Görkem Pacaci

My research focuses on program synthesis, particularly applying it to Interpretable Machine Learning. This kind of machine learning aims to have transparent models that people can reason about, as opposed to opaque models built by more conventional techniques. The program synthesis techniques we apply and develop come from inductive synthesis of compositional relational logic programs, a specialized form of definite clause programs bringing algebraic properties.