Publications

In Proceedings of the 25th International World Wide Web Conference (WWW), 2016
We study the problem of determining the proper aggregation granularity for a stream of time-stamped edges. To this end, we propose ADAGE and demonstrate its value in automatically finding the appropriate aggregation intervals on edge streams for belief propagation to detect malicious files and machines.

In Proceedings of the 21st IEEE Symposium on Computers and Communication (ISCC 2016)
We use distributed and scalable clustering techniques to perform estimation of population estimation, including mobility, based on mobile phone calls data.

In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016)
We propose a novel Bayesian label propagation model to unify the multi-source information, including content-agnostic features of different node types and topological information of the heterogeneous network. Our approach does not need to examine the source codes nor inspect the dynamic behaviours of a binary. Instead, it estimates the maliciousness of a given file through a semi-supervised label propagation procedure, which has a linear time complexity w.r.t. the number of nodes and edges. The evaluation on 567 million real-world download events validates that our proposed approach efficiently detects malware with a high accuracy.

IEEE Transactions on Computers, 2016
Size-based scheduling algorithms can perform disastrously with skewed workloads and incorrect size information. PSBS is a scheduling discipline that performs very well even when job sizes are incorrect.

In Proceedings of the IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS'16) In the context of large-scale data architectures, we propose an efficient technique to speedup the routing of a large number of real-time queries while minimizing the number of machines that each query touches (query span).