Short Bio

I am a Ph.D. Candidate major in Electrical Engineering and minor in Computer Science at University of Southern California. I am lucky to have Prof. Gerard Medioni as my advisor and work on machine learning algorithms for structured multivariate time series and high dimensional data. My research lab is Institute for Robotics and Intelligent Systems, Viterbi School of Engineering.

I worked as a quantitative research intern at Barclays Capital on algorithmic trading, a research intern at SONY US Research Center on kernel metric learning and ranking, and a research intern at Microsoft Research Asia on graphical model based feature learning. I got my BS in Electronic Engineering from Tsinghua University.

My general passion is to design effecient and elegant solution to solve challenging problems in real world by a combination of machine learning, optimization and statistics.

News 

06/2012   Quantitative Research Intern at Barclays Capital, New York, NY.

06/2012   One paper on non-parametric online change-point detection is accepted by ECCV 2012.

06/2012   One paper on very crowed scene tracking is accepted by ECCV 2012.

04/2012   One paper on strcture learning of high dimension data is accepted by ICML 2012.

04/2012   One workshop paper on Probabilistic Tensor Voting is accepted by CVPR 2012.

07/2011   One paper on Structured Time Series Alignment is accepted by ICCV 2011.

06/2011   Research intern at SONY US Research Center, San Jose, CA.

04/2011   Passed my PhD Oral Qualifying Examination.

Research Interests 

1. On the theoretical side, my current research focuses on analytic analysis for Robust Manifold Learning and Tensor Voting. These are unsupervised learning methods for modeling high dimensional data and multivariate time series.

2. At the algorithm level, I am working on different machine learning domains include, modeling structured multivariate time series, fast mining large-scale time series, spatio-temporal alignment, change-point detection, multi-manifold structure learning, metric and kernel learning, non-parametric manifold denoising, convex optimization, etc.

3. As an application, I am using the spatial-temporal manifold model for human motion analysis and recognition. I am also working on image contour grouping for image enhancement.

DMW is an unsupervised similarity learning and alignment algorithm for structured multivariate time series. Under the spatio-temporal manifold model, DMW can align two series with different length, dimensionality and sampling frequency.

 


 


Related Publications:

Dian Gong and Gerard Medioni, "Dynamic Manifold Warping for View Invariant Action Recognition", Proc. of the IEEE 13th International Conference on Computer Vision (ICCV 2011), Barcelona, Spain, November 2011.

LLD is a non-linear and non-parametric denoising algorithm for high-dimensional data with the intrinsic manifold strucutre. LLD denoises the manifold by jointly optimizing the local to global alignment error and graph Laplacian (Laplacian-Bertrami) energy.

 


 


Related Publications:

Dian Gong, Fei Sha and Gerard Medioni, "Locally Linear Denoising on Image Manifolds", Proc. of the 13th International Conference on Artifical Intelligence and Statistics (AISTATS 2010), Sardinia, Italy, May 2010. Journal of Machine Learning Research: W&CP 9.

Previous Works

Publications

  • Journal

Dian Gong, Xuemei Zhao, Yunfan Li, "Tight geometric bound for Marcum Q-function",  IEE Electronic Letters, Volume 44, Feb. 28, 2008. [Zhao and Gong contributed equally to this work]

  • Conference

Dian Gong, Gerard Medioni, Sikai Zhu and Xuemei Zhao, "Kernelized Temporal Cut for Online Tempoal Segmentation and Recognition", Proc. of the 12th European Conference on Computer Vision (ECCV 2012), Firenze, Italy, October 2012. [Video] [Project Webpage] [new!]

Xuemei Zhao, Dian Gong and Gerard Medioni, "Tracking Using Motion Patterns for Very Crowded Scenes", Proc. of the 12th European Conference on Computer Vision (ECCV 2012), Firenze, Italy, October 2012. [Video] [Project Webpage] [new!]

Dian Gong, Xuemei Zhao and Gerard Medioni, "Robust Multiple Manifolds Structure Learning", Proc. of the 29th International Conference on Machine Learning (ICML 2012), Edinburgh, Scotland, June 2012. [Slide] [Project Webpage] [new!]

