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Hussain Kazmi

Hussain Kazmi is currently an FWO postdoctoral research fellow at KU Leuven, where his research is at the intersection of machine learning, optimal decision making and energy. His core area of expertise lies in developing algorithms that integrate domain expertise and downstream task information into data-driven models for smart(er) energy systems. Very recently, this research work has received the annual award of the International Institute of Forecasters. Currently, he leads a cross-European EIT InnoEnergy working group aimed at developing a data science program for energy engineers.

He holds a PhD at the intersection of data science and energy engineering from KU Leuven (2019), as well as MSc degrees in Sustainable Energy Technology, and Energy and Nuclear Engineering from Technical University of Eindhoven (The Netherlands) and Politecnico di Torino (Italy) respectively. In 2021, he was a visiting research scholar at KTH Royal Institute of Technology (Sweden). As the first data scientist at two different Belgian clean energy startups (Enervalis and iLECO), he has also helped set up data science teams in applied settings.

Domain/sector

  • Energy & Utilities

Organisation

courses

Data Science for Energy Engineers

course - Leuven - InnoEnergy

The control room of the future: AI empowered dashboards

Study day - Ghent - VAIA, UGhent & On Track Lab