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About Mohammad
Dr. Mohammad Goudarzi is a Lecturer (equivalent to Assistant Professor) in the Department of Software Systems and Cybersecurity, Faculty of Information Technology at Monash University, where he joined in July 2024 and organizes the SSC Seminars series. Previously, he was a Senior Research Associate at UNSW Sydney and the Cybersecurity CRC from January 2023 to July 2024, leading an IoT data security project in collaboration with Cisco. Goudarzi earned his PhD in Computer Science and Engineering from the University of Melbourne in June 2022, focusing on energy and time-aware scheduling of applications in edge and fog computing environments. His doctoral thesis received the IEEE TCCLD Outstanding PhD Thesis Award and the IEEE TCSC Outstanding PhD Dissertation Award in 2022. He also holds the Oracle Cloud Architect of the Year Award (2022), IEEE Outstanding Service Award (2021), Monash Faculty Education Excellence Award for FIT5225 Cloud Computing and Security (2023), and was selected as one of the top 200 young computer science and mathematics scientists by the Heidelberg Laureate Forum in 2024. Goudarzi teaches units including FIT5225 Cloud Computing and Security and FIT5202 Data Processing for Big Data, and supervises PhD students in areas such as AI-driven resource management for distributed systems.
Goudarzi's research centers on distributed systems and algorithms, cloud/fog/edge computing, Internet of Things, applied machine learning, and applied security. He develops advanced frameworks like FogBus2 for resource management and reinforcement learning techniques for scheduling and service offloading in edge environments. Key publications include "Deep Reinforcement Learning-based scheduling for optimizing system load and response time in edge and fog computing environments" (Future Generation Computer Systems, 2024), "μ-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog Computing Environments" (IEEE Transactions on Services Computing, 2024), "A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments" (IEEE Transactions on Mobile Computing, 2023), "Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions" (ACM Computing Surveys, 2022), and "iFogSim: An extended iFogSim Simulator for Mobility, Clustering, and Microservice Management in Edge and Fog Computing Environments" (Journal of Systems and Software, 2022). His research has been featured in the Australian Financial Review, highlighting its impact on sustainable computing.
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