Gregg Hunter Email & Phone Number

Ashburn, Va, Us

Automation Technology LLC, Ashburn, VA, September 2008 – Present.Technical Project Manager, Software Engineer, supporting Northrop Grumman Projects.-- Most Significant Achievement: Quickly assumed management of system development and deployment of the Army Portfolio Management System (system tracks/manages/reports IT investments, systems, and capabilities) project in mid-stream development, and led the 6-man engineering team through deployment of the final prototype. This effort involved acquiring previously undocumented requirements, competition for very limited development resources, and test/deployment to remote servers/networks where we had limited physical access.-- Acquired and documented software subsystem requirements from various domain experts and resolved requirements conflicts.-- Interface with test team and developers to identify and resolve issues. -- Packaged software for delivery to customer and supervise installation and test.-- Worked programming tasks in Java and Oracle when required to meet deadlines. AI Software Engineer, on the Deepmile Networks, Semantic Modeler/Analyzer System Prototype. -- Most Significant Achievement: Created an automated method to guide Data Extraction from unstructured text and Semantic Network construction using an enhanced Ontology.-- Designed Software for Automated Data Extraction using Java, Jena, AutoMap, and Eclipse.-- Implemented a Social Data Network in Java / HBase and import DyNetML files (XML based representation of Structured Social Network Data) using Open-Source XML libraries.-- Implemented an Ontology Framework in Java and HBase.-- Created OWL ontologies in Protoge, and Integrated Jena (Open-Source OWL data processing library) for importing the ontologies, into our Data Analysis product.-- Created and maintained all test procedures for the middleware layer logic.-- Automated all middleware layer tests using the JUnit testing framework.

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Our Submarine Diagnostics System for NAVSEA utilized Data Mining and Expert Systems technologies to analyze system event data and acoustic signals using Java, Matlab, Jess, Oracle, Weka Windows, and Linux. Most Significant Achievement: Continued to move the project forward despite vague objectives, extremely dynamic requirements, and external challenges in acquiring data for analysis. The Final Acceptance Test was completed on time and within budget.Task Management – estimated, prioritized, assigned, tracked, and coordinated tasks involving data mining, software development, and documentation. The multidisciplinary development team was co-located in 4 different offices, across 3 states.Systems Engineering Tasks – refined vague customer requirements, documented the system design, wrote or reviewed all technical documentation, created and maintained the project work breakdown, and was the technical customer interface. Maintained CMMI Level 3 compliance.Software Engineering Tasks – specified technologies, created system designs in UML, coordinated work between developers, and conducted design and code reviews.Hardware Engineering Tasks – researched, specified, ordered, assembled, and troubleshoot high-performance computer systems for two different job sites.System QA Activities – responsible for test procedures, and Final Acceptance Test Plan.

Falls Church, Va, Us

Mobile Knowledge Management System Prototype, USMC.This innovative product manages a local knowledge-base of lessons-learned and utilizes Web-Services to synchronize and perform data-mining activities on the central repository. This 7-man project used: Java, XML, Hypersonic, SQL Server, Cold Fusion, PKI, Ajax, WSDL, and Magic Draw.--Most Significant Achievement: Turned a doomed project into a major success. The Mobile Lessons Knowledge Management design was selected for fielding throughout the DoD.--Customer interface to the USMC Center for Lessons Learned.--Managed System Requirements and Schedule in an extremely dynamic environment.--Defined the Software Architecture and the Technologies to be employed.--Lead the Software Development Teams, which were co-located across two states.--Responsible for all V&V including the creation and execution of the Final Acceptance Test Plan.--Developed Software Enhancements ( Java ) when the developers were unable to do so.

Falls Church, Va, Us

Responsible for two visualization/collaboration products that were being marketed to external customers. Technologies used: C Sharp, C, Satellite Tool Kit, Remote View, and ESRI products. --Most Significant Achievement: Directly lead the exploration and resolution of a software problem that had persisted for over a year. The elimination of this elusive bug was essential for the survival of our High Definition Projector Array product.--Primary customer contact supporting two different visualization products.--Responsible for Requirements Test Matrix, Procedures, Test Plan and supervising testers.--Provided Systems Engineering support after the resignation of our System Engineer.--Responsible for work breakdown and scheduling for a team of 6 engineers.

