Survey

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Survey

Document related concepts

no text concepts found

Transcript

Sarah LaRocca 621 Washington Blvd Unit 2S Oak Park, IL 60302 Phone: (919) 357-3517 Email: [email protected] Citizenship: United States Skills and Expertise Analysis: regression modeling; machine learning; graph theory; risk and decision analysis; optimization; business analytics; text mining Software: R; Python; Matlab; SAS; SQL; Java; Hadoop; H2O; Trifacta; Tableau; ArcGIS; LaTeX; Linux Subjects: property & casualty insurance; critical infrastructure systems; network reliability; electric power; water systems; energy; environment; public health Education Ph.D., Environmental Systems Engineering, Johns Hopkins University, 2014. M.S., Environmental Systems Engineering, Johns Hopkins University, 2010. B.S., Environmental Science, Highest Distinction, University of North Carolina at Chapel Hill, 2006. Employment Associate Data Scientist, Zurich North America, August 2014–Present. Research Assistant, Dr. Seth Guikema, Johns Hopkins University, August 2008–July 2014. Environmental Scientist, RTI International, Research Triangle Park, NC, July 2006–July 2008. Research Assistant, Dr. Douglas Crawford-Brown, University of North Carolina, May 2004–July 2006. Selected Project Experience Worker’s compensation insurance pricing Served as the data scientist on a team developing models for pricing worker’s compensation insurance. Retrieved approximately 150GB of internal policy and claim data from multiple sources. Munged initial data sources to allow for matching claims with corresponding policies. Transformed data for analysis using a Hadoop-based platform from Palantir with a combination of Java and Palantir’s own domain-speciﬁc ETL language. Interviewed stakeholders (e.g. ﬁeld underwriters, risk engineers, and program managers) to generate initial hypotheses for pricing model rebuild; helped lead subsequent hypothesis reﬁnement and prioritization workshop. Assessed resulting hypotheses for insight potential using methods such as clustering analysis, principal components analysis, and regression modeling. Conducted text mining on claim notes for over 1 million claims to identify miscategorized occupations on claims. Hadoop vendor and software evaluation Attended over two weeks of daily presentations from Cloudera and Hortonworks on their Hadoop platforms. Evaluated offerings from the perspective of a data scientist, with particular focus on data capabilities and integration with statistical and business tools. Participated in grading and ﬁnal selection of a Hadoop vendor for use at Zurich North America. Established best practices within the team for use of open-source tools such as git/Gitlab, R/RStudio, and iPython/Jupyter; provided recommendations to IT for server installation of relevant tools. Sarah LaRocca 2 Network reliability modeling Demonstrated a statistically signiﬁcant relationship between the initial topological characteristics of scale-free networks and their corresponding robustness to both random failures and targeted attacks. Created an algorithm in Matlab to generate large volume of random networks of varying sizes and topological characteristics. Simulated both random failures and targeted attacks in each of these networks, and evaluated network performance after failures. Developed a beta regression model using R to describe network robustness as a function of initial network topology. Used model to accurately estimate network robustness to failures for real-world networks, including a food web and the 9/11 terrorist network. Topological and physical performance modeling of electric power systems Classiﬁed different types of functional models that can be used for risk and vulnerability analysis of electric power systems, and used these models to estimate power system performance. Compared estimates obtained with these models to an AC power ﬂow model. Showed that in general, the greater the inclusion of physical characteristics of the system in a functional model, the better the estimate of the systems actual performance when perturbed. Developed statistical models combining simpliﬁed topological measures to be used as a surrogate for physical ﬂow models for predicting electric power system performance after failures. Nuclear fuel fabrication facility site selection Co-led a multi-criteria decision analysis project to support the site selection process for a Fortune 100 company’s nuclear fuel fabrication facility. Developed framework for analysis, including selecting and deﬁning criteria and structuring the decision hierarchy. Elicited preferences from upper-level management to establish site rankings. Air dispersion modeling and training Conducted air dispersion modeling using EPA’s ISCST3 and AERMOD and NOAA’s HYSPLIT tools in support of multiple human health risk assessment projects for the EPA. Developed an extensive protocol for Native American tribes to use for performing air dispersion modeling in support of multimedia environmental and health impact assessments. Created and facilitated a training seminar on the use of EPA’s AERMOD for employees of the government of Beijing, China in support of air pollution reduction efforts prior to the 2008 Olympic Games. Honors, Awards, and Fellowships SAS and INFORMS Analytics Section Student Analytical Scholarship, 2012. Society for Risk Analysis Engineering and Infrastructure Specialty Group Student Merit Award [paper competition winner], 2011. Society for Risk Analysis Student Travel Award, 2011. Johns Hopkins University Graduate Representative Organization Travel Award, 2011. Chesapeake Water and Environment Student Paper Competition Winner, 2011. National Science Foundation Graduate Research Fellowship, 2010. RTI International Science and Engineering Group Annual Award, 2007. Smallwood Summer Undergraduate Research Fellowship, University of North Carolina, 2005. Phi Beta Kappa, University of North Carolina, 2005. Sarah LaRocca 3 Publications LaRocca, S. and S. Guikema. Characterizing and predicting the robustness of power-law networks. Reliability Engineering & System Safety 133: 2015. LaRocca, S., J. Johansson, H. Hassel, and S. Guikema. Topological performance measures as surrogates for physical ﬂow models for risk and vulnerability analysis for electric power systems. Risk Analysis, 2014. Johansson, J., S. LaRocca, H. Hassel, and S. Guikema. Comparing topological performance measures and physical ﬂow models for vulnerability analysis of power systems. Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference, Helsinki, Finland, June 2012. LaRocca, S., S. Guikema, J. Cole, and E. Sanderson. Broadening the discourse on infrastructure interdependence by modeling the ‘ecology’ of infrastructure systems. Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering, Zürich, Switzerland, August 2011. LaRocca, S. and S. Guikema. A survey of network theoretic approaches for risk analysis of complex infrastructure systems. Proceedings of the International Conference on Vulnerability and Risk Analysis and Management, Hyattsville, MD, April 11, 2011. Francis, R.A., S.R. Geedipally, S.D. Guikema, S.S. Dhavala, D. Lord, and S. LaRocca. Characterizing the performance of the Conway-Maxwell Poisson generalized linear model. Risk Analysis 32(1): 2011.