George’s background is in genomics and data science. He received his bachelor's degree from the University of Pennsylvania, and his doctorate from Yale University. Following an academic career, he began his career at NIH in 2009 with NIGMS. In 2011 George was appointed as Director of the newly formed Office of Portfolio Analysis in DPCPSI, and now leads a team of analysts, data scientists, and software developers to enable data-driven decision-making.
Sharon is a Communications professional with 28 years of experience at NIH. She provides the Office with expert administrative support and invaluable institutional knowledge of NIH. She is the primary contact for OPA and secretary for Dr. Santangelo. She handles all administrative issues in order to keep the Office moving forward.
Harry is a software developer with a background in data analysis and Natural Language Processing. As an undergraduate he studied how NLP techniques can identify themes in historic and literary documents. Harry brings his experience in the digital humanities to help with portfolio analysis at OPA. He also has experience with website development and database management from his time working as a full-stack engineer.
Kirk's background is in text and data mining, statistical machine learning and natural language processing; for OPA he works as a programmer/scientific analyst, writing software that helps the office analyze large amounts of disparate data efficiently. Typical projects involve automatically linking NIH grants to external data sources, biomedical text mining, and author resolution.
Matt's background is in software engineering with a focus on natural language processing, information retrieval, and machine learning. At OPA, he works on the development of a variety web applications, web services, and batch computations. Typical projects include citation resolution and linking, classifying grants via machine learning, and working on the iSearch web application.
Shannon's academic background is in international political science, English, and biology. She supports the software development team testing iSearch applications and writing documentation.
Paula is our training program director, an analyst, and a problem solver with a background in biochemistry and cell biology. She provides guidance in the use of portfolio analysis methods and tools, and consults with NIH staff to find effective solutions to their portfolio analysis questions. Paula is typically involved in trans-NIH analyses, training activities, and coordinating the use of OPA tools across NIH.
Patricia’s background is in Clinical Endocrinology and Molecular Biology. She worked for 7 years at NIH as part of the intramural program before joining OPA in 2014. As part of the training team, Patricia coordinates and organizes OPA classes and workshops, teaches portfolio analysis tools and methods to NIH staff, and develops case studies, video tutorials, and other resources to share with the NIH community. She participates in analyses requested by NIH senior leadership, and coordinates trans-NIH activities.
Ehsan’s background is in programming. At OPA he develops specialized software for synthesizing large volumes of qualitative scientific information. Ehsan’s programs aim to extract useful information about NIH research programs that can be used to support programmatic decision making.
Rob’s degree is in Biotechnology but his primary role at OPA is developing new data sources for the office. He has worked building enhanced patent and Microsoft academic graph databases, creating automated methods linking source data like patents to existing NIH and other agency grants by mining the federal support sections. Rob is depended on to conduct portfolio analyses and support data collection and data cleansing for other analysts in our office.
Travis’s background is in physics and mathematics, but in OPA his contribution is creating striking visual presentations of data. Travis brings academic experience and expertise in scientific computing, programming, data analysis, algorithms, simulations, research and modeling to OPA. Typical projects include the development of new tools for quantitative portfolio analysis.
Ian’s academic background focused on the self-assembly of neural circuits, first with Dr. Katherine Kalil at the University of Wisconsin-Madison and then in the lab of Dr. Susan Wray at NINDS. Ian develops metrics and tools for research assessment, analyzes trans-NIH research trends and productivity, and conducts workshops for NIH staff on the use of our OPA data science tools. Typical projects include the development of metrics for research assessment and new tools for quantitative portfolio analysis.
Aviva brings a background in Chemistry and Public Policy Analysis to OPA to strengthen our capacity in research design, data gathering and compilation, statistical analysis, econometric modeling, and network analysis. She performs analysis and evaluation for NIH senior leadership and develops methodology for NIH-wide cost per publication estimates. Aviva is currently initiating an effort to situate the NIH within the broader context of biomedical research funding.
Chuck is a graduate of the U.S. Air Force Academy with a background in mechanical engineering, systems engineering and information technology. At OPA he is primarily responsible for specifying, acquiring, and implementing OPA IT infrastructure, adding computational and storage capacity. A recent success was the design and implementation of a complex computing environment (a five server, 150TB Hadoop Computing Cluster) in just six months, with the help of OIT, while the average implementation time is 18 months.
Rebecca’s background is in cell biology, genetics, and biochemistry, with a long-standing interest in science communications. She brings her science writing and editing expertise to OPA, where she prepares data analyses and other developments from the office for external consumption in the form of presentations and written reports. She also manages the OPA website, including The Analyst blog. In addition to communicating about OPA, Rebecca performs portfolio analyses to support programmatic decision-making across the NIH.
Payam’s background is in software engineering and data systems. Payam is integral to the collaborative work between OPA and ODP involving the development of an advanced machine learning architecture to efficiently classify prevention research across the NIH portfolio. He also contributes to the development of iSearch as well as assisting OPA teammates with their day-to-day data and analytics needs.
Matt has a background in mathematics and statistics and has previously spent 14 years working for the Government Statistical Service in the United Kingdom. Matt works as a statistical portfolio analyst using a range of NIH tools and statistical software to better understand research portfolios. Typical projects include analysis of researcher specialties, tribal health research and analysis of training activities as well as identifying new and innovative ways to present data.
This page last reviewed on October 5, 2017