Nashville Metropolitan Area
I have over 10 years of experience in data science, artificial intelligence, machine learning, and cybersecurity, with a focus on solving complex problems and generating actionable intelligence. As the CEO and founder of Sourced Intel, I have designed and developed OSINT Watcher, a best of breed OSINT (Open-Source Intelligence) gathering and process automation system that uses advanced AI tools to analyze raw data and produce actionable intelligence. I also provide training and consulting in AI, advanced analytics, and cybersecurity to various clients, leveraging my extensive technical and domain expertise. Since April of 2018, I have been an Enterprise Data Scientist for the State of Tennessee, where I have led and executed machine learning and AI based projects for facial recognition, acoustic drone detection, sentiment analysis, and other problem domains. I have also marketed new enterprise analytics capabilities, remedied multiple pain points, and demonstrated analytical solutions for various state agencies and IT professionals. I have mentored and empowered other data scientists and IT staff to enhance their skills and performance. My mission is to use data science and AI to create value, innovation, and impact for the public and private sectors.
My position at the State of Tennessee has evolved to a specialty in Artificial Intelligence. The primary change is more focus than title. I have become a technical resource in Artificial Intelligence systems. I'll flesh this out as the role evolves.
Providing data science leadership and advanced analytics capabilities to the State of Tennessee. Work in analytics has included the areas of Artificial Intelligence, Machine Learning, and Mathematical Modeling. Leadership opportunities have included locating customers for and marketing new enterprise analytics capabilities to State Agencies and IT professionals across the State. Using direct contact with agencies and principals, presentations, and speaking to IT and analytics focused groups has resulted in the discovery of multiple pain points within the agencies and thereby the opportunity to demonstrate advanced analytical solutions. An important part of leadership involves mentoring which has resulted in the establishment of a Machine Learning Technical Exchange where advanced analytics projects are dissected with other state analytics professionals. Recognition of the leadership and technology innovation has been provided by the State CIO Mrs. Stephanie Dedmon in nominating Sadler for the Nashville Technology Council 2020 Innovator of the Year Award. Representative Projects: • Selection of toolsets / and models for State wide employee AI based chat working with sensitive State documents • Establishing a Facial Recognition capability for the State. This project was selected by the State CIO as a project to be submitted for the NASCIO Emerging & Innovative Technologies Award, where it was selected as one of the national finalists. • Development of an Acoustic Drone Detection System – Proof of Concept program for the Department of Corrections to identify drones approaching prisons. Designed real time sensors and signal processing software to acoustically detect drones. Recognizing the potential conflict between the State and Citizen led to the parallel creation of an acquisition strategy. The dual aspects of this program is the reason this was the project submitted to the NTC for the 2020 Innovator of the Year award.
Contractor providing Data Science support to the State of Tennessee in the areas of Artificial Intelligence, Machine Learning, and Mathematical Modeling.
Founded Sourced Intel to provide a best of breed OSINT (Open-Source Intelligence) gathering and process automation tool which I designed and developed from the ground up. Additionally, the company utilizes our core competencies to provide training and consulting in AI, advanced analytics, and cybersecurity. The OSINT Watcher product automates the intelligence gathering process. By using advanced AI tools, it can take raw data, perform the analysis of the data, and generate actionable intelligence. The system is entering alpha test as of July 2023.
Founded ValeGreen as a consulting company to commercialize competencies in Machine Learning, Computer Vision, Data Analytics, Mathematical Optimization, GPU Programming, Cyber Security, and autonomous Robotics / Drones. Created an AWS / GPU based computer vision / machine learning pipeline. The system is able to automatically scale within AWS to allow an arbitrarily large volume of real-time image processing requests. The system can identify faces and characteristics of the image that the customer is interested in, process those characteristics, and return multiple image results in real time. The system includes an adaptive categorization of facial characteristics that began with an analysis of several standard facial recognition databases and will adapt on the basis of new data provided by the application. The customer is a global company at the very top of its market segment. Modeled underwater acoustics for a video game that simulated US Navy passive sonar systems for training incoming ASW sailors to recognize submarine signals. Responsibility was primarily mathematical modeling of phased array acoustic sensors in the aquatic environment. Developed plain English search engine with ontologically skewed results. The example was federal acquisition law question and answer system, the idea being ‘solicitation’ should return items like RFPs instead of what is returned by a standard web search engine. Provided security services to several customers (Southwest Airlines, Sony) including penetration testing, information assurance controls establishment and auditing, and application code security review. Researched and developed the principles behind the Fractal Artificial Neural Network (FrANN™) which was then spun off as FnnTEK Inc., a standalone company.
Invented an artificial general intelligence core called FrANN™ (Fractal Artificial Neural Network) and founded FnnTEK, Inc. to commercialize the technology. Developed the proof-of-concept software which was presented to the NSA, resulting in a sponsorship that led to an initial round of funding. NSA’s interest was determining human intent from large collections of unstructured data (handwritten documents, audio and video recordings) and structured sources. Developed a second application called Yannis™ using the FrANN™ core to create an autonomous network security appliance. The system uses a Kohonen Self Organizing Map (SOM) to determine anomalous versus normal data across a network and FrANN™ based intent analysis to determine any malicious intent (or lack thereof) of the anomaly. The system was production ready and in the process of undergoing independent testing by the Department of Homeland Security when funding was cut after the OMB break in incident. Developed the core production FrANN™ technology from proof of concept software, recruited and managed (with agile methods) a geographically disparate development team to create the Yannis™ product. This included the hardware specifications, software design, and production partnerships required to prepare the product for market release.
Instrumental in success of multiple SIPRNET projects to include: Migration of email to virtualized server stack using VMware. Automation of enterprise administrative tasks via custom scripting and programming. Created and administered the SIPRNET NOC SharePoint site. Planned and executed a server consolidation and virtualization effort using VMware, Worked on multiple Level III support issues on SIPRNET and JWICS. Experience: HP Blade Administration, VMware Server Consolidation, C#, VB Script, Network Troubleshooting, CISCO infrastructure, MS Active Directory, Widows Server, SQL Server, and Workstation administration