Mr. Morris is an applied statistician with wide exposure to evaluation with interval data. Since joining Demand Side Analytics, he has contributed to a variety of energy efficiency and demand response evaluation projects and supported the development of the IPMVP Option C uncertainty guidelines for the Efficiency Valuation Organization. He is versed in three of the most prominent statistical packages: R, SAS, and Stata, and he has experience translating code from one language to another. He attended the University of Georgia, where he received the Hollingsworth Award for excellence in undergraduate mathematics and received a M.S. degree in Statistics. He currently teaches Statistics at Kennesaw State University. 

Examples of recent projects include: 

• Analysis of NY vehicle registration data (11.9M vehicles) to develop granular forecasts of electric vehicle adoption, including assessing the impact on hourly (8,760) substation load forecasts. As part of this project, he analyzed the rate of vehicle turnover, estimated the historical penetration over time of electrified vehicles, estimated innovation diffusion curves, estimated adoption propensity scores over time, developed 8760 hourly EV load shapes, and assessed the impact of electric vehicle adoption on substation loads. 
• Analysis of peak reduction impacts from smart thermostats. As part of this project, he used 5-minute thermostat run-time data to estimate summer and winter peak load reduction impacts. Helped develop an automated tool that implements the analysis within 24 hours of each event and draft a report that is sent to the client. 
• Audit analysis of seven large scale randomized control trials for home energy reports behavioral interventions in Pennsylvania, designed to encourage energy conservation of electricity. In total, the randomized control trial includes 1.2 million participants and hundreds of thousands of customers in the control groups.