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Prof Sunil Gupta

STAFF PROFILE

Position

Head, AI, Optimisation and Materials Discovery

Faculty

Applied Artificial Intel Inst

Department

A2I2P

Campus

Geelong Waurn Ponds Campus

Qualifications

Doctor of Philosophy, Curtin University, 2012

Biography

Dr. Gupta graduated with a PhD in computer science from Curtin University in Jan 2012. He completed his PhD in a period of 2.5 years receiving the Chancellor's Commendation for excellence for his exceptional doctoral work in Machine Learning and AI. Prior to his PhD, he completed a Master of Engineering degree in Signal Processing from Indian Institute of Science, Bangalore. Since completing his PhD, Dr. Gupta has been at Deakin University. He currently works as a Professor and the Head of AI Optimisation and Materials Discovery at the Applied Artificial Intelligence Institute (A2I2). His research interests lie in broad areas of machine learning and artificial intelligence.

Read more on Sunil's profile

Research interests

AI, Machine learning, Bayesian optimisation, Data mining, Pattern recognition, Deep learning, Active learning, Transfer learning, Reinforcement learning, Healthcare data analytics, Computer vision, AI safety and assurance, Adaptive Clinical Trials, AI-driven materials design and discovery

Affiliations

Adjunct Professsor, Indian Institute of Technology, Kanpur, India.

Knowledge areas

AI, Machine learning, Bayesian optimisation, Data mining, Pattern recognition, Deep learning, Active learning, Transfer learning, Reinforcement learning, Healthcare data analytics, Computer vision, AI safety and assurance, Adaptive Clinical Trials, AI-driven materials design and discovery

Awards

  • Winner of the “Best Paper Award” at Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018.
  • 2017: Vice Chancellor’s Award for Outstanding Contribution through Innovation that spans the Value Promise
  • 2017: Best Student Paper Award at Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017
  • 2017: Professional Poster Award for our superalloy design work at 4th World Congress on Integrated Computational Materials Engineering, 2017
  • 2016: Best Paper RunnerUp and Best Poster awards at Asian Conference on Machine Learning (ACML) 2016
  • 2016: Finalists INTEL Track 5 Student Paper Award at International Conference of Pattern Recognition (ICPR), 2016
  • 2015: Best Paper Award, at PAKDD 2015
  • 2014: Recipient of Best Papers of SDM, at SIAM Data Mining Conference 2014
  • 2012: Recipient of Chancellor’s Commendation for excellence for my PhD thesis at Curtin University
  • 2010: Recipient of KDD Travel Awards, ACM SIGKDD Data Mining Conference 2010
  • 2009: Recipient of CIPRS Scholarship, Curtin University, Australia, 2009

Publications

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2024

Root Cause Explanation of Outliers under Noisy Mechanisms

P Nguyen, T Tran, S Gupta, T Nguyen, S Venkatesh

(2024), Vol. 38, pp. 20508-20515, Proceedings of the AAAI Conference on Artificial Intelligence, E1

conference
2023

Machine learning-based discovery of vibrationally stable materials

Sherif Tawfik, Mahad Rashid, Sunil Gupta, Salvy Russo, Tiffany Walsh, Svetha Venkatesh

(2023), Vol. 9, pp. 1-6, npj Computational Materials, Berlin, Germany, C1

journal article

Protocol for a bandit-based response adaptive trial to evaluate the effectiveness of brief self-guided digital interventions for reducing psychological distress in university students: the Vibe Up study

K Huckvale, L Hoon, E Stech, J Newby, W Zheng, J Han, R Vasa, S Gupta, S Barnett, M Senadeera, S Cameron, S Kurniawan, A Agarwal, J Kupper, J Asbury, D Willie, A Grant, H Cutler, B Parkinson, A Ahumada-Canale, J Beames, R Logothetis, M Bautista, J Rosenberg, A Shvetcov, T Quinn, A MacKinnon, S Rana, T Tran, S Rosenbaum, K Mouzakis, A Werner-Seidler, A Whitton, S Venkatesh, H Christensen

