蘇敬勇，教授博導，哈爾濱工業大學（深圳）青年拔尖教授。分別於2006年和2008年獲得哈爾濱工業大學儀器科學與技術專業本科和碩士學位，2013年博士畢業於佛羅里達州立大學統計系。之後任職於美國德州理工大學數學與統計系，擔任助理教授和終身副教授。主要從事為複雜的函式型數據（包括形狀和圖像）建立統計模型和算法。結合統計學、微分幾何和最佳化算法解決計算機視覺、機器學習、醫學圖像分析、生物學等領域的具體問題。已在國際頂級期刊和會議（IEEE TPAMI，IJCV，CVPR，Annals of Applied Statistics）發表多篇論文，含ESI高被引論文。
基本介紹
- 中文名：蘇敬勇
- 畢業院校：佛羅里達州立大學
- 職業：教師
- 職稱：教授
研究方向
1. 計算機視覺和模式識別（Computer Vision and Pattern Recognition）
2. 大數據 (Big Data)
3. 統計學習 (Statistical Learning)
4. 流形統計學 (Statistics on Manifolds)
5. 函式型與形狀數據分析 (Functional Data Analysis, Shape Data Analysis)
6. 圖像分析 (Image Understanding)
教育經歷
2006.9-2008.8 哈爾濱工業大學 碩士 儀器科學與技術
2008.9-2013.8 佛羅里達州立大學 博士 統計學
研究與工作經歷
2013.9-2019.2 美國德州理工大學 助理教授 數學與統計系
2019.2-2019.12 美國德州理工大學 副教授 數學與統計系
科研成果及獎勵
2019 Departmental Service Award, Department of Mathematics & Statistics, Texas Tech University.
2016 Departmental Award for Excellence in Research,Texas Tech University.
2014 Best Scientific Paper Award by International Conference on Pattern Recognition.
2013 The R.A. Bradley Award, Department of Statistics, Florida State University
2013 Graduate Student Research and Creativity Award, Florida State University.
2012 NSF Travel Award, CVPR 2012 Doctoral Consortium.
2010-2019 NSF Travel Awards to SAMSI, MBI and SRCOS.
論文及著作
期刊代表作
Z. Zhang, J. Su, H. Le, E. Klassen and A. Srivastava 2018. Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories. Journal of Mathematical Imaging and Vision :1-18.
R. Anirudh, P. Turaga, J. Su and A. Srivastava 2017. Elastic Functional Coding of Riemannian Trajectories. IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI) 39 (5): 922-936.
F. Souza, S. Sarkar, J. Su and A. Srivastava 2017. Spatially Coherent Interpretations of Videos Using Pattern Theory. International Journal of Computer Vision 121 (1): 5-25.
B. B. Amor, J. Su and A. Srivastava 2016. Action Recognition Using Rate-Invariant Analysis of Skeletal Shape Trajectories. IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI) 38(1): 1-15.
F. Souza, S. Sarkar, A. Srivastava and J. Su 2016. Pattern Theory for Representation and Inference of Semantic Structures in Videos. Pattern Recognition Letters 72: 41-51.
J. Su, S. Kurtek, E. Klassen and A. Srivastava 2014. Statistical Analysis of Trajectories on Riemannian Manifolds: Bird Migration, Hurricane Tracking, and Video Surveillance. Annals of Applied Statistics 8(1): 530-552.
S. Kurtek, J. Su, C. Grimm, M. Vaughan, R. Sowell and A. Srivastava 2013. Statistical Analysis of Manual Segmentations of Structures in Medical Images. Computer Vision and Image Understanding 117(9): 1036-1050.
J. Su, F. Huffer and A. Srivastava 2013. Detection, Classification and Estimation of Individual Shapes in 2D and 3D Point Clouds. Computational Statistics and Data Analysis 58: 227-241.
J. Su, I. L. Dryden, E. Klassen, H. Le and A. Srivastava 2012. Fitting Smoothing Splines to Time-Indexed, Noisy Points on Nonlinear Manifolds. Journal of Image and Vision Computing 30(6-7): 428-442.
會議論文及發表演說
F. Souza, S. Sarkar, A. Srivastava and J. Su 2015. Temporally Coherent Interpretations for Long Videos Using Pattern Theory. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
R. Anirudh, P. Turaga, A. Srivastava and J. Su 2015. Exploring the Latent Functional Space of Trajectories on Riemannian Manifolds with Applications to Human Actions. IEEE CVPR.
J. Su, A. Srivastava, F. Souza and S. Sarkar 2014. Rate-Invariant Analysis of Trajectories on Riemannian Manifolds with Application in Visual Speech Recognition. IEEE CVPR. Accepted as Oral (5.75% rate).
F. Souza, S. Sarkar, J. Su and A. Srivastava 2014. Pattern Theory-Based Interpretation of Activities. ICPR, Stockholm, Sweden, August 2014. Best Scientific Paper Award.
J. Su, Z. Zhu, A. Srivastava and F. Huffer 2010. Detection of Shapes in 2D Point Clouds Generated from Images. International Conference on Pattern Recognition, Istanbul, Turkey, August 2010. Accepted as Oral (18% rate).
J. Su, Z. Zhu, A. Srivastava and F. Huffer 2010. A Fully Statistical Framework for Shape Detection in Image Primitives. The 7th IEEE Workshop on Perceptual Organization in Computer Vision (POCV), San Francisco, California, June 2010.
著作章節
S.H. Joshi, J. Su, Z. Zhang and B.A. Boulbaba 2016. Elastic Shape Analysis of Functions, Curves and Trajectories. Riemannian Computing in Computer Vision: 211-231.
J. Su and L. Tang 2014. Shape Estimation from 3D Point Clouds. Intelligent Data analysis and its Applications, Volume I - Advances in Intelligent Systems and Computing 297:39-46.
J. Su, S. Kurtek and A. Srivastava 2013. Joint Registration and Shape Analysis of Curves and Surfaces. Shape Perception in Human and Computer Vision 1(1): 213-224.
