
Helps students see their full potential.
Always patient, kind, and understanding.
Always fair, constructive, and supportive.
Challenges students to reach their potential.
A true inspiration to all learners.
Dr. Md Anwarul Kaium Patwary serves as a Lecturer in the Department of Computer Science and Software Engineering within the School of Physics, Mathematics and Computing at The University of Western Australia. His academic background includes a BSc (Honours) in Information Technology from Universiti Utara Malaysia, an MSc in Computer Science from Universiti Putra Malaysia, and a PhD in Computer Engineering from the University of Tasmania, completed in 2020 with a thesis focused on dynamic graph partitioning. At UWA, Patwary has progressed through roles including Casual Teaching Fellow and Adjunct Lecturer since November 2019, currently holding the position of Lecturer. He also served as a Visiting Lecturer at Southwest University from December 2023 to December 2023. In addition to research, he contributes to teaching undergraduate units such as CITS2200 Data Structures and Algorithms and CITS2002 Systems Programming, and supervises PhD and higher degree by research students.
Patwary's research interests encompass graph machine learning, graph neural networks, graph partitioning, dynamic graphs, parallel and distributed computing, deep learning, graph theory, and distributed systems. His scholarly output includes 10 research items, such as peer-reviewed articles, chapters, and conference papers, with a total of approximately 399 citations according to Google Scholar. Key publications feature 'First demonstration of early warning gravitational-wave alerts' (The Astrophysical Journal Letters, 2021, 53 citations), which advanced early detection systems for gravitational waves; 'Early Warnings of Binary Neutron Star Coalescence Using the SPIIR Search' (Astrophysical Journal Letters, 2022, 17 citations); 'ADeepWeeD: An adaptive deep learning framework for weed species classification' (Artificial Intelligence in Agriculture, 2025, 6 citations); 'SDP: Scalable Real-time Dynamic Graph Partitioner' (IEEE Transactions on Services Computing, 2021); 'SMOaaS: a Scalable Matrix Operation as a Service model in Cloud' (The Journal of Supercomputing, 2021); and 'Towards secure fog computing: A survey on trust management, privacy, authentication, threats and access control' (Electronics, 2021, 67 citations). These works demonstrate his impact in areas ranging from astrophysics signal processing and secure computing environments to AI applications in agriculture and scalable cloud services.