Presentations

2018

Daniel B. Neill. Machine learning, big data, and development (invited seminar series). International Monetary Fund, Washington, DC, March 2018 (part 1) and June 2018 (part 2).

2017

Daniel B. Neill. Machine learning for public health and disease surveillance. New York University, Department of Population Health, January 2017.

Daniel B. Neill, Chunpai Wang, Feng Chen, and Daniel Hono. Efficient pattern detection in web-scale graphs by subcore-tree decomposition and subset scanning. Joint Statistical Meetings, Baltimore, MD, July 2017.

Zhe Zhang and Daniel B. Neill. Identifying significant predictive bias in classifiers. Fourth Workshop on Fairness, Accountability, and Transparency in Machine Learning, Halifax, Canada, August 2017.

Dylan Fitzpatrick and Daniel B. Neill. Support vector subset scan for spatial pattern detection. GEOMED 2017 International Conference on Spatial Statistics, Spatial Epidemiology, and Spatial Aspects of Public Health, Porto, Portugal, September 2017.

Daniel B. Neill and William Herlands. Machine learning for drug overdose surveillance. Bloomberg Data for Good Exchange Conference, New York, NY, September 2017.

Daniel B. Neill and Mallory Nobles. A pre-syndromic surveillance approach for early detection of novel and rare disease outbreaks. Interdisciplinary Association for Population Health Science Conference, Austin, TX, October 2017.

Daniel B. Neill. Multidimensional subset scanning for the public good. University of Texas at Austin, McCombs School of Business, October 2017.

Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Detecting anomalous patterns of care using health insurance claims. INFORMS Workshop on Data Science, Houston, TX, October 2017.

Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Detecting anomalous patterns of care using health insurance claims. INFORMS Conference on Information Systems and Technology, Houston, TX, October 2017.

Daniel B. Neill. Event and pattern detection at the societal scale (invited keynote). ACM SIGSPATIAL Workshop on Analytics for Local Events and News, Redondo Beach, CA, November 2017.

Daniel B. Neill. Machine learning, big data, and development. NIPS 2017 Workshop on Machine Learning for the Developing World, Long Beach, CA, December 2017.

2016

Daniel B. Neill. Event and pattern detection for urban systems. New York University, Center for Urban Science and Progress, February 2016. (pdf)

Daniel B. Neill. Event and pattern detection at the societal scale. New York University, Courant Institute, Department of Computer Science, February 2016. (pdf)

Daniel B. Neill. Event and pattern detection at the societal scale. Georgia Institute of Technology, School of Computational Science and Engineering, March 2016. (pdf)

Daniel B. Neill. Event and pattern detection for urban systems. New York University, Wagner School of Public Service, April 2016. (pdf)

Daniel B. Neill. Fast subset scan for population health and disease surveillance. Harvard University, Department of Biostatistics, T.H. Chan School of Public Health, May 2016. (pdf)

Edward McFowland III, Sriram Somanchi, and Daniel B. Neill. Efficient discovery of heterogeneous treatment effects in randomized experiments via anomalous pattern detection. Eighth International Workshop on Applied Probability, Toronto, Canada, June 2016. (pdf)

Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Detecting anomalous patterns of care using health insurance claims. Eighth International Workshop on Applied Probability, Toronto, Canada, June 2016. (pdf)

Dylan Fitzpatrick, Yun Ni, and Daniel B. Neill. Support vector subset scan for spatial pattern detection. Eighth International Workshop on Applied Probability, Toronto, Canada, June 2016. (pdf)

Edward McFowland III, Sriram Somanchi, and Daniel B. Neill. Efficient discovery of heterogeneous treatment effects in randomized experiments via anomalous pattern detection. Conference on Digital Experimentation, Cambridge, MA, October 2016.

Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Detecting anomalous patterns of care using health insurance claims. Workshop on Health IT and Economics, Washington, D.C., October 2016.

Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Detecting anomalous patterns of care using health insurance claims. Conference on Digital Experimentation, Cambridge, MA, October 2016.

Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Detecting anomalous patterns of care using health insurance claims. INFORMS Annual Meeting, Nashville, TN, November 2016.

Daniel B. Neill. Fast subset scan for population health and disease surveillance. Weill Cornell Medical College, Department of Healthcare Policy and Research, December 2016.

Zhe Zhang and Daniel B. Neill. Identifying significant predictive bias in classifiers. NIPS Workshop on Interpretable Machine Learning for Complex Systems, Barcelona, Spain, December 2016.

