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Svetha Venkatesh

Svetha Venkatesh

Award Badge
Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
25999
World Ranking
1258
National Ranking
32

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award
  • 2004 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to the formulation and extraction of semantics in multimedia data.

Overview

Svetha Venkatesh is affiliated with Deakin University in Australia and has a substantial research output primarily in the field of Computer Science. Their main areas of study include Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Molecular Biology, and Computational Theory and Mathematics.

Venkatesh has contributed extensively to various research topics, with a focus on Reinforcement Learning in Robotics, Machine Learning and Data Classification, Advanced Bandit Algorithms Research, Gaussian Processes and Bayesian Inference, Domain Adaptation and Few-Shot Learning, Advanced Multi-Objective Optimization Algorithms, and Machine Learning and Algorithms.

The scientist's frequent collaborators include Santu Rana, Sunil Gupta, Truyen Tran, Hung Lê, and Kien Do, with whom they have published numerous works.

Research publications by Svetha Venkatesh have appeared in several prominent venues. The most frequent publication outlets include arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Knowledge-Based Systems, bioRxiv (Cold Spring Harbor Laboratory), and Defence Technology.

Key recent papers authored or coauthored by Venkatesh include:

  • GraphDTA: predicting drug-target binding affinity with graph neural networks, 2020, Bioinformatics
  • Bayesian Optimization for Adaptive Experimental Design: A Review, 2020, IEEE Access
  • Coupling machine learning with 3D bioprinting to fast track optimisation of extrusion printing, 2020, Applied Materials Today
  • Precision psychiatry with immunological and cognitive biomarkers: a multi-domain prediction for the diagnosis of bipolar disorder or schizophrenia using machine learning, 2020, Translational Psychiatry
  • The Lancet Commission on self-harm, 2024, The Lancet

Venkatesh has been recognized as a Fellow of the International Association for Pattern Recognition (IAPR) since 2004, for contributions to the formulation and extraction of semantics in multimedia data.

Best Publications

  • Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection

    Dong Gong;Lingqiao Liu;Vuong Le;Budhaditya Saha

  • Video abstraction: A systematic review and classification

    Ba Tu Truong;Svetha Venkatesh

  • GraphDTA: predicting drug-target binding affinity with graph neural networks.

    Thin Nguyen;Hang Le;Thomas P Quinn;Tri Nguyen

  • Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View.

    Wei Luo;Dinh Phung;Truyen Tran;Sunil Gupta

  • Activity recognition and abnormality detection with the switching hidden semi-Markov model

    T.V. Duong;H.H. Bui;D.Q. Phung;S. Venkatesh

  • Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model

    N.T. Nguyen;D.Q. Phung;S. Venkatesh;H. Bui

  • Predicting healthcare trajectories from medical records: A deep learning approach.

    Trang Pham;Truyen Tran;Dinh Q. Phung;Svetha Venkatesh

  • Bayesian Optimization for Adaptive Experimental Design: A Review

    Stewart Greenhill;Santu Rana;Sunil Gupta;Pratibha Vellanki

  • $\mathtt {Deepr}$: A Convolutional Net for Medical Records.

    Phuoc Nguyen;Truyen Tran;Nilmini Wickramasinghe;Svetha Venkatesh

  • Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety

    Kit Huckvale;Svetha Venkatesh;Helen Christensen

  • Policy recognition in the abstract hidden Markov model

    Hung H. Bui;Svetha Venkatesh;Geoff West

  • Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression

    Senjian An;Wanquan Liu;Svetha Venkatesh

  • DeepCare: A Deep Dynamic Memory Model forźPredictive Medicine

    Trang Pham;Truyen Tran;Dinh Phung;Svetha Venkatesh

  • Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

    Romero Morais;Vuong Le;Truyen Tran;Budhaditya Saha

  • Joint learning and dictionary construction for pattern recognition

    Duc-Son Pham;S. Venkatesh

  • Robot Navigation Inspired by Principles of Insect Vision

    Mandyam V. Srinivasan;Javaan S. Chahl;Keven Weber;Svetha Venkatesh

  • Face Recognition Using Kernel Ridge Regression

    Senjian An;Wanquan Liu;S. Venkatesh

  • Affective and Content Analysis of Online Depression Communities

    Thin Nguyen;Dinh Phung;Bo Dao;Svetha Venkatesh

  • Hierarchical Conditional Relation Networks for Video Question Answering

    Thao Minh Le;Vuong Le;Svetha Venkatesh;Truyen Tran

  • Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

    Truyen Tran;Tu Dinh Nguyen;Dinh Phung;Svetha Venkatesh

  • New enhancements to cut, fade, and dissolve detection processes in video segmentation

    Ba Tu Truong;Chitra Dorai;Svetha Venkatesh

Frequent Co-Authors

Dinh Phung
Dinh Phung Monash University
Geoff West
Geoff West Curtin University
Chitra Dorai
Chitra Dorai IBM (United States)
Ognjen Arandjelovic
Ognjen Arandjelovic University of St Andrews
Terry Caelli
Terry Caelli Deakin University
Mandyam V. Srinivasan
Mandyam V. Srinivasan University of Queensland
Helen Christensen
Helen Christensen University of New South Wales
Susanne Boll
Susanne Boll Carl von Ossietzky University of Oldenburg
Horst Bunke
Horst Bunke University of Bern
Javaan Chahl
Javaan Chahl University of South Australia

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