20032024

Research activity per year

Personal profile

Biography

Enes Makalic is a Professor of Machine Learning at the Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Australia. He has a lifelong interest in theoretical computer science and a mission to enable global impact through quality teaching and research that emphasizes collaborative, inter-disciplinary partnerships. Since completing his PhD in machine learning, he has spent over 15 years working in Bayesian inference, information theoretic statistics and digital health.

Research interests

His research interests include:

  • Theoretical and applied Bayesian statistics, including model selection and parameter estimation of ultra-high dimensional statistical models;
  • The minimum message length principles of inductive inference, and applications of information theoretic statistics to epidemiology;
  • Image processing and risk prediction, focusing on digital mammography and breast cancer; and
  • Statistical genetics and genomic prediction models for rare, polygenic diseases and traits.

Enes is also an active member of the academic community, serving as a reviewer and program committee member for numerous journals and conferences.

Monash teaching commitment

Enes has developed and coordinated subjects and short courses in the areas of computer science, biostatistics, survival analysis, and machine learning. He enjoys mentoring students, and has supervised Honours, Masters and PhD students to completion.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Machine Learning, PhD, Minimum message length inference of artificial neural networks, MONASH UNIVERSITY

Award Date: 19 Jun 2007

Computer Science, Bachelor of Computer Science (Honours), MONASH UNIVERSITY

Award Date: 31 Dec 2002

Research area keywords

  • Statistics
  • Machine Learning
  • Data Science
  • Digital Health
  • Statistical genomics
  • Information Theory

Collaborations and top research areas from the last five years

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