Feng Chen, Petko Bogdanov, Daniel B. Neill, and Ambuj K. Singh. Anomalous and significant subgraph detection in attributed networks. Tutorial presented at IEEE International Conference on Big Data, December 2016. (part 1) (part 2)

2015

Skyler Speakman, Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Penalized fast subset scanning. 45th Symposium on the Interface of Computing Science and Statistics (“Best of JCGS” invited session), Morgantown, WV, June 2015. (pdf)

Daniel B. Neill and Feng Chen. Human rights event detection from heterogeneous social media graphs. Human Rights Media Central Workshop, Pittsburgh, PA, July 2015. (pdf)

Seth Flaxman, Andrew Gelman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alex Smola, and Aki Vehtari. Large-scale Gaussian processes for spatiotemporal modeling of disease incidence. Joint Statistical Meetings, Seattle, WA, August 2015. (pdf)

Jason Hong, Tom Mitchell, Daniel B. Neill, and Aarti Singh. Machine learning and health: from neurons to society. World Economic Forum: Annual Meeting of the New Champions, Dalian, China, September 2015. (pdf)

Daniel B. Neill. Event and pattern detection at the societal scale. University of Chicago, Harris School of Public Policy, October 2015. (pdf)

Daniel B. Neill. Event and pattern detection at the societal scale. Harvard University, School of Engineering and Applied Sciences, November 2015. (pdf)

Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, and Alexander J. Smola. Novel approaches to local area spatiotemporal crime rate forecasting with Gaussian processes. American Society of Criminology Annual Meeting, Washington, DC, November 2015. (pdf)

2014

Daniel B. Neill. Scaling up event and pattern detection to big data. MIT Workshop on Challenges in Big Data for Data Mining, Machine Learning and Statistics, Cambridge, MA, March 2014. (pdf)

Daniel B. Neill. Scaling up event and pattern detection to big data. NYU Stern School of Business, Information Systems Seminar, New York, NY, April 2014. (pdf)

Feng Chen and Daniel B. Neill. Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs. Seventh International Workshop on Applied Probability, Antalya, Turkey, June 2014. (pdf)

Sriram Somanchi and Daniel B. Neill. A star-shaped scan statistic for detecting irregularly-shaped spatial clusters. Seventh International Workshop on Applied Probability, Antalya, Turkey, June 2014. (pdf)

Edward McFowland III and Daniel B. Neill. Discovering novel anomalous patterns in general data. Statistical Learning and Data Mining Meeting on Data Mining in Business and Industry, Durham, NC, June 2014. (pdf)

Seth Flaxman, Alex Smola, and Daniel B. Neill. Kernel space-time interaction tests for identifying leading indicators of crime. Joint Statistical Meetings, Boston, MA, August 2014. (pdf)

Mallory Nobles, Seth Flaxman, and Daniel B. Neill. Urban predictive analytics. INFORMS Annual Meeting, San Francisco, CA, November 2014. (pdf)

Sriram Somanchi, David Choi, and Daniel B. Neill. StarScan: a novel scan statistic for irregularly-shaped spatial clusters. International Society for Disease Surveillance Annual Conference, Philadelphia, PA, December 2014. (pdf)

Mallory Nobles, Lana Deyneka, Amy Ising, and Daniel B. Neill. Identifying emerging novel outbreaks in textual emergency department data. International Society for Disease Surveillance Annual Conference, Philadephia, PA, December 2014. (pdf)

2013

Daniel B. Neill. Fast subset scanning for scalable event and pattern detection. Stony Brook University, Stony Brook, NY, May 2013. (pdf)

Seth Flaxman and Daniel B. Neill. New tests for space-time interaction in spatio-temporal point processes. 2nd Spatial Statistics Conference, Columbus, OH, June 2013. (pdf)

Daniel B. Neill. Machine learning and event detection for the public good. Data Science for the Social Good Summer Fellowship Program, Chicago, IL, July 2013. (pdf)

Feng Chen and Daniel B. Neill. Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs. INFORMS Annual Meeting, Minneapolis, MN, October 2013. (pdf)

Feng Chen and Daniel B. Neill. Non-parametric scan statistics for disease outbreak detection on Twitter. International Society for Disease Surveillance Annual Conference, New Orleans, LA, December 2013. (pdf)

Skyler Speakman, Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. Penalized fast subset scanning. 6th International Conference on Computational and Methodological Statistics, London, UK, December 2013. (pdf)

2012

Daniel B. Neill. Analytical methods for large scale surveillance of unstructured data. International Conference on Digital Disease Detection, Boston, MA, February 2012. (pdf)

Edward McFowland III, Skyler Speakman, and Daniel B. Neill. Fast generalized subset scan for anomalous pattern detection. Sixth International Workshop on Applied Probability, Jerusalem, Israel, June 2012. (pdf)

Daniel B. Neill, Skyler Speakman, Edward McFowland III, and Sriram Somanchi. Efficient subset scanning with soft constraints. Sixth International Workshop on Applied Probability, Jerusalem, Israel, June 2012. (pdf)

Skyler Speakman, Edward McFowland III, and Daniel B. Neill. Scalable detection of anomalous patterns with connectivity constraints. 29th Quality and Productivity Research Conference, Long Beach, CA, June 2012. (pdf)

Daniel B. Neill and Seth Flaxman. Detecting spatially localized subsets of leading indicators for event prediction. 32nd International Symposium on Forecasting, Boston, MA, June 2012. (pdf)

Daniel B. Neill. Predicting and preventing emerging outbreaks of crime. CMU Workshop on Machine Learning and Social Sciences, Pittsburgh, PA, October 2012. (pdf)

Sriram Somanchi and Daniel B. Neill. Fast graph structure learning from unlabeled data for event detection. INFORMS Annual Conference, Phoenix, AZ, October 2012.

