Rate My Professor Matthew McKay

Matthew McKay is a Professor and Australian Research Council (ARC) Future Fellow in the Department of Electrical and Electronic Engineering at the University of Melbourne, serving as Head of the Communications and Networks research group. He holds an additional appointment as Honorary Professorial Fellow in the Department of Microbiology and Immunology and Laboratory Head at the Peter Doherty Institute for Infection and Immunity. Prior to joining the University of Melbourne, McKay was a Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology (HKUST), where he retains an Adjunct Professor position. His career trajectory reflects a transition from core electrical engineering challenges to interdisciplinary applications in computational biology.

McKay's foundational research advanced statistical signal processing and information-theoretic tools for wireless systems, exemplified by seminal work on capacity bounds for spatially correlated Rician MIMO channels published in IEEE Transactions on Information Theory in 2005. Over the past decade, inspired by random matrix methods in vaccine design, he has applied these techniques to model pathogen evolution and engineer vaccines against HIV, hepatitis C virus, dengue, SARS-CoV-2, monkeypox, and influenza viruses. Notable achievements include fitness models of HIV envelope proteins utilized by MIT collaborators for novel immunogens; bioinformatics platforms predicting SARS-CoV-2 T cell epitopes that informed commercial vaccine development; demonstrations of Omicron cross-reactivity by vaccine-induced T cells; evolutionary analyses revealing how HCV Envelope 1 promotes antiviral resistance, published in Nature Communications in 2023; and machine learning tools for seasonal antigenic prediction of influenza A H3N2. Together with collaborators and students, McKay has received multiple paper awards in electrical engineering, including a Young Author Best Paper Award. His scholarship has amassed over 10,000 citations, underscoring profound influence in signal processing, computational immunology, and evolutionary biology.