Professional Experience

I am a statistician and an engineer working on the Data Science component of diverse projects (e.g., global security, climate, nonproliferation) relevant to national security.

Prior to joining LLNL as a staff member, I was a Research Scientist (NATO International Civilian) in the Maritime Security Program at NATO Science & Technology Organization-CMRE where I performed big data analytics for maritime situational awareness under a research Navy Grant sponsored by the Office of Naval Research Global. The main output of the research, called TREAD (i.e., Traffic Route Extraction and Anomaly Detection) architecture was awarded at the 16^th International Conference on Information Fusion and, with more than 200 citations, the related paper published in 2013, has become a reference work in the field. TREAD is an unsupervised learning methodology able to extract patterns of life from massive heterogeneous spatiotemporal data of ships at sea, thus enhancing route prediction and anomaly detection.

As a Fulbright scholarship recipient, I was a post-doctoral Research Scholar in Bayesian process control at the University of Washington, Seattle in 2011. During 2009–2011, I worked as a research associate in the area of Statistics for Experimental and Technological Research at the University of Naples Federico II, Italy. I obtained my Ph.D. in Applied Statistics in Aerospace, Naval and Quality Engineering from University of Naples Federico II-Italy in 2009, supervised by Professor Pasquale Erto, with a dissertation on Bayesian control methods for non-Normal stochastic processes.

Research Interests

Bayesian inference, statistical modeling, Big Data, machine learning, anomaly detection, reliability theory, statistical process control, situational awareness, information fusion for surveillance and security applications.

Professional Memberships

• Professional Engineer
• International Society of Information Fusion
• International Cartographic Association commission on Location-Based Services

Last update: October 21^st, 2018

Post-doc Fulbright Scholar, University of Washington, Seattle-WA US, 2011

Ph.D., Applied Statistics, University of Naples Federico II, Italy 2009

M.S., Industrial Engineering, University of Naples Federico II, Italy, 2005

• Santer B. D., Po-Chedley S., Zelinka, M., Cvijanovic I., Bonfils C., Durack, P., Fu Q., Kiehl, J., Mears, C., Painter, J., Pallotta, G., Solomon, S., Wentz, F., and Zou C.Z. Human Influence on the Seasonal Cycle of Tropospheric Temperature, 2018, Science, vol. 361, 6399
• Riveiro M., Pallotta G., Vespe M. Maritime Anomaly Detection: a review, Wiley Journal WIREs Data Mining and Knowledge Discovery, 2018
• Anguedaz V., Pallotta G., Vespe M Maritime Traffic Networks: From Historical Positioning Data to Unsupervised Maritime Traffic Monitoring, IEEE Transactions on Intelligent Transportation Systems, 99, pp. 1-11, 2018
• Pallotta G., Konjevod G., Cadena, J., Nguyen, P., Context-aided analysis of large evolving networks, Statistical Analysis and Data Mining: The ASA Data Science Journal , 2017
• Santer B. D., Fyfe J. C., Pallotta G., Meehl G.A., England M. H., Flato M., Hawkins E., Mann M.E., Painter J., Bonfils C., Cvijanovic I., Mears C., Wentz F., Po-Chedley S., Fu Q., and Zou C.Z., Causes of differences in model and satellite tropospheric warming rates, Nature Geoscience, 10, pp. 478–485, doi:10.1038/ngeo2973, 2017
• Santer B. D., Solomon S., Pallotta G., Mears C., Po-Chedley S., Fu Q., Wentz F., Zou C.-Z., Painter J., Cvijanovic I., and Bonfils C., Comparing tropospheric warming in climate models and satellite data. Journal of Climate, 30, 373–392, doi: 10.1175/JCLI-D-16-0333.1, 2017
• Erto P., Pallotta G., Palumbo, B., Mastrangelo C., The Performance of Semi-empirical Bayesian Control Charts for Monitoring Weibull Data, Quality Technology and Quantitative Management, Special Issue on Shewhart Control Charts – pp. 1-18, 2017
• Erto P., Pallotta G., and Mastrangelo C., A Semi-empirical Bayesian chart to monitor Weibull percentiles, Scandinavian Journal of Statistics, 42 (3), pp. 701–712. ISSN 1467-9469, 2015
• Pallotta G., and Jousselme A-L. Data-driven detection and Context-Based classification of maritime anomalies, Proc. Int. Conf. on Information Fusion (FUSION), 2015
• Jousselme A-L., and Pallotta G. Dissecting uncertainty-based fusion techniques for maritime anomaly detection, Proc. Int. Conf. on Information Fusion (FUSION), 2015
• Millefiori L., Pallotta G., Horn, S., Braca P., and Bryan K. Validation of the Ornstein-Uhlenbeck Route Propagation Model in the Mediterranean Sea, Proc. IEEE OCEANS Conf., 2015
• Fabbri T., Vicen R., Grasso R., Pallotta G., Millefiori L., and Cazzanti L. Optimization of surveillance vessel network planning in maritime command and control systems by fusing METOC & AIS vessel traffic information, Proc. IEEE OCEANS Conf., 2015
• Cazzanti L., and Pallotta G., Mining Maritime Vessel Traffic: Promises, Challenges, Techniques, Proc. IEEE OCEANS Conf., 2015
• Pallotta G., Horn, S., Braca P., and Bryan K. Context-Enhanced Vessel Prediction Based On Ornstein-Uhlenbeck Processes Using Historical AIS Traffic Patterns, Proc. Int. Conf. on Information Fusion (FUSION), 2014
• Pallotta G., Millefiori L., and Bryan K. Operational Use of SAR Imagery for Enhancing Maritime Anomaly Detection, Proc. Int. SAS/SAR Conf., Institute of Acoustics, 2014
• Anguedaz V., Pallotta G., and Vespe M. Automatic Generation of Geographical Networks for Maritime Traffic Surveillance, Proc. Int. Conf. on Information Fusion (FUSION), 2014
• Anguedaz V., Pallotta G., and Vespe M. Unsupervised Maritime Pattern Analysis to Enhance Contextual Awareness, Proc. First Int. Workshop on Context-Awareness in Geographic Information Services CAGIS (in conjunction with GIScience), 2014
• Pallotta G., Vespe M., and Bryan K. Vessel Pattern Knowledge Discovery from AIS Data: a framework for Anomaly Detection and Route Prediction. Entropy, Big Data, 15(6), pp. 2218-2245, 2013
• Pallotta G., Vespe M., and Bryan K. Traffic knowledge discovery from AIS data, Proc. Int. IEEE Conf. on Information Fusion (FUSION), LeCadre Best Tech. Paper Award (first runner-up), 2013
• Pallotta G., Vespe M., and Bryan K. Traffic Route Extraction and Anomaly Detection from AIS Data, Proc. COST MOVE Workshop on Moving Objects at Sea, 2013
• Vespe M., Pallotta G., Visentini I., Bryan K., and Braca P. Maritime Trajectory Mining for Anomaly Detection, Proc. NATO Port and Regional Maritime Security Symposium, 2013
• Pallotta G., and Palumbo B. New approach to the identification of the Inverse Weibull model, Proc. 25^th Scientific Meeting of the Italian Statistical Society, 2012
• Erto P., and Pallotta G. A New Control Chart achieved via Innovation Process Approach, in Statistics for Innovation, Springer-Verlag, pp. 233–245. ISBN 978-88-470-0814-4, 2009
• Erto P., Pallotta G., and Park S. H. An example of Data Technology product: a control chart for Weibull processes, International Statistical Review, 76 (2), pp. 157–166, 2008
• Erto P., and Pallotta G. A control chart of the Weibull percentiles via Bayesian - Bootstrap approach, Proc. Int. QMOD Conf., 2008
• Erto P., and Pallotta G. A new control chart for Weibull technological processes, Quality Technology and Quantitative Management, 4 (4) pp. 553–567. ISSN 1684-3703, 2007
• Erto P., and Pallotta G. A Bayesian Cumulative Memory control chart for Weibull processes, Proc. Int. QMOD Conf., 2006

