Collaboration
Academic and industry partnerships in safe, scalable decision-making for future power systems.
From rigorous methods to real systems
Let’s make flexible energy assets dependable enough to operate the grid.
I work with researchers and practitioners who want to turn uncertainty-aware optimization and safe AI into tools that can be tested, trusted, and deployed.
Start a conversation Ways to collaborate
Two routes, one shared standard of evidence.
Academic partnerships
For research groups working across optimization, power systems, and AI safety.
- Joint papers and grant proposals
- MSc and DPhil co-supervision
- Invited seminars and focused workshops
- International research partnerships
Industry partnerships
For system operators, aggregators, data centres, and technology teams moving from concept to demonstration.
- Flexibility scheduling pilot studies
- Uncertainty-aware operational tools
- Technical workshops and method transfer
- Evidence for investment and policy decisions
Research focus
Problems where collaboration can create leverage.
Safe AI for grid-edge flexibility Distributionally robust optimization DER aggregation and reserves AI data-centre flexibility Equitable energy transitions
Typical outcomes
Work designed to travel beyond the first meeting.
Open-access papers and technical reports.
Optimization and decision-support tools.
Data products and benchmarking workflows.
Joint workshops and dissemination activities.
Have a problem in mind?
yihong.zhou@eng.ox.ac.uk