Sebastian operates at a unique intersection of three worlds: academic theory, quantum engineering, and high-stakes financial markets. He is an Assistant Professor at the Faculty of Electronics at the Military University of Technology in Warsaw, where he develops mathematical frameworks applying quantum principles to anomaly detection and advanced data analysis in complex financial environments. He also works as a Quantum Machine Learning Engineer at finQbit.
He is co-creator of Quantum Information Field Theory (QIFT) — an innovative research approach that treats complex data structures as quantum fields, bridging fundamental theory with practical computational models.
At finQbit, he brings high-level theory down to earth — more precisely, onto real quantum processors. He is co-author of the 2026 publication Option Pricing on Noisy Intermediate-Scale Quantum Computers, demonstrating that quantum neural networks (QNNs) executed on next-generation hardware (IBM Fez, IQM Garnet, IonQ Forte, Rigetti Ankaa-3) can successfully model the nonlinear dynamics of options markets.
His interdisciplinary track record spans:
At Q-Con, he demonstrates that the path to quantum advantage in finance does not require perfect hardware — it requires precise alignment between algorithms and the intrinsic noise characteristics of contemporary quantum processors.
