Mr. Sickels has extensive experience leading the conceptualization and development of analytic web applications for the DoD and Intelligence Community (IC). His focus is always on ensuring that analytic applications naturally and transparently support analytic thought. He has over 15 years’ experience as a Principal Investigator (PI), Project Manager (PM), and technical advisor for clients in both the IC and DoD.
Prior to joining IDI and as Principal Investigator, Mr. Sickels led the conceptualization, development, and refinement of the Indicators Analysis Tool (IAT), a Bayesian network-based extension of the IC’s “indicators” Structured Analytic Technique. This web application features an innovative and intuitive dynamic visualization of evidential weight (a particular form of log-likelihood ratios) that brings both rigor and a natural transparency to the “indicators” analytic process. He continues to support this effort as a key consultant to his previous employer.
Mr. Sickels served as Project Manager and Principal Investigator on IARPA’s Collaboration and Analyst System Effectiveness (CASE) program. His team’s goal was developing computer-based support for collaborative intelligence analysis. In conjunction with Princeton University, Mr. Sickels developed opportunities to apply Latent Dirichlet Allocation (LDA)-based techniques (a machine learning approach to probabilistic topic and interaction modeling) to inferring opportunities for collaboration and sharing.
As a technical consultant, Mr. Sickels authored reports that provided expert guidance to the IC for their technology portfolio and investment planning processes in three technology areas: Sentiment Analysis, Complex Event Processing (CEP), and User Modeling for Tailored Information Delivery. These reports captured time-phased opportunities for technology adoption and investment, as well as providing extensive background on the technologies’ evolution and technical foundations. They also identified risks, with risk mitigation strategies explicitly incorporated into all recommendations.
M.S., Electrical Engineering, University of Maryland, 1994
B.S. with High Distinction, Systems Engineering, George Mason University, 1992
Invited by the Chief Technology Officer (CTO), Applications Services, Central Intelligence Agency, to present a “CTO Seminar” on Latent Dirichlet Allocation (LDA) probabilistic topic modeling and its potential application to IC analytics. April, 2006.
Sickels, S., Collaboration and Analyst System Effectiveness (CASE) Connect, Final Technical Report. AFRL-RI-RS-TR-2009-68, Air Force Research Laboratory, Information Directorate, Rome Research Site, Rome, New York. March, 2009. (Available at http://goo.gl/6QIdGm, which points to a www.dtic.mil site.)
Sickels, S., User Modeling for Tailored Information Delivery. Commissioned by and presented to the Intelligence Community. August, 2012.
Sickels, S., Complex Event Processing (CEP). Commissioned by and presented to the Intelligence Community. April 2013.
Sickels, S., Sentiment Analysis. Commissioned by and presented to the Intelligence Community. February, 2016.
System and Method for Multi-Perspective Collaborative Modeling; Sickels, et al.; United States 7,895,020; February 22, 2011.