NAN DU

Georgia Tech, College of Computing

About Me

Aug 2011 -

  • Research Assistant, School of Computational Science & Engineering, College of Computing

    • Machine learning for social network structure inference based on information cascades;
    • Continuous-time influence maximization over large-scale social networks;
    • Machine learning for user-engagement modeling and online advertisement assignment;

Contact

dunan AT gatech Dot edu

Institute of Data Analysis and High-Performance Computing (IDH 1120), KACB, Gatech, Atlanta 30332.

Research

My research focuses on modeling diffusion of influence and information over large-scale social and information networks based on the confluence of the cutting-edge statistical machine learning and high-performance computing techniques, which has practical applications in many socialized online systems, including personalized advertising and recommendations.

Selected Publications

Conference

  • Learning Time-Varying Converage Functions . Nan Du, Yingyu Liang, Maria-Florina Balcan, and Le Song. Neural Information Processing Systems (NIPS), 2014, Montreal, Quebec, Canada.

  • Shaping Social Activity by Incentivizing Users. Mehrdad Farajtabar, Nan Du, Manuel Gomez Rodriguez, Isabel Valera, Hongyuan Zha, Le Song. Neural Information Processing Systems (NIPS), 2014, Montreal, Quebec, Canada.

  • Influence Function Learning in Information Diffusion Networks (full oral presentation). Nan Du, Yingyu Liang, Maria-Florina Balcan, and Le Song. International Conference on Machine Learning (ICML) , June. 22 - June 24, 2014, Beijing, China. [PAPER]

  • Scalable Influence Estimation in Continuous-Time Diffusion Networks (Best Paper Award, full oral presentation). Nan Du, Le Song, Manuel Gomez Rodriguez, and Hongyuan Zha. Neural Information Processing Systems (NIPS). Dec. 5 - Dec. 10, 2013, Lake Tahoe, Nevada, USA. [PAPER] [SLIDE][POSTER][CODE][Bibtex]

  • Uncover Topic-Sensitive Information Diffusion Networks (full oral presentation). Nan Du, Le Song, Hyenkyun Woo, and Hongyuan Zha. Sixteenth International Conference on Artificial Intelligence and Statistics (AISTATS) , Apr. 29 - May 1, 2013, Scottsdale, AZ, USA. [PAPER][Bibtex]

  • Learning Networks of Heterogeneous Influence (spotlight presentation). Nan Du, Le Song, Alex Smola, and Ming Yuan. Neural Information Processing Systems (NIPS) , Dec. 5 - Dec. 10, 2012, Lake Tahoe, Nevada, USA. [PAPER][Bibtex]

  • Analysis of large multi-modal social networks: patterns and a generator(full oral presentation). Nan Du, Hao Wang, and Christos Faloutsos. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) , Sep. 20 - Sep. 24, 2010, Barcelona, Catalonia, Spain. [PAPER][Bibtex]

  • Large human communication networks: patterns and a utility-driven generator(full oral presentation). Nan Du, Christos Faloutsos, Bai Wang and Leman Akoglu. Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD) , June. 28 - July. 1, 2009, Paris, France. [PAPER][Bibtex]

  • Overlapping community structure detection in networks. Nan Du, Bai Wang and Bin Wu. Proceedings of the 17th ACM Conference on information and Knowledge Management (CIKM) , 2008, Napa Valley, California, USA. [PAPER][Bibtex]

  • Improved recommendation based on collaborative tagging behaviors. Shiwan Zhao, Nan Du, Andreas Nauerz, Xiatian Zhang, Quan Yuan, and Rongyao Fu. Proceedings of the 13th international conference on Intelligent user interfaces(IUI) , Jan 13-16, 2008, Canary Islands, Spain. [PAPER][Bibtex]

Workshop

  • Community detection in large-scale social networks. Nan Du, Bin Wu, Xin Pei, Bai Wang, and Liutong Xu. Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis (SNAKDD) , 2007, San Jose, California, USA. [PAPER][Bibtex]

  • A parallel algorithm for enumerating all maximal cliques in complex network. Nan Du, Bin Wu, Liutong Xu, Bai Wang, and Xin Pei. The Second International Workshop on Mining Complex Data, 2006, HongKong, China. [PAPER][Bibtex]

Teaching

Teaching Assistant

Spring 2013, CSE 8803, Advanced Machine Learning, Office Hour: 2:00-3:00pm, Friday, Location: IDH 1120

Fall 2013, CSE 6740, Computational Data Analysis, Office Hour: 2:00-3:00pm, Friday, Location: IDH 1120

Skills

Programming

C/C++    Matlab  R  Java  SQL  JavaScript

HPC

MPI  OpenMP  CUDA  SSE  Hadoop

Visualization

D3  Prefuse

Machine Learning