Bernhard Scholz

Professor Bernhard Scholz is a faculty member in the School of Computer Science at the University of Sydney. He specializes in compiler optimization, static program analysis, Datalog systems, blockchain technology, and parallel processing. His research focuses on improving compiler efficiency, analyzing complex programs, and developing tools for smart contract security.

He holds a professorial position and has been involved in significant projects like the Fantom blockchain partnership, which funds specialized blockchain research. His work includes developing the Soufflé Datalog compiler and tools like MadMax for smart contract analysis.

Research interests span compiler design, formal verification, distributed systems, and energy-efficient computing. His recent work emphasizes blockchain security, Datalog scalability, and parallel execution optimization. Notable contributions include EVMTracer for Ethereum analysis and Julia Cloud Matrix Machine for cloud-based matrix computations.

Key grants include ARC Discovery Projects on heterogeneous systems and smart contracts. Awards include industry partnerships and sustained research funding. He advises on large-scale program analysis and has collaborated globally with institutions like ETH Zurich and Fantom Foundation.

Labs and collaborations include the University of Sydney's Blockchain Lab and Fantom-funded projects. His work bridges theoretical compiler research with practical applications in security and distributed systems.