Abolfazl Rahimnejad

Abolfazl Rahimnejad is a Postdoctoral Fellow in the TCDT Lab, where his research focuses on developing schema-agnostic federated learning using encoder-based representations and transformer architectures to enable collaborative learning across heterogeneous, structurally mismatched datasets, which is an emerging challenge in large-scale distributed systems.

Before joining TCDT, he was a Postdoctoral Research Associate with the Intelligent and Cognitive Engineering (ICE) Laboratory at McMaster University, working on data-driven state estimation, safe reinforcement learning, and robust optimization for smart-grid and energy-system applications.

Abolfazl holds a PhD in Engineering Systems & Computing from the University of Guelph / McMaster University. He has published on robust nonlinear filtering strategies, state estimation, smart-grid optimization, and data-driven resilient operation and control of smart systems, and brings broad experience across smart grids, machine learning, and cyber-physical systems, supported by strong computational, simulation, and practical expertise.

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