaoting Zhang, Junzhou Huang, Wei Wang, Xiaolei Huang, Dimitris Metaxas, "Discriminative Sparse Representations for Cervigram Image Segmentation", IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro, ISBI'10, Rotterdam, Netherlands, April, 2010.
        {Conference Proceeding }
      2010
      • Junzhou Huang, Shaoting Zhang and Dimitris Metaxas. " Efficient MR Image Reconstruction for Compressed MR Imaging ", In Proc. of the 13th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'10, Beijing, China, 2010. Oral presentation. MICCAI Young Scientist Award.
        {Conference Proceeding }
      2010
      • Junzhou Huang, Shaoting Zhang and Dimitris Metaxas. " Fast Optimization for Mixture Prior Models ", In Proc. of the 11th European Conference on Computer Vision, ECCV'10, Crete, Greece, September, 2010.
        {Conference Proceeding }
      2010
      • Shaoting Zhang, Junzhou Huang, Wei Wang, Xiaolei Huang, Dimitris Metaxas, "Cervigram Image Segmentation Based on Reconstructive Sparse Representations", Proc. of SPIE, Medical Imaging: Image Processing, San Diego, USA, February, 2010. Oral presentation.
        {Conference Proceeding }

      Journal Article 2010
      • Junzhou Huang and Tong Zhang. "The Benefit of Group Sparsity", Annals of Statistics, Volume 38, Number 4 (2010), 1978-2004.
        {Journal Article }

      Conference Proceeding 2009
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, "Learning with Dynamic Group Sparsity", The 12th International Conference on Computer Vision, ICCV'09, Kyoto, Japan, October 2009. Oral presentation.
        {Conference Proceeding }
      2009
      • Junzhou Huang, Tong Zhang, Dimitris Metaxas, "Learning with Structured Sparsity", The 26th International Conference on Machine Learning, ICML'09, Montreal, Quebec, Canada, June, 2009. Oral presentation.
        {Conference Proceeding }

      Conference Proceeding 2008
      • Tian Shen, Yaoyao Zhu, Xiaolei Huang, Junzhou Huang, Dimitris Metaxas, Leon Axel, "Active Volume Models with Probabilistic Object Boundary Prediction Module", In Proc. of the 11th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'08, LNCS-5241, pp. 331-341, 2008.
        {Conference Proceeding }
      2008
      • Junzhou Huang, Zhen Qian, Xiaolei Huang, Dimitris Metaxas, Leon Axel, "Tag Separation in Cardiac Tagged MRI", In Proc. of the 11th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'08, LNCS-5242, pp. 289-297, 2008.
        {Conference Proceeding }
      2008
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, "Simultaneous Image Transformation and Sparse Representation Recovery", In Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, CVPR'08, pp. 1-8, 2008.
        {Conference Proceeding }

      Conference Proceeding 2007
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Leon Axel, "Dynamic Texture Based Heart Location and Segmentation in 4-D Cardiac Images" , IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'07, pp. 852-855, 2007.
        {Conference Proceeding }
      2007
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, and Leon Axel, "Adaptive Metamorphs Model for 3D Medical Image Segmentation", In Proc. of the 10th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'07, pp. 302-310, 2007.
        {Conference Proceeding }
      2007
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, "Optimization and Learning for Registration of Moving Dynamic Textures", In 11th International Conference on Computer Vision, ICCV'07, pp. 1-8, 2007. Oral presentation.
        {Conference Proceeding }

      Conference Proceeding 2006
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Debarata Banerjee, "3D Tumor Shape Reconstruction from 2D Bioluminescence Images" , IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'06, pp. 606-609, 2006. Oral presentation.
        {Conference Proceeding }
      2006
      • Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Debarata Banerjee, "3D Tumor Shape Reconstruction from 2D Bioluminescence Images and Registration with CT Images", 1st Workshop on Microscopic Image Analysis with Applications in Biology, MIAAB'06, 2006. Oral presentation.
        {Conference Proceeding }

      Journal Article 2005
      • Junzhou Huang, Tieniu Tan, Li Ma, Yunhong Wang, "Phase Correlation Based Iris Image Registration Model", Journal of Computer Science and Technology, Vol. 20, No. 2, pp. 419-425, March 2005.
        {Journal Article }