Skyler Speakman, Yating Zhang, and Daniel B. Neill. Tracking dynamic water-borne outbreaks with temporal consistency constraints. International Society for Disease Surveillance Annual Conference, San Diego, CA, December 2012. (pdf)

Daniel B. Neill and Tarun Kumar. Fast multidimensional subset scan for outbreak detection and characterization. International Society for Disease Surveillance Annual Conference, San Diego, CA, December 2012. (pdf)

2011

Daniel B. Neill. Spatial scan tips and tricks for practical outbreak detection. Invited webinar for the International Society for Disease Surveillance, January 2011. (pdf)

Daniel B. Neill. Spatial and subset scanning for multivariate health surveillance. Data Fusion Research Meeting, Ottawa, ON, March 2011. (pdf)

Daniel B. Neill. Machine learning for population health and disease surveillance. Advanced Analytics Workshop, Washington, DC, April 2011. (pdf)

Edward McFowland III and Daniel B. Neill. Fast generalized subset scan for anomalous pattern detection in mixed data sets. 17th Conference for African-American Researchers in the Mathematical Sciences, Los Angeles, CA, June 2011.

Daniel B. Neill. Fast multivariate subset scanning for scalable cluster detection. Joint Statistical Meetings 2011, Miami, FL, August 2011. (pdf)

Edward McFowland III and Daniel B. Neill. Efficient methods for anomalous pattern detection in general datasets. INFORMS Annual Conference, Charlotte, NC, November 2011. (pdf)

Sriram Somanchi and Daniel B. Neill. Fast learning of graph structure from unlabeled data for anomalous pattern detection. INFORMS Annual Conference, Charlotte, NC, November 2011. (pdf)

Skyler Speakman and Daniel B. Neill. Dynamic pattern detection with connectivity and temporal consistency constraints. INFORMS Annual Conference, Charlotte, NC, November 2011. (pdf)

Kan Shao, Yandong Liu, and Daniel B. Neill. A generalized fast subset sums framework for Bayesian event detection. Presented at the 11th IEEE International Conference on Data Mining, 2011. (pdf)

2010

Daniel B. Neill, Fast subset scanning for multivariate event detection. ENAR 2010 Annual Meeting, New Orleans, LA, March 2010. (pdf)

Edward McFowland III, Skyler Speakman, and Daniel B. Neill. Fast generalized subset scan for anomalous pattern detection. Sixteenth Conference for African American Researchers in the Mathematical Sciences, Baltimore, MD, June 2010. (pdf)

Daniel B. Neill. Fast subset sums for scalable Bayesian detection and visualization. Fifth International Workshop on Applied Probability, Madrid, Spain, July 2010. (pdf)

Skyler Speakman, Edward McFowland III, and Daniel B. Neill. Scalable detection of anomalous patterns with connectivity constraints. INFORMS Annual Conference, Austin, TX, November 2010. (pdf)

Edward McFowland III, Skyler Speakman, and Daniel B. Neill. Fast generalized subset scan for anomalous pattern detection. INFORMS Annual Conference, Austin, TX, November 2010. (pdf)

Daniel B. Neill, Edward McFowland III, and Huanian Zheng. Fast subset scan for multivariate spatial biosurveillance. International Society for Disease Surveillance Annual Conference, Park City, UT, December 2010. (pdf)

Daniel B. Neill and Yandong Liu. Generalized fast subset sums for Bayesian detection and visualization. International Society for Disease Surveillance Annual Conference, Park City, UT, December 2010. (pdf)

Daniel B. Neill. Research challenges for biosurveillance: the next ten years (invited plenary). International Society for Disease Surveillance Annual Conference, Park City, UT, December 2010. (pdf)

2009

Daniel B. Neill and Weng-Keen Wong. A tutorial on event detection. Presented at the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2009. (pdf)

Daniel B. Neill. Fast subset sums for multivariate Bayesian scan statistics. International Society for Disease Surveillance Annual Conference, Miami, FL, December 2009. (pdf)

Skyler Speakman and Daniel B. Neill. Fast graph scan for scalable detection of arbitrary connected clusters. International Society for Disease Surveillance Annual Conference, Miami, FL, December 2009. (pdf)