Talks

  • Neill DB: "Event detection," half-day tutorial (with Weng-Keen Wong). 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Paris, France, June 2009.
  • Dubrawski A. Machine learning in support of biomedical security. University of Colombo, Sri Lanka. April 2009.
  • Dubrawski A. Statistical machine learning as a platform for analysis of multi-stream food safety data. Twelfth Biennial CDC/ATSDR Symposium on Statistical Methods, Decatur, GA. April 2009.
  • Neill DB: "Multivariate Bayesian scan statistics for event detection and characterization," Twelfth Biennial CDC/ATSDR Symposium on Statistical Methods, Decatur, GA, April 2009.
  • Dubrawski A. Selected analytic algorithms and data representation structures developed by the CMU Auton Lab that may be relevant to BioSense data and goals. CDC Public Health Informatics BioSense Team Seminar, Atlanta, GA. February 2009.
  • Dubrawski A. Applications of statistical and computational methods of machine learning. Warsaw University, Warsaw, Poland. January 2009.
  • Dubrawski A. Data-driven analytics in support of biomedical security. Polytechnic University of Catalunya, Barcelona, Spain. January 2009.
  • Neill DB: "A nonparametric scan statistic for multivariate spatial biosurveillance," Joint Statistical Meetings 2008, Denver, CO, August 2008.
  • Neill DB: "Linear-time subset scanning," Fourth International Workshop on Applied Probability, Compiegne, France, July 2008.
  • Das K: Anomaly pattern detection in categorical datasets. ACM Conference on Knowledge Discovery and Data Mining, Las Vegas, Nevada. August 2008.
  • Cami A:  Integrating a commuting model with the Bayesian aerosol release detector. Postdoctoral Symposium, University of Pittsburgh. May 2008.
  • Cooper GF: Bayesian biosurveillance. Donald A. B. Lindberg Symposium, Pittsburgh, Pennsylvania. May 2008.
  • Hogan WR:  The Bayesian aerosol release detector.  Donald A. B. Lindberg Symposium, Pittsburgh, Pennsylvania. May 2008.
  • Neill DB: Multivariate event detection and characterization. Washington Statistical Society Seminar, Washington, DC. May 2008.
  • Neill DB: Multivariate outbreak detection and characterization. Donald A. B. Lindberg Symposium, Pittsburgh, Pennsylvania. May 2008.
  • Tsui FC: Disease case detection using NLP. Donald A. B. Lindberg Symposium, Pittsburgh, Pennsylvania. May 2008.
  • Wager MM: Informatics in biosurveillance: A ten-year retrospective. Donald A. B. Lindberg Symposium, Pittsburgh, Pennsylvania. May 2008.
  • Cooper GF: Efficient Bayesian model averaging. Invited Speaker, Department of Biostatistics, Bioinformatics, & Epidemiology, Medical University of South Carolina. December 2007.
  • Siddiqi S: A constraint generation approach to learning stable linear dynamical systems. Conference on Advances in Neural Information Processing Systems (NIPS). Vancouver, British Columbia, Canada. December 2007.
  • Siddiqi S: Latent variable and predictive models of dynamical systems. Thesis Proposal Defense, Robotics Institute, Carnegie Mellon University. December 2007. [pdf]
  • Dubrawski A: Applying outbreak detection algorithms to prognostics. AAAI Fall Symposium on AI in Prognostics, Arlington, Virginia. November 2007.
  • Dubrawski A: Efficient representation of data in support of situational awareness.INFORMS 2007, Seattle, Washington. November 2007.
  • Tsui FC: Biosurveillance systems: Evaluation framework and lessons learned. Invited talk at 4th TEPHINET Southeast Asia/Western Pacific Bi-regional Scientific Conference, Taipei, Taiwan. November 2007.
  • Cami A:  Effect of work-related mobility in the simulation of aerosol anthrax releases with BARD.  Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Neill DB. A nonparametric scan statistic for multivariate disease surveillance.  Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Neill DB: An empirical comparison of spatial scan statistics for outbreak detection. Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Neill DB: Detecting and preventing emerging epidemics of crime.  Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Neill DB. Incorporating learning into disease surveillance systems.  Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Roure J: Learning specific detectors of adverse events in multivariate time series. Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Shen Y: A Bayesian biosurveillance method that models unknown outbreak diseases. NSF Workshop on BioSurveillance Systems and Case Studies, Indianapolis, Indiana. October 2007. [talk ppt] [paper pdf]
  • Shen Y: An outbreak detection algorithm that efficiently performs complete Bayesian model averaging over all possible spatial distributions of disease. Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007. [talk ppt] [paper pdf]
  • Siddiqi S: Learning stable multivariate baseline models for outbreak detection. Conference of the International Society for Disease Surveillance. Indianapolis, Indiana. October 2007.
  • Das K: Detecting anomalous records in categorical datasets. ACM Conference on Knowledge Discovery and Data Mining (KDD), San Jose, California. August 2007.
  • Hogan WR:  Bayesian analysis of surveillance data and meteorological data for detection of aerosol releases of B. anthracis spores.  Joint Statistical Meetings. July 2007.
  • Neill DB: A multivariate Bayesian method for spatial biosurveillance. Joint Statistical Meetings, Salt Lake City, Utah. July 2007.
  • Hogan WR: Approximating the sum of lognormal distributions to enhance models of inhalational anthrax. Quantitative Methods in Defense and National Security. February 2007.
  • Adamou C: Modeling Clinician Detection Time of a Disease Outbreak Due to Inhalational Anthrax. National Syndromic Surveillance Conference, Seattle, Washington. November 2005. [abstract] [poster]
  • Garman C: The Effect of Inferring Work Location from Home Location in Performing Bayesian Biosurveillance. National Syndromic Surveillance Conference, Seattle, Washington. November  2005. [abstract]
  • Shen Y: Neill DB: A Bayesian Scan Statistic for Spatial Cluster Detection. National Syndromic Surveillance Conference,Seattle, Washington. November 2005. [talk ppt] [paper pdf]
  • Shen Y:A Generalization of the Standard AMOC Curve. National Syndromic Surveillance Conference, Seattle, Washington. November 2005.  [talk ppt] [paper pdf]
  • Wong WK: Population-wide Anomaly Detection. The Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,Chicago, Illinois. August2005. [talk ppt] [paper pdf] [poster]
  • Cooper GF: Bayesian Biosurveillance of Disease Outbreaks. The Twentieth Conference on Uncertainty in Artificial Intelligence, Banff, Canada. July 2004. [talk ppt] [paper pdf]
  • Wong WK: Bayesian Biosurveillance Using Multiple Data Streams. National Syndromic Surveillance Conference, Boston, Mass. November 2004. [talk ppt] [paper pdf]

This material is based upon work supported by the National Science Foundation under Grant No. 0325581. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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