B. M. — Quantum Computing Profile

Skills

Quantum
Quantum Algorithms · QAOA · Variational Algorithms (VQE) · Adiabatic / Quantum Annealing · Quantum Simulation · Quantum Information Theory · Post-Quantum Cryptography · Qiskit · Cirq · Q# / Microsoft QDK · Azure Quantum · D-Wave (Ocean) · Pasqal

Scientific computing
HPC · MPI · Distributed & Parallel Computing · NumPy / SciPy · Jupyter · Data Acquisition · FPGA · Detector Instrumentation · Low-Latency Systems · Numerical Simulation

Software
Python · Rust · C++ · C · Java · SQL · Design Patterns · Event-Driven Architecture · Microservices · gRPC / REST

Cloud & platform
Azure · AWS · GCP · Hybrid Cloud · Kubernetes · Terraform / IaC · Observability & SRE · FinOps

AI/ML
Machine Learning · TensorFlow · Keras · scikit-learn · GenAI / LLM · RAG & Embeddings · Vector Databases

Non-technical
Technical Leadership · Mentoring · Scientific Communication · Keynote Speaking · Research Publication · English (C2) · German (C2) · Croatian (Native) · French (B2)

About

I started out building readout controllers for a detector at CERN, where the data arrives at 1 TB/s and is not interested in whether you're ready. That's still more or less the job: getting physics and computers to agree on something useful.

PhD in quantum/nuclear physics, then ten years of shipping systems that had to actually stay up — Layer-7 load balancing at AWS, thousands of microservices migrated for tier-1 bank and aviation, an MES platform that Ferrari and Tesla lines run on. And at Microsoft in Dublin working on Azure Quantum, where a fair amount of my time went into explaining that quantum advantage is a schedule, not a slogan.

Hands-on with IBM, Qiskit, Cirq, Q#, D-Wave and Pasqal. Recent work: QAOA applied to medical research, and a deliberately unsentimental benchmark of D-Wave against Google OR-Tools. Keynote at Graz, top-rated session at AI Tour Munich.

I like problems where the physics is hard and the engineering is harder.