      Conference Proceeding 2004
      • Junzhou Huang, Li Ma, and Yunhong Wang and Tieniu Tan, "Iris Recognition Based on Local Orientation Description", Asian Conference on Computer Vision, ACCV'04, pp. 954-959, Korea, 2004.
        {Conference Proceeding }
      2004
      • Jiali Cui, Yunhong Wang, Junzhou Huang, Tieniu Tan, Zenan Sun, "An Iris Image Synthesis Method Based on PCA and Super-Resolution", 17th International Conference on Pattern Recognition, ICPR'04 (4), pp. 471-474, 2004.
        {Conference Proceeding }
      2004
      • Junzhou Huang, Yunhong Wang, Tieniu Tan, Jiali Cui, "A New Iris Segmentation Method for Recognition", 17th International Conference on Pattern Recognition, ICPR'04 (3), pp. 554-557, 2004.
        {Conference Proceeding }
      2004
      • Junzhou Huang, Yunhong Wang, Jiali Cui, Tieniu Tan, "Noise Removal and Impainting Model for Iris Image", International Conference on Image Processing, ICIP'04, pp. 869-872, 2004.
        {Conference Proceeding }

      Conference Proceeding 2003
      • Junzhou Huang, Li Ma, Tieniu Tan and Yunhong Wang, "Learning-based Resolution Enhancement of Iris Images", 14th British Machine Vision Conference, BMVC'03, pp. 153-162, Norwich, U.K., 2003.
        {Conference Proceeding }

Presentations

    • June  2016
      Biomarker Discovery from Histopathology Images for Clinical Outcome Prediction

       Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland, USA, June 2016. 

    • June  2016
      Multi-modal Biomarker Discovery from Imaging Genomic Data

      School of Medicine, University of Maryland, Baltimore, USA, June 2016.

    • January  2016
      Integration of Pathological Images and Cell Profiling Data for Clinical Outcome Prediction

      National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA, January 2016. 

    • November  2015
      Big Image-Omics Data Analytics for Clinical Outcome Prediction

      Department of Clinical Science, University of Texas Southwestern Medical Center, Dallas, TX, USA, November 2015. 

    • September  2014
      Recent Algorithm Development in Diffusion Optical Imaging

      Department of Bioengineering, University of Texas at Arlington, TX, USA, September 2014.

    • June  2014
      Preconditioning for Accelerated Iteratively Reweighted Least Squares in Structured Sparsity Reconstruction

      IEEE Conference on Computer Vision and Pattern Recognition, Columbus, Ohio, USA, June 2014.

    • May  2014
      Multichannel Compressed Sensing with Forest Sparsity

      SIAM Conference on Optimization, San Diego, CA, USA, May 2014.

    • March  2014
      O(1) Algorithms for Overlapping Group Sparsity

      INFORMS Optimization Society Conference, Houston, TX, USA, March 2014.

    • March  2013
      Low-frequency Energy Disaggregation

      Samsung Research America, Dallas, TX, USA, March 2013.

    • August  2012
      Biomedical Imaging and Learning: When Statistical Learning Met Bio-Applications

      Department of Bioengineering, University of Texas at Arlington, TX, USA, August 2012

    • May  2012
      Fast Composite Splitting Algorithm for Linear Composite Regularization

      SIAM Conference on Imaging Science, Philadelphia, PA, USA, May 2012.

    • April  2012
      Structured Sparsity: When Statistical Learning Met Signal Processing

      Department of Electrical Engineering, University of Texas at Arlington, TX, USA, April 2012.

    • August  2011
      Sparsity and Deformable Models for Improved Medical Imaging and Diagnosis
       SPIE on Wavelets and Sparsity XIV, San Diego, CA, USA.
    • April  2011
      Sparsity Techniques and Their Applications
      NAVTEQ, Chicago, IL, USA.
    • March  2011
      Sparsity: From Theory to Applications in Machine Learning and Medical Imaging
      Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA.
    • March  2011
      Structured Sparsity and Its Applications on Medical Imaging and Machine Vision

      Department of Computer Science and Engineering, University of Texas at Arlington, TX, USA, March 2011.

    • October  2010
      Structured Sparsity and Its Applications
      6th Annual Watson Workshop Emerging Leaders in Multimedia and Signal Processing, Hawthorne NY, USA.
    • September  2010
      Efficient MR Image Reconstruction for Compressed MR Imaging
      13th Annual International Conference on Medical Image Computing and Computer Assisted Intervention,
      MICCAI’10, Beijing, China.
    • September  2010
      Structure Sparsity for Dynamic Data Analysis

      ExxonMobil Corporate Strategic Research, Clinton, NJ, USA, September 2010.

    • August  2010
      Structured Sparsity and Its Applications on Biomedical Imaging Computer Vision

      Siemens Corporate Research, Princeton, NJ, USA, August 2010. 

