Helen Paik

Helen Paik is an Associate Professor in the School of Computer Science and Engineering at UNSW Sydney and Research Director of the UNSW–UTS Trustworthy Digital Society initiative. Her research addresses the design and deployment of dependable distributed systems, and asks how the software-engineering disciplines of testing, verification, provenance and compliance can be extended to systems society is now being asked to trust. Her work spans software engineering fundamentals - distributed architectures, data management, and cyber-physical systems - and their application to digital identity, privacy, security, and trustworthy AI. Her current projects run along three connected lines. The first brings software-engineering assurance to machine learning: locating and steering trustworthiness-relevant behaviour in large language models, robustness testing and repair of generative models, watermarking and provenance for AI-generated code, and verifiable evaluation of machine reasoning. The second concerns accountable digital money and tokenised-asset infrastructure: formal verification of settlement finality, the functioning of markets in tokenised real-world assets, and accountable credential disclosure in self-sovereign identity. The third bridges the two, turning regulatory and legal text into executable, checkable constraints so that compliance can be verified rather than asserted. She has published over 140 peer-reviewed papers and led industry-embedded research through Cooperative Research Centres and national programs, partnering with organisations in finance, government, infrastructure, cybersecurity, startups, and digital services. At UNSW she teaches data management and web applications, and leads a group of doctoral and master's candidates working across AI assurance, tokenised finance, and machine-executable compliance. She serves the research community through editorial boards, technical committee leadership, and program chair roles at international conferences. Distributed computing and systems software, Software architecture, Cyberphysical systems and internet of things, Cybersecurity and privacy, Data and information privacy, Automated software engineering, Software testing, verification and validation, Natural language processing, Machine learning