Dr. R. Scott Starsman is the Director for Defense Systems with Avineon, Inc. He is responsible for a portfolio of Information Technology projects supporting Defense and Federal customers. He has successfully delivered Machine Intelligence, Knowledge Management, Business Process Modeling, and advanced Geographical Information Systems solutions to demanding customers with complicated technical environments and urgent operational requirements. He is also responsible for the design and development of cutting edge technical solutions to challenging problems and has developed innovative approaches to machinery failure prediction; automated question answering systems; imagery analysis; combat systems interoperability modeling; advanced data analysis; and cross domain data replication to serve coalition partners. He completed a Naval career of 20 years serving aboard the USS CHANDLER and USS MOUNT WHITNEY and in technical leadership positions at SPAWAR, DISA, Task Force Web, and NAVSEA.
Podcasts / Webinars
HDIAC Webinars » Machine-Learning Techniques to Protect Critical Infrastructure From Cybersecurity Incidents or Equipment Incidents
Securing our critical infrastructure is vital to national security. This presentation demonstrates techniques that can be used to detect cyberattacks or equipment failures. A typical industrial control system is used as an example, with data collected to monitor and control the system. Data science techniques to prepare the data for machine learning will be analyzed. Various machine-learning approaches used to detect anomalies due to cyberattacks or equipment failures will be demonstrated and their efficacy discussed.