Recent presentations

• Improving predictions of radiological surface contamination uncertainty via an ensemble of simulations, Inaugural Data Science Workshop 2018, Livermore-CA US
• Maritime Anomaly Detection Data and Methods: a review, invited speaker at 2018 CoDA conference
• Analysis of community evolution in networks, 2016 Joint Statistical Meeting , Chicago-IL US
• Community detection in traffic networks, 2016 CoDA conference

NATO Technical reports

• Millefiori L., Braca P., Pallotta G. and Bryan K. (2015) Stochastic motion model for maritime traffic, NATO UNCLASSIFIED, CMRE-FR-2015-008
• Jousselme A-L., Pallotta G., Locke J. (2015) A risk game to measure the impact of information quality on human threat assessment and decision making, NATO UNCLASSIFIED, CMRE-FR-2015-001
• Pallotta G., Vespe M. (2014) Vessel Traffic Dataset from ground-based AIS Receiver Castellana: description and use, NATO UNCLASSIFIED, CMRE-DA-2014-001
• Pallotta G., Visentini I., Bryan K., Horn, S. (2013) The NEREIDS project for enhancing maritime surveillance with space-based observations, NATO UNCLASSIFIED, CMRE-FR-2013-024
• Pallotta G., Vespe M., Bryan K. (2013) Traffic Route Extraction and Anomaly Detection (TREAD): Vessel Pattern Knowledge Discovery and Exploitation for Maritime Situational Awareness, NATO UNCLASSIFIED, CMRE-FR-2013-001

• LLNL Engineering Directorate Award 2018 (for being both a first author and contributing to multiple publications)
• NATO Appreciation letter, NATO Science and Technology Organization, 2015
• Horizon 2020 Big Data Research grant for DatACRON - Big Data Analytics for Time Critical Mobility Forecasting, European Commission, 2015
• Jean-Pierre Le Cadre best technical paper award (first runner-up), Traffic knowledge discovery from AIS data, Int. Society of Information Fusion, 2013
• Fulbright grant, Research Scholar, United States Department of State, 2011
• International House Federico II research award, 2008