Svetha Venkatesh is an ARC Australian Laureate Fellow, Alfred Deakin Professor and Director of Centre for Pattern Recognition and Data Analytics (PRaDA) at Deakin University. She was elected a Fellow of the International Association of Pattern Recognition in 2004 for contributions to formulation and extraction of semantics in multimedia data, and a Fellow of the Australian Academy of Technological Sciences and Engineering in 2006. In 2017, Professor Venkatesh was appointed an Australian Laureate Fellow, the highest individual award the Australian Research Council can bestow. Professor Venkatesh and her team have tackled a wide range of problems of social significance, including the critical areas of autism, security and aged care.
The outcomes have impacted the community and evolved into publications, patents, tools and spin-off companies. This includes three full patents, one start-up company (iCetana) and two significant products - TOBY Playpad, Virtual Observer.
Professor Venkatesh has tackled complex pattern recognition tasks by drawing inspiration and models from widely diverse disciplines, integrating them into rigorous computational models and innovative algorithms. Her main contributions have been in the development of theoretical frameworks and novel applications for analyzing large scale, multimedia data. This includes development of several Bayesian parametric and non-parametric models, solving fundamental problems in processing multiple channel, multi-modal temporal and spatial data.
PhD in Computer Science
University of Western Australia
MTech in Electrical Engineering
IIT, New Delhi, India
BTech in Electronics and Telecommunications
IIT, Roorkee, India
Scientific/Research Societies and Academies
Our methods are grounded in statistical machine learning and pattern recognition. In our research, we ask the following questions:
We use Bayesian mathematics to develop an astract framework for optimising design and manufacturing of products and processess.
We present a portable platform for pervasive delivery of early intervention therapy using multi-touch interfaces and principled ways to deliver stimuli of increasing complexity and adapt to a child’s performance.
We are embarking on questions that arise in examination of large, disparate and multimodal hospital data sets. Can we impact and inform the formation of dynamic health intervention and improved safety and care
July 2018: Delivering efficiencies in health care and manufacturing, Indian Institute of Science, Bangalore, India
April 2018: Accelerating Experimental Design, Intelligent Polymer Research Institute, University of Wollongong, Australia
March 2018: Detecting Rare Events, Collaborative Deans’ Lecture, Melbourne School of Engineering, Melbourne, Australia
Feb 2018: Delivering Efficiencies in Health Care and Manufacturing, The 11th IAPR International Conference on Biometrics (ICB 2018), Gold Coast, Australia
Nov 2017: Delivering Efficiencies in Healthcare and Manufacturing, Digital Image Computing: Techniques and Applications (DICTA2017), Sydney, Australia
Nov 2017: Machine Learning for Alloy and Material design, Institute for Frontier Materials Annual Conference, Geelong, Australia
Nov 2017: Machine Learning, Pattern Recognition and HMR, at Research Australia University Roundtable, Melbourne, Australia
Nov 2017: Close Encounters with Machine Learning, Creative Innovation (CI2017), Melbourne, Australia
Oct 2017: Detecting rare events, International Federation of Psychiatric Epidemiology Congress (IFPE2017), Melbourne, Australia
July 2016: Machine Learning: Beyond Data, 18th Annual Conference of the International Society for Bipolar Disorders (ISBD), Amsterdam, Netherlands
April 2016: Keynote, 20th Pacific Asia Conference on Knowledge Discovery and Data Mining PAKDD, New Zealand
Oct 2015: Dennis Moore Distinguished Oration, Australian Computer Society, Perth, Australia
Oct 2015: Harrison Lecture for Innovation, Geelong Smart Network, Geelong, Australia
Oct 2014: Suicide risk detection using electronic medical records, Brain Sciences UNSW Symposium, Kensington, Australia