Dimitris Floros is a power systems research scientist working at the intersection of stochastic optimization, probabilistic forecasting, and data-driven decision support. He is currently a postdoctoral researcher at Duke University, developing risk-adjusted energy management and unit commitment methods (ARPA-E project GRACE). Specifically, he is researching the optimal scheduling of electrical power systems under uncertainty.
His research experience includes uncertainty quantification, probabilistic forecasting via scenario ensembles, and stochastic optimization to improve the reliability, affordability, and flexibility of modern power systems. He holds a Ph.D. in Electrical and Computer Engineering (Aristotle University of Thessaloniki) where he researched the theoretical and computational analysis of network data, a research area at the intersection of data analytics, network science, and high-performance computing.
Positions
2022 – current Postdoctoral Researcher, Duke University, Nicholas School of the Environment
2025 - 2026 System Architect (Part-Time Research Consultant), GridSeer Inc.
Education
- 2022 Ph.D. in Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece
- 2016 Diploma (M.Sc.) in Engineering, Aristotle University of Thessaloniki, Greece
Skills
- Modeling & Optimization: Stochastic and robust optimization, machine-learning-based probabilistic forecasting, simulation, and data-driven decision support for power system operations and planning (unit commitment, power flow, congestion/headroom analysis). (
CPLEX, Gurobi, Pyomo, JuMP, Nixtla, PyTorch, scikit-learn) - Scientific Computing: Algorithm design, high-performance and parallel computing, numerical methods, and scalable data pipelines. (
Python, Julia, MATLAB, C/C++, CUDA, MPI) - Software Engineering: Research-to-prototype translation, modular software design, APIs, database integration, and reproducible research workflows. (
Git, Ansible, SQL, Linux/Unix, Docker, CI/CD) - Technology Translation: Bridging research outputs to deployable analytics and decision tools; scoping requirements, validating with stakeholders, and iterating toward operational use.
- Collaboration & Mentorship: Graduate student mentoring, code and manuscript review, cross-disciplinary collaboration with engineers, facilities operators, and policy/legal experts.
- Languages: English (Fluent), French (Intermediate), Spanish (Conversational), Greek (Native)