About Me

I’m Farid, a PhD student in computer science at Linköping University. I do research at the intersection of machine learning and symbolic reasoning.

Publications

Prompt, Prove, Patch: The Neuro-Symbolic Loop for General Policy SynthesisICAPS’26 RIPL

A neuro-symbolic framework that iterates between policy synthesis, formal verification, and patching to produce general, provably correct policies.

A Comparison of Sampling Strategies for Learning PoliciesICAPS’26 RIPL

Evaluating different sampling strategies for learning policies in classical planning, analyzing their effect on policy quality and generalization.

Combining Heuristics and Transition Classifiers in Classical PlanningECAI’25

Integrating learned transition classifiers with search heuristics to improve the efficiency of classical planning algorithms.

Federated Learning for Power Consumption Forecasting in Radio Base StationsMSc Thesis ’23

Applying federated learning to forecast power consumption across radio base stations while preserving data privacy.