(2023), Vol. 13, BMJ Open, C1

journal article

Machine learning identifies a COVID-19-specific phenotype in university students using a mental health app

A Shvetcov, A Whitton, S Kasturi, W Zheng, J Beames, O Ibrahim, J Han, L Hoon, K Mouzakis, S Gupta, S Venkatesh, H Christensen, J Newby

(2023), Vol. 34, Internet Interventions, C1

journal article

Balanced Q-learning: Combining the influence of optimistic and pessimistic targets

T George Karimpanal, H Le, M Abdolshah, S Rana, S Gupta, T Tran, S Venkatesh

(2023), Vol. 325, Artificial Intelligence, C1

journal article

NeuralBO: A black-box optimization algorithm using deep neural networks

D Phan-Trong, H Tran-The, S Gupta

(2023), Vol. 559, pp. 1-15, Neurocomputing, Amsterdam, The Netherlands, C1

journal article

Guiding Visual Question Answering with Attention Priors

T Le, V Le, S Gupta, S Venkatesh, T Tran

(2023), pp. 4370-4379, WACV 2023 : Proceedings of the IEEE Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, E1

conference

Continual Learning with Dependency Preserving Hypernetworks

D Chandra, S Varshney, P Srijith, S Gupta

(2023), pp. 2338-2347, WACV 2023 : Proceedings of the IEEE Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, E1

conference

On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation

T Nguyen-Tang, M Yin, S Gupta, S Venkatesh, R Arora

(2023), Vol. 37, pp. 9310-9318, AAAI 2023 : Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, D.C., E1

conference

Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space

A Shilton, S Gupta, S Rana, S Venkatesh

(2023), Vol. 202, pp. 31435-31488, PMLR 2023 : Proceedings International Conference Machine Learning Research, Honolulu, Hawaii, USA, E1

conference

Multi-weather Image Restoration via Domain Translation

P Patil, S Gupta, S Rana, S Venkatesh, S Murala

(2023), pp. 21639-21648, ICCV 2023 : Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision, Paris, France, E1

conference

Domain Generalization with Interpolation Robustness

R Palakkadavath, T Nguyen-Tang, H Le, S Venkatesh, S Gupta

(2023), Vol. 222, pp. 1039-1054, Proceedings of Machine Learning Research, E1

conference

Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee

G Ngo, D Nguyen, D Phan-Trong, S Gupta

(2023), Vol. 222, pp. 943-958, Proceedings of Machine Learning Research, E1

conference
2022

Prescriptive analytics with differential privacy

H Harikumar, S Rana, S Gupta, T Nguyen, R Kaimal, S Venkatesh

(2022), Vol. 13, pp. 123-138, International Journal of Data Science and Analytics, C1

journal article

Verification of integrity of deployed deep learning models using Bayesian Optimization

D Kuttichira, S Gupta, D Nguyen, S Rana, S Venkatesh

(2022), Vol. 241, pp. 1-12, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

journal article

Dual-frame spatio-temporal feature modulation for video enhancement

P Patil, S Gupta, S Rana, S Venkatesh

(2022), Vol. 130, pp. 1-14, Pattern Recognition, Amsterdam, The Netherlands, C1

journal article

Utilization of Bayesian Optimization and KWN Modeling for Increased Efficiency of Al‐Sc Precipitation Strengthening

K Deane, Y Yang, J Licavoli, V Nguyen, S Rana, S Gupta, S Venkatesh, P Sanders

(2022), Vol. 12, pp. 1-19, Metals, Basel, Switzerland, C1

journal article

Real-Time Skill Discovery in Intelligent Virtual Assistants

P Gopal, S Gupta, S Rana, V Le, T Nguyen, S Venkatesh

(2022), Vol. 13280, pp. 315-327, PAKDD 2022 : Proceedings of the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining 2022, Chengdu, China, E1

conference

Sympathy-based Reinforcement Learning Agents

M Senadeera, T Karimpanal, S Gupta, S Rana

(2022), Vol. 2, pp. 1164-1172, Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, E1

