Pengtao Xie

Senior Director of Data Solutions and Service, Research Scientist
Petuum Inc.
pengtaoxie2008@gmail.com,   pengtao.xie@petuum.com

I obtained my PhD from the Machine Learning Department,
School of Computer Science, Carnegie Mellon University.

Research Interests: Diversity-promoting machine learning (ML), ML for healthcare, large-scale distributed ML, natural language processing, probabilistic graphical models, deep learning.

Curriculum Vitae    


News


Publications


Patents

  • G.Ran, T.Finley, M.Bilenko, and P.Xie. Neural Networks for Encrypted Data. U.S. Patent Application 14/536,145, filed November 7, 2014.

Teaching

Teaching assistant at Carnegie Mellon University for:

Student Mentoring

  • Yuntian Deng (MS student in Language Technologies Institute, CMU)
  • Yuping Gong (MS student in Language Technologies Institute, CMU)
  • Wanchao Liang (MS student in Information Networking Institute, CMU)
  • Hakim Sidahmed (MS student in Language Technologies Institute, CMU)
  • Yuan Xie (PhD student at Indiana University Bloomington)

Talks

  • Database Seminar, Carnegie Mellon University, Mar 2016. Sufficient Factor Broadcasting for Distributed Machine Learning.
  • 11th CSL Student Conference, University of Illinois Urbana-Champaign, Feb 2016. Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization. [Slides]
  • Artificial Intelligence Seminar, Carnegie Mellon University, Feb 2016. Diversity-Inducing Learning of Latent Variable Models: Frequentist and Bayesian Perspectives. [Slides]
  • VALSE Webinar, Oct 2015. Diversity Regularization of Latent Variable Models: Theory, Algorithm and Applications. [Slides]
  • Machine Learning Lunch Seminar, Carnegie Mellon University, Sept 2015. Mutual Angular Regularization of Latent Variable Models: Thoery, Algorithm and Applications. [Slides]
  • Beihang University, Aug 2015. Diversifying Restricted Boltzmann Machine for Document Modeling.
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Sydney, Aug 2015. Diversifying Restricted Boltzmann Machine for Document Modeling.
  • VASC Seminar, Carnegie Mellon University, April 2015. Integrating Image Clustering and Codebook Learning.
  • Machine Learning Lunch Seminar, Carnegie Mellon University, April 2015. Integrating Data Clustering and Representation Learning.
  • SCS Student Seminar, Carnegie Mellon University, April 2015. Incorporating Word Correlation Knowledge into Topic Modeling.
  • CL+NLP Seminar, Carnegie Mellon University, Apr 2015. Incorporating Word Correlation Knowledge into Topic Modeling.
  • Database Seminar, Carnegie Mellon University, Mar 2015. Mining User Interests from Personal Photos.
  • 29th AAAI Conference on Artificial Intelligence, Austin, Jan 2015. Integrating Image Clustering and Codebook Learning.
  • Database Seminar, Carnegie Mellon University, Sept 2014. CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph.
  • Machine Learning Lunch Seminar, Carnegie Mellon University, Sept 2014. Privacy Preserving Neural Network Prediction on Encrypted Data.[Video]
  • Cylab Student Seminar, Carnegie Mellon Unversity, Sep 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data.
  • SDI/ISTC Seminar, Carnegie Mellon Unversity and Intel, Sep 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data.
  • Cloud Machine Learning Team and Machine Learning Group, Microsoft Research, Aug 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data.
  • Cryptography Group, Microsoft Research, Jul 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data.
  • 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), Beijing, Aug 2013. Multi-Modal Distance Metric Learning.

Professional Activities

  • Program Committee Member for the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 2017  
  • Program Committee Member for IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017  
  • Reviewer for Neural Information Processing Systems (NIPS), 2016  
  • Program Committee Member for Asian Conference on Computer Vision (ACCV), 2016  
  • Reviewer for European Conference on Computer Vision (ECCV), 2016  
  • Program Committee Member for Annual Meeting of the Association for Computational Linguistics (ACL), 2016  
  • Program Committee Member for IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016  
  • Reviewer for Journal of the American Statistical Association (JASA)  
  • Program Committee Member for Annual Meeting of the Association for Computational Linguistics (ACL), 2015  
  • Reviewer for Conference on Empirical Methods in Natural Language Processing (EMNLP), 2015  
  • Reviewer for International Conference on Computer Vision (ICCV), 2015  
  • Reviewer for ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015  
  • Reviewer for International Conference on Machine Learning (ICML), 2014  
  • Reviewer for IEEE Transactions on Multimedia (TMM)  
  • Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)  
  • Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS)  
  • Membership: ACM, IEEE  

Industry Experience

  • Cloud Machine Learning Team and Machine Learning Group, Microsoft Research, Redmond, May 2014 -- Aug 2014.
    Mentors: Thomas Finley, Misha Bilenko, Ran Gilad-Bachrach. I also work closely with Kristin Lauter and Michael Naehrig.
  • Web Search and Mining Group, Microsoft Research Asia, Aug 2009 -- Jun 2010. Mentor: Rong Xiao.

Awards&Honors

  • Siebel Scholarship, 2014. Press Release: [CMU SCS] [CMU] [CMU LTI]
  • KDD Travel Award, 2015
  • CMU Research Fellowship, 2013-2018
  • Excellent Master Graduate Award, Dept. of CS, Tsinghua University, 2013
  • UAI Travel Award, 2013
  • Excellent Bachelor Thesis Award,2010
  • National Scholarship,2009
  • National First Prize in China Undergraduate Mathematical Contest of Modeling (CUMCM),2008
  • Goldman Sachs Global Leader Scholarship,2008