Falls Church, Va, Us

Developer on the Analyst Tool Suite, which is a COTS / GOTS products Integration and Data Fusion product. The leveraged technologies were: Java, J2EE, Eclipse IDE, XML, Visual Links, and Oracle.--Support Data Mining and Knowledge Discovery tasks. --Integrate and develop models for Link Analysis visualization tools.--Prototype and provide assessments of new J2EE related frameworks (Struts, etc.). --Review software design and system architecture documents. --Create a database for analysis models.

Chief Technologist for my startup consulting business with concentration in AI Technologies. Consulted on AI Software Projects in the areas of: Expert Systems (software project estimation), Fuzzy Systems (business process automation), and Neural Networks (Machine Learning and Pattern Recognition).

San Jose, California, Us

Project Lead on a computer security R&D project for the Defense Information Systems Agency. This project required generating requirements, design (UML and XML), test plans, and writing software in Java, C++, or delegating work to others. Authored several proposals and white papers in the areas of Computer Security and AI, such as: An Automated Attack Generator using a Bayesian Network and Genetic Algorithm Hybrid, and An Intelligent Agent Based Approach to Enterprise Computing Systems Security.Extended and maintained a Java-based Rule Engine which was the core component within Symantec’s Commercial Enterprise Network Security product. This was a distributed, Intelligent Agent based, Network Security event correlation engine running on Windows and Unix.

Conducted Research and Algorithm Development for Palm Inc. Created an algorithm for a Multi-Objective Decision Support System based on Utility Theory. This system optimized purchasing decisions based on the personality and needs of the user. Integrated the ILOG Rules 7.0 Rule Engine into a C++ / Unix legacy financial application. This Expert System automates the loan scoring process for Fannie Mae.

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Managed a team of 5 Engineers on a one year project to build a commercial satellite health and maintenance activity scheduler. Responsible for requirements, design, scheduling, work breakdown, and CMMI Level 3 compliance. (Used: Process Max SEI Mgt Tool, Java, UML, XML, Rational Rose, Visual Café).Designed and implemented a geo-spatial threat tracking module that identifies deviations in the routine movements of known terrorist organizations. This adaptive system, based on Fuzzy Set Theory, was written in Java and interfaced to other internally developed software.

Lead Engineer on a Network Computer Security project. This system utilized distributed Intelligent Agents and Case Based Reasoning. Responsible for the system design (UML), task estimates, work breakdown, Java / JatLite / C++ implementation, and supervising a developer.Designed and implemented a generic security alert data file parser that focused on simplistic configuration and high data format flexibility. This was written in Java and output XML.

East Hartford, Ct, Us

Software Manager, responsible for scheduling, customer relations, requirements, analysis, design, implementation, V&V, and delivery of Pratt & Whitney’s first commercial jet engine management and diagnostics product. This 5-man, 1-year project was implemented using UML, Java, C++ and CORBA Lead Neural Network R&D Engineer for all of Pratt & Whitney (over 35,000 employees).- Designed a high-speed Jet Engine Compressor Simulation. - Developed an Airfoil Design Optimizer .- Devised a frequency-based algorithm for selecting training data. Designed an auto-configuring jet engine diagnostic data storage and retrieval module. Developed an Automated Jet Engine Failure Simulator. Designed and implemented a Generic Interprocess Communication Service/Library .Worked on the design and implementation of our first Diagnostic Expert System.

Researcher in the area of signal processing.Authored an SBIR proposal that was awarded over 430k dollars from NASA.Developed a trainable system for performing color separations in digital images.

Research and Development in the area of AI while working towards my thesis:An Intelligent System for Noise Removal and Scene Analysis in Digital Images.The ideas and methods utilized in this thesis are original and my own work, such as: * Noise tolerant data coding scheme. * Fuzzy membership function and variables used for pattern matching. * Method for constructing intuitive fuzzy membership functions. * Efficient database design (small size & fast search). * Autonomous noise-tolerant learning algorithm. * Clustering algorithm for error elimination during scene analysis.All the above algorithms were implemented in C.This extensive research, development and implementation effort resulted in a system capable of locating/correcting noise and identifying objects in digital images. The system automatically learns to identify possible random noise by repetitious viewing of pictures containing objects similar to those presented for correcting. The process of identifying noise is done by using fuzzy pattern matching to compare coded image segments to similar structures in a dynamic database. This pattern matching process allows scene analysis to be conducted while noise identification and elimination is in progress.