My name is Gustavo Batista and I am the head of the Machine Learning group at the School of Computer Science and Engineering at the University of New South Wales.

I have researched machine learning for nearly 30 years, which has given me a comprehensive understanding of the area. I have diverse interests. My previous research concerns data pre-processing and evaluation methods, and I investigated and proposed techniques for missing data imputation, class imbalance treatment, and model assessment. I have recently developed methods to learn from time-oriented data, including time series and data streams.

My research in data streams led me to develop methods that identify changes in data distributions and adapt classifiers to those changes. I have developed methods for label shift detection and adaptation and algorithms to estimate the class prevalence, a machine learning task known as quantification.

While I am passionate about theory, I find it equally exciting to translate these concepts into applications. For example, I developed an optical sensor to identify insect species using wing movement. This technology can be applied to monitor disease-vector mosquitoes with funding from USAID (Zika) and IVCC-UK (Malaria). I have also developed object-detection models that are efficient to execute on nanosatellites’ onboard hardware.

I joined UNSW as an associate professor in 2019 after working for more than ten years at the University of Sao Paulo (USP).

News

• [Oct 2026] PhD opportunity: a fully funded UNSW Scientia PhD Scholarship on Multimodal AI for Political Communication: Computational Methods to Study Polarisation in Australia and Chile, with Dr Mathias Felipe de Lima Santos and colleagues at PUC Chile. Domestic applicants; applications open soon.
• [2026] I am serving as Demonstrations Chair for IEEE ICDM 2026 in Shenyang, China.
• [2026] I am glad to take on the role of Managing Editor of the Machine Learning Journal.
• [2026] I am now the Postgraduate Coordinator of the School of Computer Science and Engineering at UNSW.
• [2026] Congratulations to Daravichet Tin, Lucas Tsutsui da Silva and Yunrui Zhang on their three papers accepted at PAKDD 2026.
• [2026] Congratulations to Vivian Jiang on the paper accepted in Knowledge and Information Systems.
• [2025] Congratulations to Zahra Donyavi, Feiyu Li and Yunrui Zhang on our paper Match: A maximum-likelihood approach for classification under label shift, accepted at ACM SIGKDD 2025.
• [2025] Congratulations to Rushi Babaria on the FastFlow paper accepted in the Proceedings of the ACM on Measurement and Analysis of Computing Systems (SIGMETRICS).
• [2025] Congratulations to Zahra Donyavi and Adriane Serapião on MetaQuant, accepted in Applied Soft Computing.
• [Feb 2025] I am glad to accept the invitation to step up as Section Editor of the Machine Learning Journal from my current position of Action Editor.
• [Feb 2025] Congratulations to Zeinab Ebrahimi for her paper accepted in Neurocomputing Journal.
• [Feb 2025] Congratulations to Yunrui Zhang for his paper accepted in PAKDD 2025.
• [Jan 2025] Congratulations to Honghui Wang for his paper accepted in Expert Systems With Applications Journal.
• [Jan 2025] Congratulations to Yunrui Zhang for his paper accepted in SIAM-SDM 2025.
• [Jan 2025] I am glad to serve as area chair for ECML-PKDD 2025.