Service

EDITOR-SHIP AND CHAIR-SHIP

Associate Editor, IEEE Transactions on Neural Networks and Learning Systems, 2021 - Present
Associate Editor, ACM Transactions on Knowledge Discovery from Data, 2019 - Present
Associate Editor, International Journal of Intelligent Systems, 2020 - Present
Guest Editor, Frontiers in Big Data, 2020
Virtual Conference Chairs, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)
Associate Conference Chairs for Virtual Operations, The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021)
Poser Co-Chairs, 2019 IEEE International Conference on Big Data (IEEE BigData 2019)
Tutorial Co-Chairs, 2018 IEEE International Conference on Big Data (IEEE BigData 2018)
Track Co-Chairs (ML and NLP), International Conference on AI + Adaptive Education (AIAED 2019)
Workshop Panel Co-Chairs, The First Workshop on "Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL'20)" (with NeurIPS'20)
Workshop Co-Chairs, The Fifth International Workshop on Deep Learning on Graphs (DLG-AAAI'21) (co-located with AAAI'21)
Workshop Co-Chairs, The Fourth International Workshop on Deep Learning on Graphs (DLG-KDD'20) (co-located with KDD'20)
Workshop Co-Chairs, The Third International Workshop on Deep Learning on Graphs (DLG-AAAI'20) (co-located with AAAI'20)
Workshop Co-Chairs, The Second International Workshop on Deep Learning on Graphs (DLG-BigData'19) (co-located with BigData'19)
Workshop Co-Chairs of The First International Workshop on Deep Learning on Graphs (DLG-KDD'19) (co-located with KDD'19)
Mini-symposium Co-Chairs, The First International Mini-symposium on High-Performance Eigenvalue and SVD Solvers: Advances and Applications (co-located with SIAM Conference on Computational Science and Engineering 2017)
Senior PC, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)
Senior PC, The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
Senior PC, The 35th AAAI Conference on Artificial Intelligence (AAAI 2021)
Senior PC, The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)
Senior PC, The 29th International Joint Conference on Artificial Intelligence (IJCAI 2020)
Senior PC, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)
Session Chair, The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)
Session Chair, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)
Session Chair, The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019)
Session Chair, The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019)
Session Chair of 2018 IEEE International Conference on Big Data (IEEE BigData 2018)

