Technical Advisory Board


Raymond R. Shoults, PhD, SM, IEEE

Ray is Emeritus Professor of EE, having retired from UTA in August 2008 after serving 33 years in academia. He served as Director of the Power System Simulation Laboratory (PSSL) at the Energy Systems Research Center from 1989 to 2001. He served as Director of the Office of Sponsored Projects from 1991 through 1994 and as Associate Chairman of the Department of Electrical Engineering duringthe1994-95 academic year. He served as EE Department Chairman from 2001 through 2008. His areas of research interest include application of intelligent control concepts to Advanced Automatic Generation Control and Advanced Load Frequency Control methods, and development of Power System Simulation software.

Darvin Schmidt, MBA

Darvin is a global, multi-lingual (English, German) operations and finance leader known for solving complex operational & financial scalability challenges, assembling collaborative teams and leveraging analytical tools and all available company assets.

He has launched, grown and exited startups, performed corporate recapitalizations and built teams that closed $700M in transaction value representing 35 public equity offerings, mergers & acquisitions and private placements for the Healthcare, Real Estate and Technology sectors while working for Arthur Anderson, Salomon Brothers, Southwest Securities and the FDIC, among others.


James Saikin, J.D.

Dr. Saikin is a Consulting Manager with C-suite experience in fast paced global enterprises and high-growth innovative technologies. A legally trained technologist, he consults on international strategic imperatives and business applications in financial/capital markets and Blockchain.

James is an expert in the development and monetization of new emerging technologies. He is a Speaker traveling for the Institute for the Certification of Computing Professionals (ICCP) speaking on Blockchain Strategic Value and Business Implications and other Emerging Technologies (such as, AI, Deep Learning, Machine Learning and Data Science Data Structure Principles and Management).