Rate My Professor Russell Tsuchida

Dr Russell Tsuchida is a Lecturer in Machine Learning in the Department of Data Science and AI within the Faculty of Information Technology at Monash University. He earned his PhD in probabilistic machine learning from The University of Queensland in 2020. After completing his doctorate, he joined Data61 under a CSIRO Early Career Researcher Fellowship and advanced to Research Scientist in 2022. Tsuchida's research focuses on advancing core probabilistic machine learning methods, including Bayesian neural networks, Gaussian processes, density estimation modeling, and uncertainty quantification. He publishes regularly in top-tier venues such as NeurIPS, ICML, ICLR, AAAI, UAI, and AISTATS. Key publications include 'Squared Neural Families: A New Class of Tractable Density Models' (NeurIPS 2023, spotlight award), 'Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions' (UAI 2019), 'Invariance of Weight Distributions in Rectified MLPs' (ICML 2018), 'Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families' (AAAI 2024), 'Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach' (WACV 2024), and 'Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey' (IEEE TPAMI 2024). His work on 'Label Distribution Learning using the Squared Neural Family on the Probability Simplex' appeared in UAI 2025 proceedings. Tsuchida's contributions have garnered over 300 citations on Google Scholar.

As a DECRA fellow, Tsuchida leads the project 'Universal uncertainty quantification using deep learning' from 2026 to 2029. He serves as an action editor for Transactions on Machine Learning Research (TMLR) and reviews for leading conferences, receiving awards from NeurIPS, ICLR, AISTATS, and TMLR. His collaborations have secured over $900,000 in funding. Tsuchida teaches courses including FIT1059 and ADS2002 in Semester 2, 2025, and supervises PhD students on topics like probabilistic modeling and uncertainty quantification. He contributes to Monash's Environmental Informatics Hub and maintains an active presence in the machine learning community through high-impact research and service roles.