Sunil Gupta

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Svetha VenkateshAlfred Deakin Professor, Deakin UniversityVerified email at deakin.edu.au
Santu RanaAssociate Professor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Truyen TranProfessor | Head of AI, Health and Science @ Deakin UniversityVerified email at deakin.edu.au
Alistair ShiltonApplied Artificial Intelligence Institute (A²I²), Deakin UniversityVerified email at deakin.edu.au
Cheng LiNational University of Singapore, SingaporeVerified email at comp.nus.edu.sg
Vu NguyenAmazonVerified email at robots.ox.ac.uk
Wei LuoDeakin UniversityVerified email at deakin.edu.au
Dang Nguyen, PhDApplied Artificial Intelligence Institute (A2I2), Deakin University, AustraliaVerified email at deakin.edu.au
Pratibha VellankiDeakin University, AustraliaVerified email at research.deakin.edu.au
Majid AbdolshahMachine Learning Scientist @ AmazonVerified email at amazon.com
Alessandra SuttiDeakin University, Institute for Frontier MaterialsVerified email at deakin.edu.au
Thanh Nguyen-TangJohns Hopkins UniversityVerified email at cs.jhu.edu
David Rubín de Celis LealAssociate Research FellowVerified email at deakin.edu.au
Tinu Theckel JoyIBM ResearchVerified email at ibm.com
Michael BerkDeakin UniversityVerified email at deakin.edu.au
Thin NguyenSenior Research Lecturer, Deakin University, AustraliaVerified email at deakin.edu.au
HARIPRIYA HARIKUMARPostdoctoral Research Fellow, Applied Artificial Intelligence Institute, Deakin UniversityVerified email at deakin.edu.au
Brett AdamsResearch Fellow, School of Computing, Curtin UniversityVerified email at curtin.edu.au
Stewart GreenhillDeakin UniversityVerified email at deakin.edu.au

Sunil Gupta

Professor, Head of AI Optimization and Materials Discovery, Deakin University

Verified email at deakin.edu.au - Homepage

Machine Learning Bayesian Optimization Healthcare Analytics Adaptive Trials Materials Discovery


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Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ... Journal of medical Internet research 18 (12), e323, 2016	759	2016
Bayesian optimization for adaptive experimental design: A review S Greenhill, S Rana, S Gupta, P Vellanki, S Venkatesh IEEE access 8, 13937-13948, 2020	332	2020
Rapid Bayesian optimisation for synthesis of short polymer fiber materials C Li, D Rubín de Celis Leal, S Rana, S Gupta, A Sutti, S Greenhill, ... Scientific reports 7 (1), 5683, 2017	122	2017
High dimensional Bayesian optimization with elastic Gaussian process S Rana, C Li, S Gupta, V Nguyen, S Venkatesh International conference on machine learning, 2883-2891, 2017	122	2017
High dimensional Bayesian optimization using dropout C Li, S Gupta, S Rana, V Nguyen, S Venkatesh, A Shilton arXiv preprint arXiv:1802.05400, 2018	121	2018
Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry S Gupta, T Tran, W Luo, D Phung, RL Kennedy, A Broad, D Campbell, ... BMJ open 4 (3), e004007, 2014	115	2014
Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso I Kamkar, SK Gupta, D Phung, S Venkatesh Journal of biomedical informatics 53, 277-290, 2015	110	2015
Coupling machine learning with 3D bioprinting to fast track optimisation of extrusion printing K Ruberu, M Senadeera, S Rana, S Gupta, J Chung, Z Yue, S Venkatesh, ... Applied Materials Today 22, 100914, 2021	105	2021
Nonnegative shared subspace learning and its application to social media retrieval SK Gupta, D Phung, B Adams, T Tran, S Venkatesh Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	94	2010
Regret for expected improvement over the best-observed value and stopping condition V Nguyen, S Gupta, S Rana, C Li, S Venkatesh Asian conference on machine learning, 279-294, 2017	92	2017
Hyperparameter tuning for big data using Bayesian optimisation TT Joy, S Rana, S Gupta, S Venkatesh 2016 23rd International Conference on Pattern Recognition (ICPR), 2574-2579, 2016	92	2016
Differentially private random forest with high utility S Rana, SK Gupta, S Venkatesh 2015 IEEE international conference on data mining, 955-960, 2015	87	2015
Multi-objective Bayesian optimisation with preferences over objectives M Abdolshah, A Shilton, S Rana, S Gupta, S Venkatesh Advances in neural information processing systems 32, 2019	67	2019
Bayesian optimization for categorical and category-specific continuous inputs D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5256-5263, 2020	62	2020
SARS‐CoV‐2 infection and venous thromboembolism after surgery: an international prospective cohort study COVIDSurg Collaborative, GlobalSurg Collaborative, D Nepogodiev, ... Anaesthesia 77 (1), 28-39, 2022	58	2022
Phenomenology and beliefs of patients with Dhat syndrome: A nationwide multicentric study S Grover, A Avasthi, S Gupta, A Dan, R Neogi, PB Behere, B Lakdawala, ... International Journal of Social Psychiatry 62 (1), 57-66, 2016	58	2016
Exploration enhanced expected improvement for Bayesian optimization J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019	56	2019
Fast hyperparameter tuning using Bayesian optimization with directional derivatives TT Joy, S Rana, S Gupta, S Venkatesh Knowledge-Based Systems 205, 106247, 2020	55	2020
Regularized nonnegative shared subspace learning SK Gupta, D Phung, B Adams, S Venkatesh Data mining and knowledge discovery 26, 57-97, 2013	54	2013
Arsenic mediated modifications in Bacillus aryabhattai and their biotechnological applications for arsenic bioremediation N Singh, S Gupta, N Marwa, V Pandey, PC Verma, S Rathaur, N Singh Chemosphere 164, 524-534, 2016	52	2016

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