J. Scott Semel

Senior Principal Analyst

Dr. Semel has 20 years experience in projects using operations research, bayesian analysis, and machine learning.  He is currently analyzing cyber threats to DoD networks.  He performed cyber threat fingerprint analysis using regex, did network threat reconnaissance in the Cyber Threat Assessments Division, and wrote reports and tippers on malicious activity. He automated tradecraft analytics for a cyber threat reconnaissance team and was a member of Joint Cyber Threat Detection and Warning Cell tasked to help characterize and automate tradecraft analytics. This incorporated finding methods to reduce false positives and coordinating knowledge bases between the Malicious Activity Discovery Division, the Cyber Threat Assessments Division, and Operations. He trained analysts in the use of Netflowviz to discover and visualize DDoS and other malicious activity. He wrote cyber-threat assessments on cloud computing, air-gap jumping vectors, supply chains, and cross-domain solutions. He did Cyber Intelligence Preparation of the Environment (CIPE) and center of gravity analysis on multiple assessments and provided visualization support through Analyst’s Notebook and NetViz. He developed cost/benefit tools for portfolio management of military and DoD lab technologies.  He created FBI threat rankings for agent resource allocation using decision analysis software. He supported exercise Terminal Fury with Extend simulation modeling of IOJMEMS factors. He supported creation of new risk assessment tool for CNSS with prioritization of NIST controls against multiple adversaries for CND. He developed geospatial data mining code using MATLAB with C-compiler, fuzzy logic, statistics, optimization, and mapping toolboxes and developed classification techniques based on association rules, artificial neural networks, decision trees, and logistic regression. He evaluated hypothesis generation techniques that use association rules, Galois lattices, and artificial intelligence techniques. He directed summer research of AFIT and NPS graduate students for new methods in effects-based targeting. He investigated the use of Hidden Markov models versus neurodynamic programming to code KEDS world event data and modeled lines of communications vulnerabilities for various military exercises.  He directed development of a time-expanded quickest transshipment algorithm to model network interdiction of military convoys. He developed method and code using deconvolution of brain potential maps with statistical and decision analysis on patients with mild traumatic brain injury versus normal patients and adapted the method to solve for source location of aerial contaminant release through the backward heat equation.


Ph.D., Applied Mathematics, University of Louisiana at Lafayette, 1997
M.S., Applied Mathematics, University of Louisiana at Lafayette, 1992
B.A. Mathematics, University of Southern California, 1988

Selected Publications and Presentations

G. Carstens, M. King, S. Semel, M. Horejs, “Methodology for Enhancing the Pre-Activation Survivability (PAS) Calculation in the Effects Expectancy (EE) Framework, “presented at 74th MORSS, 2006.

R.D. Sidman, J.S. Semel, T.D. Lagerlund, and M.R. Ford, “The Effect of Reference-Electrode Choice on the Spatial Resolution of Topographical Potential Maps in the Discrimination of Deep Cerebral Sources,” J. Neuroscience Methods, 68 (1996) 175-184.

R.D. Sidman, C.H. Chu, T.D. Lagerlund, and J.S. Semel, “Computing Environment and Tools for Network-Based Interactive Neuroscience Data Visualization,” (abstract) J. Clin. Neurophysiology, 13 (1996) 440-441.

J.S. Semel, R.D. Sidman, L. Ke, and T.D. Lagerlund, “The Effect of Noise in Scalp-Recorded EEG and EP Data in Approximating Voltages on the Cortical Surface,” (abstract) J. Clin. Neurophysiology, 13, (1996) 453.