    • August  2010
      Sparse Learning for Biomedical Imaging and Informatics

      Siemens Medical Solutions, Malvern, PA, USA, August 2010.

    • November  2009
      Sparse Learning and Beyonds

      Institute of Computing Technology, Chinese Academy of Science, Beijing, China, November 2009.

    • October  2009
      Learning With Dynamic Group Sparsity

      International Conference on Computer Vision, ICCV’09, Kyoto, Japan.

    • June  2009
      Learning With Structure Sparsity

      International Conference on Machine Learning, ICML’09, Montreal, Canada.

    • October  2007
      Optimization and Learning for Registration of Moving Dynamic Textures

      International Conference on Computer Vision, ICCV’07, Rio de Janeiro, Brazil, October 2007.

    • March  2006
      3D Tumor Shape Reconstruction from 2D Bioluminescence Images

      IEEE Int’l Symposium on Biomedical Imaging: From Nano to Macro, ISBI’06, Washington, USA, April 2006.

  • Past
    •  
      Big Image-Omics Data Analytics for Clinical Outcome Prediction

      Department of Clinical Science, University of Texas Southwestern Medical Center, Dallas, TX, USA, November 2015.

Support & Funding

This data is entered manually by the author of the profile and may duplicate data in the Sponsored Projects section.
    • Aug 2016 to Present CAREER: Large Scale Learning for Complex Image-Omics Data Analytics sponsored by  - $535763
    • June 2016 to Present A Materials Genome Approach to Novel Environment-Friendly Magnets sponsored by  - $15000
    • Sept 2014 to Present Gift Research Grant on Digital Map Data sponsored by  - $50000
    • Sept 2014 to Present Algorithm Development for Big Image Data sponsored by  - $136058
    • Sept 2014 to Aug 2017 CI-P: Planning for SMART-MOVE: A Spatiotemporal Annotated Human Activity Repository for Advanced Motion Recognition and Analysis Research sponsored by  - $116000
    • Sept 2014 to Aug 2017 CMMI:Statistics-based Optimization Methods for Adaptive Interdisciplinary Pain Management sponsored by  - $374998
    • Aug 2014 to Aug 2017 III: Small:Robust Materials Genome Data Mining Framework for Prediction and Guidance of Nanoparticle Synthesis sponsored by  - $250000
    • Aug 2012 to Aug 2015 GAANN - Educating Health Informatics Researchers at the Computer Science and Engineering Department of the University of Texas at Arlington sponsored by  - $533064
    • May 2012 to Apr 2013 Structured Sparsity Based Compressive Sensing for Rapid Magnetic Resonance Imaging sponsored by  - $10000
    • July 2013 to June 2014 Machine Learning Algorithm Development for Non-intrusive Load Monitoring sponsored by  - $149998

Students Supervised

  • Doctoral
    • Present
    • Present
    • Present
    • Present
    • Sept 2015
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      http://cseweb.uta.edu/~yeqing/

  • Master's
    • Present
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    • Present
    • Present
    • Present
    • Jan 2015
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Courses

      • CSE 6392-001 Scalable Searching and Optimization

        This course will provide an overview of the current state-of-the-art of big data searching techniques in computer vision, machine learning and data mingearning by studying a set of cutting-edge advanced topics in these areas. Several selected research topics reflect the current state in these fields. The main objective of this course is to review cutting-edge searching& learning research in big data through lectures covering the underlying statistical & mathematical concepts and representative algorithms, paper reading, and implementation. The instructor will work with students on building ideas, performing experiments, and writing papers. Students can decide to submit his/her results to a learning/mining/vision related conference, or just play with funs.

        The course is application-driven and includes advacnced topics in imaging, learning and vision, such as different imaging techniques and advanced learning tools in different applications. It will also include selected topics relating to the emerging compressed sensing and sparse learning theory and techniques. The course will provide the participants with a thorough background in current research in these areas, as well as to promote greater awareness and interaction between multiple research groups within the university. The course material is well suited for students in computer science, computer engineering, electrical engineering and biomedical engineering.

        Spring - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours
      • CSE 5311-001 DESIGN AND ANALYSIS OF ALGORITHMS

        This course provides an overview of the Design and Analysis of Algorithms. Computer algorithms is at the heart of computer sciences. Algorithms are used everywhere, from operating systems to databases, to solving a variety of optimization problems. This course will cover all major areas of algorithms: sorting algorithms, greedy algorithms, graph algorithms, dynamical programming, maximum flow problems, string matching algorithms, geometric algorithms, and randomized algorithms. Besides above traditional algorithms, several state-of-art practical algorithms will be covered. Major ideas are introduced through examples and historical perspectives, so that students will have a grasp on the evolution and development of algorithms. Class projects are required to practice the algorithms learned in the class. After completing this course, students will have the ability to independently investigate a computational problem, design a practical algorithm to solve it and analyze the performance of the algorithm.

