Milad Hoseinpour
EECS Ph.D. Candidate at the University of Michigan.
About Me
I am a Ph.D. candidate in the Department of Electrical Engineering and Computer Science at the University of Michigan, fortunate to be advised by Prof. Vladimir Dvorkin. I received my M.Sc. and B.Sc. degrees in Electrical Engineering from Tarbiat Modares University and Babol Noshirvani University of Technology, respectively.
Research Interests
My research develops anytime-valid inference methods for real-time decision-making in safety-critical systems. I design sequential tests, e-processes, and confidence sequences that enable reliable detection, diagnosis, and certification, while maintaining rigorous statistical guarantees under continuous monitoring. My work is motivated by applications in power systems, where trustworthy statistical evidence is essential for reliable grid operation.
Feel free to email me if you come across any research interests we may have in common. I am always open to potential collaborations.
news
| Sep 10, 2026 | I presented our work Outage Identification from Electricity Market Data: Quickest Change Detection Approach at the 2026 PowerUp Conference (slides, paper). |
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| Jun 30, 2026 | Our paper, DiffOPF: Diffusion Solver for Optimal Power Flow, has been published online in Electric Power Systems Research (EPSR) as part of the proceedings of the Power Systems Computation Conference (PSCC) 2026. |
| Jun 09, 2026 | I am honored and grateful to be inducted into the 2025–2026 Excellence in ECE Honor Roll in recognition of my contributions to the ECE community. |
| Apr 24, 2026 | The DiffOPF repository is now available online. |
| Apr 07, 2026 | Our paper “Constrained Diffusion Models for Synthesizing Representative Power Flow Datasets” has been accepted for publication in IEEE Transactions on Power Systems ! |
| Jan 27, 2026 | Our paper DiffOPF: Diffusion Solver for Optimal Power Flow has been accepted to the Power Systems Computation Conference (PSCC) 2026. |
| Jan 20, 2026 | Our new paper Outage Identification from Electricity Market Data: Quickest Change Detection Approach has been released on arXiv! |
| Dec 10, 2025 | I am honored to have been selected as a 2026 Fellow in the Institute for Energy Solutions’ PhD and Postdoctoral Fellowship Program. |
| Oct 27, 2025 | I will be presenting at the 2025 INFORMS Annual Meeting in Atlanta: Synthesizing Power Flow Datasets via Constrained Diffusion Models (slides, paper). |
| Oct 15, 2025 | Our new paper DiffOPF: Diffusion Solver for Optimal Power Flow has been released on arXiv! |
| Oct 02, 2025 | I am serving as an Organizer for the 2026 Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS). |
| Aug 25, 2025 | Our new paper Constrained Diffusion Models for Synthesizing Representative Power Flow Datasets has been released on arXiv! |
| Aug 21, 2025 | I began serving as a Leading Committee Member for Academic Careers in ECE (ACE), a group within the EECS Department at the University of Michigan dedicated to supporting Ph.D. students and post-doctoral researchers interested in pursuing future faculty careers. |
| Jun 12, 2025 | Our paper Domain-constrained diffusion models to synthesize tabular data: A case study in power systems is accepted for presentation at the 2025 ICML workshop DataWorld: Unifying Data Curation Frameworks Across Domains (poster). |
| May 21, 2025 | I was honored to receive the Student Poster Competition Award at the Institute for Energy Solutions’ 2025 Energy Symposium. |
selected publications
- arXiv
- arXiv
- EPSRProsumers’ Cost Recovery in Peer-to-Peer Electricity MarketsElectric Power Systems Research, 2024
- TSGPrivacy-Preserving and Approximately Truthful Local Electricity Markets: A Differentially Private VCG MechanismIEEE Transactions on Smart Grid, 2023