Kevin Shuai Xu
Kevin S. Xu

Assistant Professor, EECS Department
University of Toledo
2801 W. Bancroft St. MS 308
Toledo, OH  43606-3390, USA



Recent news

  • Sept. 23: Our paper "Evaluating link prediction accuracy on dynamic networks with added and removed edges" has been accepted to SocialCom 2016. A preprint is available at http://arxiv.org/abs/1607.07330

Upcoming events

Research

I direct the Interdisciplinary Data Engineering and Science (IDEAS) Laboratory at the University of Toledo. Our research is primarily in the areas of machine learning and statistical signal processing with applications primarily to network science and human dynamics. Current research projects include the following:
  • Statistical models and efficient inference procedures for discrete-time and continuous-time dynamic networks
  • Analysis of physiological data (such as heart rate variability and electrodermal activity) collected using wearable sensors
  • Applications of machine learning and data mining in cybersecurity

Education

  • PhD, Electrical Engineering: Systems, University of Michigan, 2012, Advisor: Alfred O. Hero III
  • MSE, Electrical Engineering: Systems, University of Michigan, 2009
  • BASc, Honors Electrical Engineering, University of Waterloo, 2007

Honors and awards

  • Winner, International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction Challenge, 2013
  • Postgraduate scholarship: Doctorate, Natural Sciences and Engineering Research Council of Canada, 2010-2011
  • Postgraduate scholarship: Master’s, Natural Sciences and Engineering Research Council of Canada, 2008
  • Runner-up to best oral presentation, Engineering Graduate Symposium, University of Michigan, 2008

Selected publications

For a full publication list, please see my CV or my Google Scholar Citations profile.
  • Han, Q., Xu, K. S., & Airoldi, E. M. (2015). Consistent estimation of dynamic and multi-layer block models. In Proceedings of the 32nd International Conference on Machine Learning (pp. 1511–1520). arXiv:1410.8597
  • Xu, K. S. (2015). Stochastic block transition models for dynamic networks. In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (pp. 1079–1087). arXiv:1411.5404
  • Xu, K. S., & Hero III, A. O. (2014), “Dynamic stochastic blockmodels for time-evolving social networks,” IEEE Journal of Selected Topics in Signal Processing, 8(4), 552–562. arXiv:1403.0921.
  • Xu, K. S., Kliger, M., & Hero III, A. O. (2014). Adaptive evolutionary clustering. Data Mining and Knowledge Discovery, 28(2), 304–336. arXiv:1104.1990.
  • Hsiao, K.-J., Xu, K. S., Calder, J., & Hero III, A. O. (2012). Multi-criteria anomaly detection using Pareto depth analysis. In Advances in Neural Information Processing Systems 25 (pp. 854–862). arXiv:1110.3741
  • Xu, K. S., Kliger, M., Chen, Y., Woolf, P. J., & Hero III, A. O. (2009). Revealing social networks of spammers through spectral clustering. In Proceedings of the IEEE International Conference on CommunicationsarXiv:1305.0051

Teaching

  • Fall 2016: EECS 4750/5750 Machine Learning
  • Spring 2016: EECS 6980/8980 Social Network Analysis (special topics course)
  • Fall 2015: EECS 1510 Introduction to Object-Oriented Programming

Software

The following software packages have resulted from my research.

Recent presentations

  • Consistent estimation of dynamic and multi-layer block models: ICML 2015 Slides Video lecture
  • Stochastic block transition models for dynamic networks: AISTATS 2015 Slides

Curriculum vitae