conference

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization

H Tran-The, S Gupta, S Rana, S Venkatesh

(2022), Vol. 151, pp. 8715-8737, AISTATS 2022 : Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, Virtual Conference, E1

conference

Black-Box Few-Shot Knowledge Distillation

D Nguyen, S Gupta, K Do, S Venkatesh

(2022), Vol. 13681, pp. 196-211, ECCV 2022 : Proceedings of the 17th European Conference on Computer Vision, Tel Aviv, Israel, E1

conference

Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions

P Patil, S Gupta, S Rana, S Venkatesh

(2022), Vol. 13688, pp. 143-160, ECCV 2022 : Proceedings of the 17th European Conference on Computer Vision, Tel Aviv, Israel, E1

conference

OFFLINE NEURAL CONTEXTUAL BANDITS: PESSIMISM, OPTIMIZATION AND GENERALIZATION

T Nguyen-Tang, S Gupta, A Nguyen, S Venkatesh

(2022), pp. 1-25, ICLR 2022 : Proceedings of the 10th International Conference on Learning Representations 2022, Virtual, E1

conference

Expected Improvement for Contextual Bandits

H Tran-The, S Gupta, S Sana, T Truong, L Tran-Thanh, S Venkatesh

(2022), Vol. 35, pp. 1-14, NeurIPS 2022 : Proceedings of the 2022 Neural Information Processing Systems Conference, Virtual Conference, E1

conference

Learning to Constrain Policy Optimization with Virtual Trust Region

H Le, T George, M Abdolshah, D Nguyen, K Do, S Gupta, S Venkatesh

(2022), Vol. 35, Advances in Neural Information Processing Systems, E1

conference
2021

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, G Wallace

(2021), Vol. 22, Applied Materials Today, C1

journal article

Predictive Model Based on Health Data Analysis for Risk of Readmission in Disease-Specific Cohorts

M Ansari, A Alok, D Jain, S Rana, S Gupta, R Salwan, S Venkatesh

(2021), Vol. 18, pp. 1-11, Perspectives in health information management, Chicago, Ill., C1

journal article

Fairness improvement for black-box classifiers with Gaussian process

D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh

(2021), Vol. 576, pp. 542-556, Information Sciences, C1

journal article

Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient

H Harikumar, T Quinn, S Rana, S Gupta, S Venkatesh

(2021), Vol. 14, BioData Mining, England, C1

journal article

Computational design of thermally stable and precipitation-hardened Al-Co-Cr-Fe-Ni-Ti high entropy alloys

J Joseph, M Senadeera, Q Chao, K Shamlaye, S Rana, S Gupta, S Venkatesh, P Hodgson, M Barnett, D Fabijanic

(2021), Vol. 888, Journal of Alloys and Compounds, C1

journal article

Identification of predictors and model for predicting prolonged length of stay in dengue patients

M Shahid Ansari, D Jain, H Harikumar, S Rana, S Gupta, S Budhiraja, S Venkatesh

(2021), Vol. 24, pp. 786-798, Health Care Management Science, Netherlands, C1

journal article

Adaptive cost-aware Bayesian optimization[Formula presented]

P Luong, D Nguyen, S Gupta, S Rana, S Venkatesh

(2021), Vol. 232, Knowledge-Based Systems, C1

journal article

An Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments

P Patil, A Dudhane, A Kulkarni, S Murala, A Gonde, S Gupta

(2021), Vol. 30, pp. 7889-7902, IEEE Transactions on Image Processing, Piscataway, N.J., C1

journal article

Feasibility of Conducting a Virtual Exit Exam in Neurosurgery during the SARS-COV19 Pandemic

P Salunke, S Sahoo, A Chacko, B Baishya, M Tripathi, R Chabbra, M Karthigeyan, A Aggarwal, A Singh, S Gupta

