Rabab Haider
Postdoctoral Fellow
AI4Opt Institute and GeorgiaTech ISyE
Hello! I am a Postdoctoral Fellow at the NSF Artificial Intelligence Research Institute for Advances in Optimization and GeorgiaTech School of Industrial and Systems Engineering, and an incoming Assistant Professor at the University of Michigan Ann Arbor.
My research explores the design and operation of energy systems under deep decarbonization. I develop tools in the domains of physics-informed machine learning, distributed intelligence for grid-edge devices, and the design of future electricity markets.
I was previously a MIT Energy Fellow (2022), MathWorks-MIT Mechanical Engineering Fellow (2021), and received the Hansen Fellowship (2018). In recognition of my research and community contributions to sustainability, I have been awarded the Raj V Tahil Fellowship Fund Award (2021) and Aarav Amar Bajpayee Memorial Prize (2023).
Latest news and announcements!
03/2024 Congrats Sam and Amanda on our new paper at the ACM e-Energy conference! In this work we quantify the equity of optimal power flow solutions through the Locational Marginal Burden.
03/2024 As we approach World Water Day (March 22) I was interviewed by GeorgiaTech ISyE to discuss my research on sustainable energy systems.
"Haider’s work underlines the critical importance of collaborative efforts and systemic thinking in shaping a sustainable future, emphasizing that progress and environmental responsibility must advance hand in hand for the benefit of all."03/2024 I was pleased to give a seminar at the Ralph O'Connor Sustainable Energy Institute (ROSEI) at Johns Hopkins University
02/2024 I was pleased to give a seminar at the University of British Columbia
02/2024 I was pleased to give a seminar at the Energy Systems Innovation Center (ESIC) at Washington State University
02/2024 I was pleased to give a seminar at the University of Michigan
02/2024 Our paper on graph neural networks for power systems has been accepted to the Power Systems Computational Conference! We are looking forward to attending the conference in Paris this summer.
10/2023 Attending the INFORMS Annual Meeting in Phoenix! Had a wonderful time connecting with colleagues and had some great conversations on my presentation on physics-informed ML and differentiable end-to-end learning for power systems.
10/2023 Pre-print Alert! Checkout our new work on graph neural networks for power system reconfiguration! We're continuing to push in the direction of physics-informed machine learning for mixed integer problems applied to power systems. This work was done in collaboration with Jules Authier, and is a key result of his masters thesis. Physics-Informed graph neural network for dynamic reconfiguration of power systems.
We are featured in the July edition of Microsoft Research's Research Focus Blog, on Twitter and LinkedIn!
Read more about our Nationwide Distributed Energy Resource Modeling modeling project and reach out to get involved in our data consortium
07/2023 Attending the 6th UI-ASSIST Annual Meeting and PES General Meeting in Orlando, to present my research in smart distribution grids: electricity market design, storage integration, and distributed grid services.
06/2023 Publication Alert! Join me at the ACM e-Energy workshop on Energy Data and Analytics where I'm presenting our paper on a project-driven DER dataset for the US grid. This work is a result of my internship with Microsoft Research and in collaboration with Breakthrough Energy.
06/2023 Our new Technical Report on the Behind-The-Meter Distributed Energy Resources is now available on the IEEE PES Resource Center! Our contributions on emerging market and business models, and future needs via interactions with policymakers can be found in Chapters 6 and 7.
05/2023 I'm chairing a session at the IISE Annual Conference on Machine Learning in Energy Systems Analysis and will be presenting my research in physics-informed ML for power systems.
05/2023 I was awarded the Aarav Amar Bajpayee Memorial Prize in recognition of my research contributions to sustainability.
05/2023 Pre-print Alert! Physics-informed machine learning for power systems reconfiguration: Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems.
03/2023 Publication Alert! Our new survey paper on voltage regulation is now available!
01/2023 Join me for the Young Scientists Lecture in the Energy Visions Seminar series: I'll be discussing our work on retail electricity market design.