Patricia Menéndez

Department of Econometrics and Business Statistics, Monash University

Melbourne, VIC

Contact me for

  • Mentoring
  • Sitting on boards or committees
  • Providing an expert opinion
  • Outreach activities
  • Conference presenting
  • Opportunities to collaborate


Patricia Menéndez is a Lecturer at the Department of Econometrics and Business Statistics at Monash University Business School.

Patricia's training is in mathematics and Statistics and she received her PhD from ETH Zurich in Switzerland. Since completing her PhD she has held academic positions at Wageningen University, University of New South Wales and University of Queensland. Before joining the department she has also worked outside academia as statistician/research scientist/data scientist for the NSW Bureau of Crime Statistics and Research, and for the Australian Institute of Marine Science. 

Patricia has experience working on multidisciplinary projects to answer research and policy-making questions in the fields of climate change, environmental and marine sciences besides criminology. She has expertise developing and applying statistical methodology, data analytics and computational methods as well as providing statistical training. She is very passionate about the application and development of statistical methodology to solve real life problems and bringing statistical knowledge closer to other disciplines. She is also very passionate about teaching and has received several awards and commendations about for her teaching.

In addition Patricia has been a Monbukagakusho fellow at Okayama University, Japan (awarded by Japanese Ministry of Education, Culture, sports, Science and Technology) and served as a member of the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers Scientific Advisory board. She was also selected as part of the fourth cohort of the STEMM Women Leadership program Homeward Bound and serves regularly in mentoring programs.

Her research interests include statistical methods for time series, computational statistics, machine learning, data visualisation tools and data science. 

Patricia identifies as culturally and linguistically diverse.