Saurabh Garg

Dr. Saurabh Garg is a senior lecturer in the discipline of Cyber Security and Systems in the School of Computing Technologies at RMIT University, Australia. He has several years of research experience in cloud computing and published highly cited journal and conference publication. He has conducted research in several areas including distributed systems, cloud computing, applied machine learning and learning analytics. His name is also listed in Stanford/Elsevier Top 2% Scientists List for 2024 [https://topresearcherslist.com/]. Based on this list, he is ranked 30 out of 9581 top researchers in Distributed Computing.

He has more than 120 publications with more than 10,000 citations in a variety of venues including highly cited journals such as IEEE Transaction of Parallel and Distributed Systems, Journal of Network and Computer Applications and ACM Computing surveys and extensively contributed to the development of software technologies such as NetworkCloudSim (https://code.google.com/p/cloudsim/) and IoTSim (https://github.com/mutazb999/IoTSim-Stream/). 

He has also collaborated extensively with international researchers both nationally and internationally in multi-disciplinary projects including bushfire modelling using Cloud, early detection of dementia through hand movements and large-scale bird sound identification. He has supervised more than 12 PhD students to completion excluding several Honour/Master research thesis students.

Before joining RMIT, Dr. Garg worked at University of Tasmania where he worked on building practical solutions integrating principles of distributed systems with machine learning and big data analytics. He has also worked
as a post-doctoral fellow at IBM Research Australia where he gained considerable experience in various research areas particularly stream computing and map-reduce, social media data analysis and genomics for bacterial disease diagnostics. He also worked at the University of Melbourne as post-doctoral fellow and completed my PhD from the same. There he worked on distributed system related paradigms such as Grid and Cloud computing. He also worked at IBM Research India and developed optimized benchmarks of BlueGene/L supercomputer. 

Following are details of some of the key research grants that Dr. Garg is/was part of:

• Internet of Things-based Acoustic Detectors for Proactive Monitoring of Threatened Forest Fauna (2024-2028), Funded by Forest and Wood Products Australia and Industry partners (approx. $510,832
• Cloud Computing Based Service Platform for Bushfire Prediction (2018 - 2021). CSIRO Data61 ($82,393)
• Investigation into Dynamic Reallocation of Computing Resources (2020), Lockheed Martin Australia Pty Ltd ($75,000).
• Machine learning insight generation for the Virtuoso enterprise learning platform (2020) , Viruoso ($17,500)

List of current and previous PhD students: 

• Botirjon Karimov (University of Tasmania), Ecoacoustics with the Internet of Things (current)
• Nasir Muhammad(University of Tasmania), Self Diagnostic Systems for IIoT (current)
• Ankur Lohachab (University of Tasmania), The Logic of Distributed Ledger Technology: A formal study, completed (2024)
• Huang, Zhiqiang (University of Tasmania), Blockchain performance optimization using cloud technology. completed (2023)
• Khizar Khizar (University of Tasmania), Effective IoT Authentication and Authorisation using Blockchain, completed (2022)
• Alexander Samuel Brown (University of Tasmania), Automatic Processing of Large-scale Bioacoustic Data Using Dynamic Workflows, completed (2022)
• Wenli Yang (University of Tasmania), Blockchain-based Decentralized Mechanism for Conversation System, completed (2022)
• Sudheer Kumar Battula (University of Tasmania), Efficient Resource Management for Fog Computing, completed (2021)
• Ujjwal K C (University of Tasmania), Effective Cloud Solutions for Wildfire Management, completed (2021)
• Venkata Satya Narasimha Rama Rao Kaluri (University of Tasmania), Real Time Biodiversity Measurement in Large Bioacoustic Datasets, completed (2021)
• Ranesh Kumar Naha (University of Tasmania), Reliable Scheduling and Resource Allocation for IoT Applications in Fog Computing, completed (2021)
• Mutaz Seleam Mohamed Barika (University of Tasmania), Scheduling Techniques for Efficient Execution of Stream Workflows in Cloud Environments, completed (2020)
• Md Anwarul Kaium Patwary (University of Tasmania), Dynamic Graph Partitioning in Streaming Manner, completed (2020)
• Erfan Aghasian (University of Tasmania), A Privacy-Based Mechanism for Users' Information Scoring and Anonymisation across Multiple Online Social Networks, completed (2019)
• Zeng Xuezhi (ANU, Canberra), Management of Service Level Agreements for Big Data Analytics Applications in Cloud: A Layer-based Study, completed (2019)
• LinLin Wu (University of Melbourne), SLA-based Resource Provisioning for Management of Cloud-based Software-as-a-Service Applications, completed (2014)