        Fall - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 5311-002 DESIGN AND ANALYSIS OF ALGORITHMS

        This course provides an overview of the Design and Analysis of Algorithms. Computer algorithms is at the heart of computer sciences. Algorithms are used everywhere, from operating systems to databases, to solving a variety of optimization problems. This course will cover all major areas of algorithms: sorting algorithms, greedy algorithms, graph algorithms, dynamical programming, maximum flow problems, string matching algorithms, geometric algorithms, and randomized algorithms. Besides above traditional algorithms, several state-of-art practical algorithms will be covered. Major ideas are introduced through examples and historical perspectives, so that students will have a grasp on the evolution and development of algorithms. Class projects are required to practice the algorithms learned in the class. After completing this course, students will have the ability to independently investigate a computational problem, design a practical algorithm to solve it and analyze the performance of the algorithm.

        Fall - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 5311-003 DESIGN AND ANALYSIS OF ALGORITHMS

        This course provides an overview of the Design and Analysis of Algorithms. Computer algorithms is at the heart of computer sciences. Algorithms are used everywhere, from operating systems to databases, to solving a variety of optimization problems. This course will cover all major areas of algorithms: sorting algorithms, greedy algorithms, graph algorithms, dynamical programming, maximum flow problems, string matching algorithms, geometric algorithms, and randomized algorithms. Besides above traditional algorithms, several state-of-art practical algorithms will be covered. Major ideas are introduced through examples and historical perspectives, so that students will have a grasp on the evolution and development of algorithms. Class projects are required to practice the algorithms learned in the class. After completing this course, students will have the ability to independently investigate a computational problem, design a practical algorithm to solve it and analyze the performance of the algorithm.

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 6392-001 Scalable Searching and Optimization

        This course will provide an overview of the current state-of-the-art of big data searching techniques in computer vision, machine learning and data mingearning by studying a set of cutting-edge advanced topics in these areas. Several selected research topics reflect the current state in these fields. The main objective of this course is to review cutting-edge searching& learning research in big data through lectures covering the underlying statistical & mathematical concepts and representative algorithms, paper reading, and implementation. The instructor will work with students on building ideas, performing experiments, and writing papers. Students can decide to submit his/her results to a learning/mining/vision related conference, or just play with funs.

        The course is application-driven and includes advacnced topics in imaging, learning and vision, such as different imaging techniques and advanced learning tools in different applications. It will also include selected topics relating to the emerging compressed sensing and sparse learning theory and techniques. The course will provide the participants with a thorough background in current research in these areas, as well as to promote greater awareness and interaction between multiple research groups within the university. The course material is well suited for students in computer science, computer engineering, electrical engineering and biomedical engineering. 

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 5392-001 TOPICS IN COMPUTER SCIENCE

        This course presents an introduction to the mathematical, physical, and computational principles underlying modern medical imaging informatics systems. It will cover fundamentals of magnetic resonance imaging (MRI), and functional MRI (fMRI), X-ray computed tomography (CT), ultrasonic imaging, as well as more general concepts required for these, such as linear systems theory, the Fourier Transform, wavelet Transform and the emerging compressive sensing techniques. Popular techniques for the registration, segmentation, and analysis of medical image data will also be discussed, as well as applications of medical imaging to image-guided intervention and healthcare.

        The course is application-driven and includes topics in medical imaging and medical informatics, such as different imaging techniques and advanced image analysis tools in medical applications and healthcare. It will also include selected hot topics relating to the emerging compressive sensing theory and techniques. The course will provide the participants with a thorough background in current research in these areas, as well as to promote greater awareness and interaction between multiple research groups within the university. The course material is well suited for students in computer science, biomedical engineering, and electrical engineering. It will be of appropriate difficulty for both undergraduate and graduate students.
        Spring - Regular Academic Session - 20121 Link

Service to the Community

  • Appointed
    • Sept 2014 to  Present National Science Foundation Review Panelist

      2014, 2015, 2016

    • Sept 2010 to  Present Program / Session / Area Chair

      The Sixth International Conference on Functional Imaging and Modeling of the Heart, New York, USA, May 2011.

      MICCAI Workshop on Sparsity Techniques in Medical Imaging, Nice, France, October 2012.

