William Pourmajidi

William Pourmajidi has over two decades of experience in software engineering, cloud computing, and data-driven systems. His career spans technical and leadership roles, including network engineering, software development, enterprise architecture, and executive leadership, providing a strong systems-level perspective on complex computing environments.

He holds a PhD and an MSc in Computer Science, with research focused on cloud computing, cloud governance, and cloud monitoring. His scholarly work examines how cloud-native architectures can be designed to be scalable, observable, and governed effectively, with particular emphasis on integrating artificial intelligence and machine learning into governance, monitoring, and compliance frameworks.

William’s academic interests include cloud-native data analytics, cloud-native machine learning, and large-scale data platforms. As an educator, he integrates theory and practice to foster analytical thinking, technical rigor, and practical problem-solving, preparing students to design, analyze, and reason about real-world data and challenges.

Courses taught

Machine Learning, Agile Software Development, SQL Databases, Prescriptive Analytics, SQL Databases, Case Study 1, Capstone Project

Areas of academic interest

Cloud-native data analytics, cloud-native machine learning, AI-driven cloud governance and observability, machine learning in distributed systems, data platforms and analytics architectures

Areas of specialization

Cloud computing and cloud-native architecture, data analytics platforms and pipelines, AI and machine learning for governance, monitoring, and compliance, software architecture for large-scale systems

Professional Certificates and Licences

Cloud+ Certification, Microsoft Certified Professional, Pragmatic Product and Project Management

Awards

• Winner of IBM Project of the year (2024)

Publications

Journals and conference publications

• Pourmajidi, W., Miranskyy, A.
  Logchain: Blockchain-assisted log storage.
  Proceedings of the IEEE International Conference on Cloud Computing (CLOUD).
• Pourmajidi, W., Zhang, L., Steinbacher, J., Erwin, T., Miranskyy, A.
  Immutable log storage as a service on private and public blockchains.
  IEEE Transactions on Services Computing.
• Pourmajidi, W., Zhang, L., Steinbacher, J., Erwin, T., Miranskyy, A.
  Immutable log storage as a service.
  Proceedings of the IEEE/ACM International Conference on Software Engineering (ICSE).
• Islam, M. S., Rakha, M. S., Pourmajidi, W., Sivaloganathan, J., Steinbacher, J.
  Anomaly detection in large-scale cloud systems: An industry case and dataset.
  Proceedings of the IEEE/ACM International Conference on Software Engineering (ICSE).
• Pourmajidi, W., Zhang, L., Miranskyy, A., Steinbacher, J., Erwin, T.
  A reference architecture for governance of cloud-native applications.
  IEEE Transactions on Cloud Computing.
• Pourmajidi, W., Zhang, L., Steinbacher, J., Erwin, T., Miranskyy, A.
  A reference architecture for observability and compliance of cloud-native applications.
  arXiv preprint.
• Sohana, S., Pourmajidi, W., Steinbacher, J., Miranskyy, A.
  CloudHeatmap: Heatmap-based monitoring for large-scale cloud systems.
  Proceedings of the ACM International Conference on the Foundations of Software Engineering.

Book chapter

• Pourmajidi, W., Zhang, L., Miranskyy, A., Steinbacher, J., Godwin, D., Erwin, T.
  The challenging landscape of cloud monitoring.
  In Knowledge Management in the Development of Data-Intensive Systems, pp. 157–189.