KEYNOTE AND INVITED TALKS

Keynote talk entitled "Deep Learning on Graphs in Natural Language Processing and Computer Vision", In the DIRA workshop at CVPR 2020, Seattle, WA, June 2020. [Website][Slides][Video]
Keynote talk entitled "Graph-to-Sequence Learning in Natural Language Processing", in the International Workshop on Machine Learning & Artificial Intelligence, Paris, France, October 2019. [Website] [Video]
Keynote talk entitled “Deep Learning on Graphs: AI + Education”, China International Symposium on Artificial Intelligence and Education, Hefei, China, August 2019.
Invited talk entitled "Deep Learning on Graphs: Methods and Applications", in the EECS Lecture Series, Fudan University, Shanghai, China, October 2019.
Invited talk entitled "Deep Learning on Graphs: Methods and Applications", in the EECS Lecture Series, Zhejiang University, Hangzhou, China, October 2019.
Invited talk entitled "Deep Learning on Graphs: Methods and Applications", in the EECS Lecture Series, Nanjing University, Nanjing, China, October 2019.
Invited talk entitled "Deep Learning on Graphs: Methods and Applications", in the EECS Lecture Series, University of California, Los Angeles, USA, October 2019.
Invited talk entitled "Deep Learning on Graphs: Methods and Applications", in the EECS Lecture Series, University of California, Santa Barbara, USA, October 2019.
Invited talk entitled "Graph-to-Sequence Learning in Natural Language Processing", Artificial Intelligence Lecture Series, University of Science and Technology of China, Hefei, China, May 2019.
Invited talk entitled "Graph-to-Sequence Learning in Natural Language Processing", Hefei University of Technology, Hefei, China, May 2019.
Invited talk entitled "Graph-to-Sequence Learning in Natural Language Processing", in the SMSD Seminar Series at MIT, Boston, USA, April 2019.
Invited talk entitled "Graph-to-Sequence Learning in Natural Language Processing", in the CSCE Graduate Seminar at TAMU, College Station, USA, April 2019.
Invited talk entitled "Graph-to-Sequence Learning in Natural Language Processing", in the CSE Lecture Series at MSU, East Lansing, USA, April 2019.
Invited talk entitled "Graph-to-Sequence Learning in Natural Language Processing", in the Computer Science and Engineering Department at University of Notre Dame, Indiana, USA, March 2019.
Invited talk entitled “Unsupervised Feature Representation Learning via Random Features for Structured Data: Theory, Algorithm, and Applications”, Technology Innovation Seminar, Nanjing University, Nanjing, China, November 2018.
Invited talk entitled “Unsupervised Feature Representation Learning via Random Features for Structured Data: Theory, Algorithm, and Applications”, Big Data Lecture Series, Central China Normal University, Wuhan, China, November 2018.
Invited talk entitled “Unsupervised Feature Representation Learning via Random Features for Structured Data: Theory, Algorithm, and Applications”, Hefei University of Technology, China, November 2018.
Invited talk entitled “Unsupervised Feature Representation Learning via Random Features for Structured Data: Theory, Algorithm, and Applications”, Artificial Intelligence Lecture Series, University of Science and Technology of China, Hefei, China, November 2018.
Invited talk entitled “Unsupervised Feature Representation Learning via Random Features for Structured Data: Theory, Algorithm, and Applications”, John Hopcroft Center Lecture Series, Shanghai Jiao Tong University, Shanghai, China, November 2018.
Invited talk entitled “Unsupervised Feature Representation Learning via Random Features for Structured Data: Theory, Algorithm, and Applications”, Zhejiang University, Hangzhou, China, November 2018.
Invited talk entitled "Managing Big Time-series and Text Data Using Unsupervised Representation Learning", IBM Research - Cambridge Lab, Boston, MA, December 2017.
Invited talk entitled "Managing Big Time-series and Text Data Using Unsupervised Representation Learning", Department of Civil and Environmental Engineering at MIT, Boston, MA, December 2017.
Invited talk entitled "Managing Big Time-series and Text Data Using Unsupervised Representation Learning", IEEE Workshop on Big Data Metadata and Management (BDMM ’2017), Boston, MA, December 2017.
Invited Talk Entitled "Unsupervised Feature Representation Learning for Time Series and Text: A Random Features Approach for Alignment-Aware Kernels", IBM AI Foundation Seminar, IBM T. J. Watson Research Center, Yorktown Heights, NY, September 2017.
Invited Talk Entitled “Solver and Techniques for Large-Scale SVD Computation and Kernel Machines”, IBM T. J. Watson Research Center, Yorktown Heights, NY, November 2016.
Invited Talk Entitled “Block Preconditioned Thick-Restart Lanczos Method with Subspace Optimization for Symmetric Eigenvalue Problems”, 2016 SIAM Annual Meeting, Boston, Massachusetts, USA, July 2016.
Invited Talk Entitled “Scale Up Large-Scale Kernel Machines for Speech Recognition”, IBM T. J. Watson research center, Summer Intern Seminar, Yorktown Heights, NY, August 2015.

TECHNICAL PROGRAM COMMITTEES

REVIEWERS

SIAM Journal on Scientific Computing (Impact Factor: 2.96)
SIAM Journal on Matrix Analysis and Applications (Impact Factor: 2.53)
IEEE Transactions on Knowledge and Data Engineering (Impact Factor: 2.476)
IEEE Transactions on Big Data (Impact Factor: 2.123)
IEEE Transactions on Parallel and Distributed Systems (Impact Factor: 4.181)
ACM Transactions on Management Information Systems (Impact Factor: 1.79)
Data Mining and Knowledge Discovery (Impact Factor: 2.714)
Pattern Recognition (Impact Factor: 3.399)
Machine Learning (Impact Factor: 2.809)
Future Generation Computer Systems (Impact Factor: 3.997)
Journal of Computer Science and Technology (Impact Factor: 0.87)
Mathematical Modelling and Analysis (Impact Factor: 0.63)

SERVING AS Ph.D. COMMITTEE MEMBERS

Shibo Yao, New Jersey Institute of Technology
Yu Chen, Rensselaer Polytechnic Institute
Xiaojie Guo, George Mason University
Zhen Zhang, Washington University in St. Louis

SOCIETIES

ACM
IEEE
AAAI

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