Meng Jiang.

I am a postdoctoral researcher of Computer Science in University of Illinois at Urbana-Champaign working with Professor Jiawei Han. I completed my Ph.D. in Department of Computer Science and Technology at Tsinghua University, Beijing with Dissertation Award in 2015. I visited Professor Christos Faloutsos at Carnegie Mellon University in 2013 and visited Professor V.S. Subrahmanian at University of Maryland Institute for Advanced Computer Studies, College Park in 2016. [C.V.]

My research focuses on developing data-driven approaches of online behavior analysis for applications such as future behavior prediction, social recommendation, fraud detection, and event summarization, called Data-Driven Behavioral Analytics. It is at the intersection of social media analysis, spatiotemporal data mining, text mining, information extraction, machine learning, and artificial intelligence.

What's New

May 2017: I am teaching summer course UIUC CS412: An Introduction to Data Warehousing and Data Mining from May 30 to August 3! (11:00 a.m.-12:15 p.m., MTR, 0216SC)
March 2017: I feel excited to join the Computer Science and Engineering Department at the University of Notre Dame as a tenure-track assistant professor in Fall 2017! I am recruiting Ph.D. students and visiting scholars. Please send me an e-mail (mjiang89@gmail.com) about yourself.
July 2017: One paper was accepted to Transactions on Knowledge and Data Engineering on large network representation learning.
May 2017: Two papers were accepted to KDD 2017 on (1) "meta pattern" information extraction and (2) causal analysis of human behaviors.
April 2017: One paper was accepted to IJCAI 2017 on disease-symptom network representation learning.
April 2017: Two tutorials were accepted to KDD 2017: (1) Data-Driven Approaches towards Malicious Behavior Modeling and (2) Mining Entity-Relation-Attribute Structures from Massive Text Data. See you this August in Halifax, Nova Scotia, Canada!
January 2017: Tutorials on turning massive, unstructured text corpora into machine-actionable structures were accepted to WWW 2017 and SIGMOD 2017.
November 2016: One full paper was accepted to AAAI 2017 on causal analysis of behavior.
October 2016: A tutorial was delivered at CIKM 2016 on Data-Driven Behavioral Analytics: Observations, Representations and Models with Professor Peng Cui and Professor Jiawei Han.
September 2016: Two short papers were accepted to ICDM 2016 on (1) causal analysis of human behaviors and (2) large network representation learning.
May 2016: A full paper CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors was accepted to SIGKDD 2016 with oral presentation.
January 2016: A survey paper Suspicious Behavior Detection: Current Trends and Future Directions on the Special Issue on Online Behavioral Analysis and Modeling, IEEE Intelligent Systems.

Latest Publications

Embedding Learning with Events in Heterogeneous Information Networks, TKDE, 2017.
MetaPAD: Meta Patten Discovery from Massive Text Corpora, KDD, 2017.
Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing, KDD, 2017.
ContextCare: Incorporating Contextual Information Networks to Representation Learning in Medical Forum Data, IJCAI, 2017.
Treatment Effect Estimation with Data-Driven Variable Decomposition, AAAI, 2017.
Steering Social Media Promotions with Effective Strategies, ICDM, 2016.
Large-Scale Embedding Learning in Heterogeneous Event Data, ICDM, 2016.
CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors, KDD, 2016.
Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms, TKDE, 2016.
Little is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds, AAAI, 2016.
Suspicious Behavior Detection: Current Trends and Future Directions, Special Issue on Online Behavioral Analysis and Modeling, IEEE Intelligent Systems Magazine, 2016.
Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach, Special Issue on the Best of SIGKDD 2014, TKDD, 2016.

Last updated on April 23, 2017.