(2021), Vol. 69, pp. 698-702, Neurology India, Mumbai, India, C1

journal article

Bayesian Optimization with Missing Inputs

P Luong, D Nguyen, S Gupta, S Rana, S Venkatesh

(2021), Vol. 12458, pp. 691-706, ECML PKDD 2020 : Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Belgium, Ghent, E1

conference

Scalable Backdoor Detection in Neural Networks

H Harikumar, V Le, S Rana, S Bhattacharya, S Gupta, S Venkatesh

(2021), Vol. 12458, pp. 289-304, ECML PKDD 2020 : Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Belgium, Ghent, E1

conference

Sparse Spectrum Gaussian Process for Bayesian Optimization

A Yang, C Li, S Rana, S Gupta, S Venkatesh

(2021), Vol. 12713, pp. 257-268, PAKDD 2021 : Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part I, Virtual Event, E1

conference

Factor screening using Bayesian active learning and gaussian process meta-modelling

C Li, D Nguyen, S Rana, S Gupta, A Gill, S Venkatesh

(2021), pp. 3288-3295, ICPR 2020 : Proceedings of the 25th International Conference on Pattern Recognition, Online from Milan, Italy, E1

conference

High Dimensional Level Set Estimation with Bayesian Neural Network

Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh

(2021), Vol. 35, pp. 12095-12103, AAAI 2021 : Proceedings of the 35th AAAI Conference on Artificial Intelligence, Virtual Event, E1

conference

A New Representation of Successor Features for Transfer across Dissimilar Environments

Majid Abdolshah, Hung Le, Thommen George, Sunil Gupta, Santu Rana, Svetha Venkatesh

(2021), Vol. 139, pp. 1-14, ICML 2021 : Proceedings of the International Conference of Machine Learning, Virtual Conference, E1

conference

Distributional Reinforcement Learning via Moment Matching

Thanh Nguyen, Sunil Gupta, Svetha Venkatesh

(2021), Vol. 35, pp. 9144-9152, AAAI 2021 : Proceedings of the 35th AAAI Conference on Artificial Intelligence, Virtual Event, E1

conference

Knowledge Distillation with Distribution Mismatch

D Nguyen, S Gupta, T Nguyen, S Rana, P Nguyen, T Tran, K Le, S Ryan, S Venkatesh

(2021), Vol. 12976, pp. 250-265, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

conference

Fast Conditional Network Compression Using Bayesian HyperNetworks

P Nguyen, T Tran, K Le, S Gupta, S Rana, D Nguyen, T Nguyen, S Ryan, S Venkatesh

(2021), Vol. 12977, pp. 330-345, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

conference

Variational Hyper-encoding Networks

P Nguyen, T Tran, S Gupta, S Rana, H Dam, S Venkatesh

(2021), Vol. 12976, pp. 100-115, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

conference

Kernel Functional Optimisation

A Arun Kumar, A Shilton, S Rana, S Gupta, S Venkatesh

(2021), Vol. 6, pp. 4725-4737, NeurIPS 2021 : Proceedings of the 35th Conference on Neural Information Processing Systems, Virtual Conference, E1

conference

Bayesian Optimistic Optimisation with Exponentially Decaying Regret

H Tran-The, S Gupta, S Rana, S Venkatesh

(2021), Vol. 139, pp. 10390-10400, Proceedings of Machine Learning Research, E1

conference
2020

Batch Bayesian optimization using multi-scale search

T Joy, S Rana, S Gupta, S Venkatesh

(2020), Vol. 187, Knowledge-Based Systems, C1

journal article

Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing

S Allender, J Hayward, S Gupta, A Sanigorski, S Rana, H Seward, S Jacobs, S Venkatesh

