Summary
Adam Polak is an assistant professor and theoretical computer scientist with a decade of experience studying fine-grained complexity and learning-augmented algorithms, focused on when classic worst-case guarantees break and how imperfect ML predictions can be harnessed robustly. He combines deep theory with practical problem-solving—previous collaborations include algorithmic work for transport scheduling and internships at Google and EPFL—bringing both rigorous proofs and applied engineering experience. A prolific collaborator who has co-authored papers with over 40 researchers worldwide, he mentors students and organizes workshops to bridge communities. Based in Milan, his work uniquely blends advances in hardness barriers with safe, prediction-augmented algorithm design, informed by postdoctoral stints at premier institutes such as MPI-INF and EPFL.
10 years of coding experience
6 years of employment as a software developer
Krajowy Fundusz na rzecz Dzieci
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Jagiellonian University
Polish, English, German, French