Erotokritos Skordilis is a postdoctoral researcher in the Complex Systems Simulation and Optimization Group within the Computational Science Center at NREL. His research focuses on the application of model-free and model-based scalable reinforcement learning in the areas of energy efficiency and renewable energy. His current projects include centralized coordination of automated fleets of vehicles and de novo molecular design.
He also has an extensive background in big data analytics with applications in power grid control and health care, as well as in mathematical programming for various operations research applications. Erotokritos received his doctorate from the department of Industrial Engineering at the University of Miami in December 2019. He holds a bachelor's degree in Computer Engineering and a master's degree in Mechanical Engineering, both from the University of Thessaly, Greece.
For additional information, see Erotokritos Skordilis's LinkedIn profile.
Disclaimer: Any opinions expressed on LinkedIn are the author’s own, made in the author's individual capacity, and do not necessarily reflect the views of NREL.
Scalable reinforcement learning
Ph.D., Industrial Engineering, University of Miami
M.S., Mechanical Engineering, University of Thessaly
B.S., Computer Engineering, University of Thessaly
Reviewer, Reliability Engineering and System Safety, Journal of Applied Statistics (2020–present)
Postdoctoral Researcher, National Renewable Energy Laboratory (2020–present)
Data Analyst, Department of Industrial Engineering, University of Miami/Florida Power & Light (2018–2019)
Data Analyst, University of Miami Hospital/Department of Nursing and Health Studies/Department of Industrial Engineering, University of Miami (2016–2018)
Independent Contractor, Kathikas Institute of Research and Technology (2014–2015)
Independent Contractor, InnovECO SA (2014–2015)
Associations and Memberships
Member, Institute for Operations Research and the Management Sciences (INFORMS)
Member, Institute of Electrical and Electronics Engineers
A Deep Reinforcement Learning Approach for Real-Time Sensor-Driven Decision-Making
and Predictive Analytics, Computers & Industrial Engineering (2020)
Autonomous Vehicle Fleet Coordination for Smart Mobility-on-Demand, INFORMS Annual Meeting (2020)
Awards and Honors
INFORMS Quality, Statistics, and Reliability Section Data Challenge Award Winner (2019)