Jacksonville, Florida, United States
Over 20 years experience in research and development, including full lifecycle project building and technology research. Broad based experience with managing multi-agent teams, including academic, military and industry based personnel. Various experience in writing new business technical proposals for projects both large and small ($100K-$250m). Specialties: Demand Side Energy Research, Data Science, Machine learning algorithms, computer vision techniques applied to medical and natural imagery, software development, full life-cycle project management, technical proposal writing. Summary: Available for speaking and teaching opportunites on the subjects of Energy Data Analysis, Energy Efficiency and Community Engagement.
Digitalization is an emerging trend revamping the energy landscape and enabling progress toward continuous energy efficiency improvements. It is argued that digitalization, from its various dimensions, shall be considered as part of policy development to ensure overall net benefit to the system and its participants. The Task Force on Digitalization in Energy was established in 2020, with the 2021-2022 mandate to enable constructive subject-matter technical and policy dialogue to help bridge the gap between academic research, industrial innovations, and policy needs and achieve higher levels of efficiency in the energy system.
Providing thought leadership and strategic insights into Energy Analytics for the Public Power partners at The Energy Authority (TEA). Our mission is to maximize the value of clients' assets in the wholesale Energy Markets. and to be the Strategic Partner of choice in providing Energy Solutions to Public Power.
Leading the research strategy and activities of the core IERC research team, and providing technical oversight of the research programmes. Building the IERC as a knowledge hub in demand side energy efficient solutions and translating industry needs into research ambitions. Creating value chains to accelerate research outcomes into the market.
Developing enabling technologies for smart buildings and campuses, using data-centric and stochastic models for decision support and prediction modeling. Technical point of contact for International Enterprise Research Center Projects to UTRCI, especially focused on the areas of data fusion and diagnostics.
PhD research focused on using machine learning and pattern recognition algorithms to find disease markers in retinal images, clustering behavior to determine tissue disease in ocular fundus images and grouping patterns in natural images.
Responsible for workshop demonstration and student support for approx 130 students per year. Courses taught included: Computer Vision and Robotics (using Matlab toolboxes), Mathematics for computer science, Data Networks and the Web (using C#, Javascript), Database Systems (SQL), Software Engineering (Object-Oriented), Software Development (C# and Java).
Topic: Identification and Segmentation of Retinal Lesions. Developed novel Algorithms to detect, segment and support the classification of disease markers in retinal images of diabetic patients. Developed novel feature extraction algorithms that returned a 98% classification result.