Conference Tutorials

Panelist

  • National Science Foundation (NSF)
  • Centers for Disease Control and Prevention (CDC)

Associate Editor / Editorial Board

  • Transactions on Machine Learning Research (2024 - )
  • IEEE Transactions on Neural Networks and Learning Systems (2022 - )
  • IEEE Transactions on Cognitive and Developmental Systems (2024 - )
  • IEEE Transactions on Consumer Electronics (2024 - )
  • IEEE Transactions on Circuits and Systems for Video Technology (2021 - )
  • IEEE Computational Intelligence Magazine (2019 - )
  • Journal of Electronic Imaging (2018 -2022)
  • Neurocomputing (2017 - 2022)
  • IET Image Processing (2017 - 2020)
  • Neural Computing and Applications (2017 - 2023)

Program Chair

Publicity Chair

Area Chair / Senior Program Committee

Program Committee

  • 2023: ICCV, CVPR, EMNLP
  • 2022: ICML, CVPR, ECCV, KDD
  • 2021: ICML, CVPR, ICLR, ACL
  • 2020: NeurIPS, ICML, CVPR, ECCV, KDD, ICLR, EMNLP, UAI, PAKDD, ECAI, IEEE BigData, AAAI-AISI, AAAI-AFFCON
  • 2019: NeurIPS, ICML, IJCAI, CVPR, ICCV, KDD, ICLR, UAI, MIPR, IEEE BigData, BMVC
  • 2018: NIPS, AAAI, IJCAI, KDD, ACM MM, MIPR, IEEE BigData, PAKDD, ICTAI, AAAI-AFFCON
  • 2017: AAAI, IJCAI, IEEE FG, PAKDD, DSAA, ACII, NLPCC
  • 2015: IJCAI

Reviewer

  • IEEE TPAMI / TKDE / TIP / TNNLS / TMM / TBD / TC / TCSVT / TETCI / Access
  • ACM CSUR / TKDD / TOMM / TOSN / TIST
  • JMLR, Pattern Recognition, Neurocomputing, PLoS ONE, IJPRAI, JVCI, JEI, OE, NCAA, etc.

Professional Associations

  • Senior Member, IEEE
  • Member, ACM
  • Member, AAAI
  • Member, SIAM

Invited Talks

  • Knowledge-Guided Graph Representation Learning. Dept. of Statistics, University of Georgia, Athens, GA. Dec. 2020.
  • Machine Learning Meets Causal Inference. Keynote Talk, NCAA 2020. Jul. 2020.
  • Machine Learning Meets Causal Inference. IEEE Atlanta Section. Jul. 2020.
  • Knowledge Guided Representation Learning on Graphs. Adobe Data Science Symposium. Jul. 2019.
  • An Introduction to Machine Learning and Deep Learning. The University of Iowa, Iowa City, IA. Apr. 2019.
  • Deep Representation Learning for Sequential Data. Kennesaw State University, Marietta, GA. Jan. 2019.
  • An Overview of Deep Learning. Guest Lecture of CSCI 4550, University of Georgia, Athens, GA. Nov. 2018.
  • An Overview of Machine Learning. Guest Lecture of CSCI 4530, University of Georgia, Athens, GA. Oct. 2018.
  • Adversarial Training for Sequential Data. Institute for Artificial Intelligence, University of Georgia, Athens, GA. Oct. 2018.
  • Adversarial Training for Sequential Data. DELUG Seminar, University of Georgia, Athens, GA. Oct. 2018.
  • Representation Learning for Data Analytics and Knowledge Inference. ECE, University of Georgia, Athens, GA. Oct. 2018.
  • Introduction to Artificial Intelligence and Machine Learning. Legal Group, Adobe Systems Inc., San Jose, CA. Mar. 2018.
  • Learning Robust Representations for Data Analytics. ECE Seminar, University of Miami, FL. May 2017.
  • Learning Robust Representations for Data Analytics. CIS Seminar, Temple University, PA. Nov. 2016.
  • Robust Representations for Data Analytics and Knowledge Inference. Adobe Research, San Jose, CA. Nov. 2016.
  • Learning Robust Representations for Data Analytics. CS Seminar, University of Minnesota Twin Cities, MN. Oct. 2016.
  • Learning Robust Representations for Data Analytics. Yahoo!-DAIS Seminar, University of Illinois Urbana-Champaign, Champaign, IL. Sept. 2016.
  • Low-Rank and Sparse Modeling. IFP, University of Illinois Urbana-Champaign, Champaign, IL. Sept. 2016.
  • Temporal Subspace Clustering for Human Motion Segmentation. New England Computer Vision Workshop, Amherst, MA. Nov. 2015.
  • Guest Lecture for EECE5642 Data Visualization: Dimensionality Reduction. Northeastern University, Boston, MA. Oct. 2015.
  • Learning with Robust Data Representations: Methodologies and Applications. NEPSSS, Northeastern University, Boston, MA. Sept. 2015.
  • Rethinking Campaign: A Causal Inference Approach. Adobe Research, San Jose, CA. Jul. 2015.
  • Guest Lecture for EECE5698 Found of Visualization: Dimensionality Reduction. Northeastern University, Boston, MA. Sept. 2014.
  • Predicting User Behaviors with Collaborative Filtering. Adobe Research, San Jose, CA. Jul. 2014.
  • Introduction to Advanced Topics in Machine Learning. Northeastern IEEE, Boston, MA. Apr. 2014.
  • Low-Rank Balanced Graphs for Semi-Supervised Learning. CDSP Workshop, Northeastern University, Boston, MA. Mar. 2014.
  • Color image canonical correlation analysis for face recognition. Hohai University, Nanjing. Apr. 2012.
  • Divide-and-Conquer based Discriminant Analysis. Harbin Institute of Technology Shenzhen Graduate School. Nov. 2011.