Dian Gong and Gerard Medioni, "Probabilistic Tensor Voting for Robust Perceptual Grouping", workshop on POCV, Proc. of the IEEE 25th Conference on Computer Vision and Pattern Recognition (CVPR 2012), Rhode Island, USA, June 2012. [Slide] [new!]

Dian Gong and Gerard Medioni, "Dynamic Manifold Warping for View Invariant Action Recognition", Proc. of the IEEE 13th International Conference on Computer Vision (ICCV 2011), Barcelona, Spain, November 2011. [Video] [Video Presentation] [Project Webpage]

Dian Gong, Fei Sha and Gerard Medioni, "Locally Linear Denoising on Image Manifolds", Proc. of the 13th International Conference on Artifical Intelligence and Statistics (AISTATS 2010), Sardinia, Italy, May 2010. Volume 9 of Journal of Machine Learning Research: W&CP 9. [Poster] [Project Webpage]

Dian Gong, Xuemei Zhao and Qiong Yang, "Sparse Non-Negative Pattern Learning for Image Represenation", Proc. of the 15th IEEE International Conference on Image Processing (ICIP 2008) ,San Diego, California, USA, October 2008. 

Qiong Yang, Dian Gong and Xiaoou Tang, "Modeling Micro-patterns for Feature Extraction",  Proc. of the 10th IEEE International Conference on Computer Vision (ICCV 2005), workshop on AMFG (Oral), pp.2-16, LCNS, Beijing, China, October 2005. 

Dian Gong, Qiong Yang, Xiaoou Tang, Jianhua Lu, “Extracting Micro-Structural Gabor Features for Face Recognition”, Proc. of the 12nd IEEE International Conference on Image Processing (ICIP 2005), Vol. 2, pp.924-5, Genova, Italy, September 2005.

Dian Gong, Yunfan Li, Xuemei Zhao, "Geometric Inversion Approach for Visual Curve Estimation", Proc. of the 42nd Annual Conference on Information Sciences and Systems (CISS 2008) (Oral), Princeton, NJ, USA, March 2008. 

Dian Gong, Zhiyao Ma, Yunfan Li, Wei Chen, Zhigang Cao, "High Order Geometric Range Free Localization in Opportunistic Cognitive Sensor Networks", Proc. of the 43rd IEEE International Conference on Communications (ICC 2008), CoCoNet (Oral), Beijing, China, 2008.

Dian Gong, Yunfan Li, "Dynamic System Analysis and Generalized Optimal Code Assignment of OVSF-CDMA Systems", Proc. of the 43rd IEEE International Conference on Communications (ICC 2008) (Oral), Beijing, China, 2008.

Dian Gong, Yusong Yan, Jianhua Lu, "Dynamic code assignment for OVSF code system ", Proc. of the 48th IEEE Global Telecommunications Conference (GLOBECOM 2005) (Oral), St. Louis, MO, USA, 2005.

  • Patents 

Qiong Yang, Dian Gong, Xiaoou Tang, Modeling Micro-Structure for Feature Extraction, US Patent 315262.02, 2007

Awards

Gold Medal, Contemporary Undergraduate Mathematical Contest in Modeling (CUMCM), 2002

International Mathematical Olympiad (IMO) Chinese National Team Candidate, 2000

Gold Medal, China Mathematics Olympiad (CMO), 2000

Miscellaneous

During the spare time, I love watching movies and listening pop music. Especially, I was a director in TDO (TDO means trade-off, it is extremely important for team work^_^) studio, Tsinghua University. We made two student movies and one music video. One of the movie is "how do I love you", which got the best idea and best actor prizes in the first Tsinghua Digital Movie Festival, 2004. 

Here is the link of this movie in youku. Actually, I just found it out by accident and I really do not know who put this online, but it is fine, enjoy it:-).


  

Links: Tie-Yan Liu, Jing ShengZhen Xiang, Chao Yu, Qiong Yang

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