Rate My Professor Max Ward

Dr. Max Ward serves as Adjunct Senior Lecturer in the School of Physics, Mathematics and Computing at the University of Western Australia, within the Faculty of Engineering, Computing and Mathematics. He completed his Bachelor of Science in Computer Science, Bachelor of Science with Honours in Computer Science in 2014, and Doctor of Philosophy in Computer Science in 2019, all at UWA. His doctoral thesis, 'Algorithms for RNA Structure and Related Graphs,' supervised by Amitava Datta and Michael Wise, developed novel algorithms for predicting RNA secondary structures. This included incorporating thermodynamic models previously unused or assumed intractable, proposing new models, tuning parameters with a novel training method, and providing new faster algorithms for circle graphs, polygon-circle graphs, and interval-filament graphs.

Ward's research centers on algorithms, computational biology focused on RNA secondary structure prediction and design, artificial intelligence, and cybersecurity, including evolutionary algorithms for hardening Active Directory graphs and metrics for choke points in attack graphs. His contributions have earned over 1,566 citations on Google Scholar. Key publications include 'Fitness functions for RNA structure design' in Nucleic Acids Research (2023), 'Deep learning models for RNA secondary structure prediction with user-defined constraints' (2022), 'Fast Fourier transform is a training-free, ultrafast, highly accurate model for RNA structure prediction' (2025), 'mRNAfold: Co-optimization of Global Stability, Local Structure, and Codon Choice via Suboptimal Folding' (preprint, 2026), and 'A Scalable Double Oracle Algorithm for Hardening Large Attack Graphs' (2023). He is affiliated with the RNA Innovation Foundry (established 2024) and the Australian Centre for RNA Therapeutics in Cancer as Adjunct Senior Lecturer. Ward was an investigator on the 'Computational Creativity to Cross Cultural Frontiers' project funded by the Department of Foreign Affairs and Trade (2022-2024) and supervises research students in computer science through the UWA Data Institute.