      The 22th International Conference on Pattern Recognition, Stockholm, Sweden, August 2014

      The 18th International Conference on Medical Image Computing and Computer Assisted Intervention, Munich, Germany, October 2015

    • Sept 2008 to  Present Journal Reviewer

      Annals of Statistics,

      SIAM Journal on Image Science,

      IEEE Signal Processing Letters,

      IEEE Transaction on Multimedia,

      IEEE Transaction on Signal Processing,

      IEEE Transaction on Image Processing,

      IEEE Transactions on Biomedical Engineering,

      IEEE Transactions on Knowledge and Data Engineering,

      IEEE Transactions on Pattern Analysis and Machine Intelligence,

      IEEE Transactions on Circuits and Systems for Video Technology,

      IEEE Transactions on Neural Systems and Rehabilitation Engineering,

      ACM Transactions on Multimedia Computing, Communications and Applications,

      Journal of Optics Express,

      Journal of NeuroComputing,

      Journal of Signal Processing,

      Journal of Medical Image Analysis,

      Journal of Machine Learning Research,

      Journal of Machine Vision and Applications,

      Journal of Signal Image and Video Processing,

      Journal of Computer Vision and Image Understanding,

      Journal of Biomedical Signal Processing and Control,

      Journal of Computational Statistics and Data Analysis,

      Journal of Visual Communication and Image Representation

    • Sept 2007 to  Present Program committee member or reviewer for conferences

      International Conference on Computer Vision, 2007-2009

      IEEE Conference on Computer Vision and Pattern Recognition, 2008

      International Conference on Tools with Artificial Intelligence, 2009

      European Conference on Computer Vision, 2010

      Pacific-Rim Symposium on Image and Video Technology, 2011

      International Conference on Functional Imaging and Modeling of the Heart, 2011

      International Workshop on High Performance Computing for Biomedical Image Analysis, 2014

      International Conference on Medical Image Computing and Computer Assisted Intervention, 2011- 2015

      International Symposium on Biomedical Imaging, 2015

      Annual Conference on Neural Information Processing Systems, 2011-2015

      International Conference on Machine Learning, 2012-2015

Service to the University

  • Volunteered
    • Sept 2011 to  Present Department/University Service

      1. Member of the Ph.D. Admission Committee, (Fall 2012-Spring 2014), CSE, UTA.
      2. Member of the Master Admission Committee, (Fall 2011- Spring 2012), CSE, UTA.
      3. Member of the Enrollments ad hoc Committee (Fall 2011- Spring 2012), CSE, UTA.
      4. Member of the Visiting Appointments Committees (Fall 2014-now), CSE, UTA.
      5. Member of the Quality Assurance Committees (Fall 2014-now), CSE, UTA.
      6. Member of graduate student committees
          a. Chen Chen, September 2013, CSE (Chair: Dr. Junzhou Huang)
          b. Yeqing Li, September 2013, CSE (Chair: Dr. Junzhou Huang)
          c. Zhongxing Peng, April 2015, CSE (Chair: Dr. Junzhou Huang)
          d. Dijun Luo, July 2012, CSE (Chair: Dr. Heng Huang)
          e. Jin Huang, November 2013, CSE (Chair: Dr. Heng Huang)
          f. Deguang Kong, November 2013, CSE (Chair: Dr. Chris Ding)
          g. Jing Xu, November 2013, CSE (Chair: Jeff Lei)
          h. Junjie Chen, April 2013, EE (Chair: Qilian Liang)
          i. Shuai Zheng, October 2014, CSE (Chair: Dr. Chris Ding)
          j. Yun Liu, October 2014, CSE (Chair: Dr. Heng Huang)
          k. Mostafa Parchami, March 2015, CSE (Chair: Dr. Gian-Luca Mariottini)
          l. Jaganmohan Chandrasekaran, June 2015 (Chair: Dr. Jeff Lei)
          m. Joy Wang, August 2015, CSE, (Chair: Dr. Heng Huang)
          n. Dheeraj Ganti, September 2015, CSE, (Chair: Dr. Junzhou Huang)

    • June 2013 to  Present Outreach Activity

      Guest Speakers and Demo Demonstration
      Summer Camp for Middle School Students, Arlington, June 2013,
      Summer Camp for Middle School Girls, Arlington, July 2013,
      Summer Camp for Middle School Students, Arlington, July 2014,
      Summer Camp for Middle School Girls, Arlington, July 2014,
      Summer Camp for Middle School Students, Arlington, July 2015.