(2020), Vol. 3, npj Digital Medicine, England, C1

journal article

Incorporating expert prior in Bayesian optimisation via space warping

A Ramachandran, S Gupta, S Rana, C Li, S Venkatesh

(2020), Vol. 195, Knowledge-Based Systems, C1

journal article

Bayesian optimisation in unknown bounded search domains

J Berk, S Gupta, S Rana, V Nguyen, S Venkatesh

(2020), Vol. 195, Knowledge-Based Systems, C1

journal article

Bayesian optimization for adaptive experimental design: a review

S Greenhill, S Rana, S Gupta, P Vellanki, S Venkatesh

(2020), Vol. 8, pp. 13937-13948, IEEE access, Piscataway, N.J., C1

journal article

Improving the tensile properties of wet spun silk fibers using rapid Bayesian algorithm

Ya Yao, Benjamin Allardyce, Rangam Rajkhowa, Dylan Hegh, Alessandra Sutti, Surya Subianto, Sunil Gupta, Santu Rana, S Greenhill, Svetha Venkatesh, Xungai Wang, Joselito Razal

(2020), Vol. 6, pp. 3197-3207, ACS biomaterials science and engineering, Washington, D.C., C1

journal article

Fast hyperparameter tuning using Bayesian optimization with directional derivatives

T Joy, S Rana, S Gupta, S Venkatesh

(2020), Vol. 205, Knowledge-Based Systems, C1

journal article

A scrap-tolerant alloying concept based on high entropy alloys

M Barnett, M Senadeera, D Fabijanic, K Shamlaye, J Joseph, S Kada, S Rana, S Gupta, S Venkatesh

(2020), Vol. 200, pp. 735-744, Acta Materialia, Amsterdam, The Netherlands, C1

journal article

Clinicopathological features of primary central nervous system diffuse large B cell lymphoma: Experience from a Tertiary Center in North India

B Radotra, M Parkhi, D Chatterjee, B Yadav, N Ballari, G Prakash, S Gupta

(2020), Vol. 11, pp. 1-9, Surgical Neurology International, New York, N.Y., C1

journal article

Frontotemporal Branch of the Facial Nerve and Fascial Layers in the Temporal Region: A Cadaveric Study to Define a Safe Dissection Plane

R Sihag, S Gupta, D Sahni, A Aggarwal

(2020), Vol. 68, pp. 1313-1320, Neurology India, Mumbai, India, C1

journal article

COVID-19: Changing patterns among neurosurgical patients from North India, efficacy of repeat testing, and inpatient prevalence

S Sahoo, S Dhandapani, A Singh, C Gendle, M Karthigeyan, P Salunke, A Aggarwal, N Singla, R Singla, M Tripathi, R Chhabra, S Mohindra, M Tewari, M Mohanty, H Bhagat, A Chakrabarti, S Gupta

(2020), Vol. 49, pp. 1-8, Neurosurgical Focus, Rolling Meadows, IL., C1

journal article

The diagnostic performance of 99mTc-methionine single-photon emission tomography in grading glioma preoperatively: a comparison with histopathology and Ki-67 indices

N Rani, B Singh, N Kumar, P Singh, P Hazari, A Jaswal, S Gupta, R Chhabra, B Radotra, A Mishra

(2020), Vol. 41, pp. 848-857, Nuclear Medicine Communications, Philadelphia, Pa., C1

journal article

Intracranial Aneurysm Biomarker Candidates Identified by a Proteome-Wide Study

T Sharma, K Datta, M Kumar, G Dey, A Khan, K Mangalaparthi, P Saharan, S Chinnapparaj, A Aggarwal, N Singla, S Ghosh, A Rawat, S Dhandapani, P Salunke, R Chhabra, D Singh, A Takkar, S Gupta, T Prasad, H Gowda, K Mukherjee, A Pandey, H Bhagat

(2020), Vol. 24, pp. 483-492, OMICS: A Journal of Integrative Biology, New Rochelle, N.Y., C1

journal article

Decompressive craniectomy in pediatric non-traumatic intracranial hypertension: a single center experience

V Williams, A Bansal, M Jayashree, J Ismail, A Aggarwal, S Gupta, S Singhi, P Singhi, A Baranwal, K Nallasamy

(2020), Vol. 34, pp. 258-263, British Journal of Neurosurgery, London, Eng., C1

journal article

A comparison of hypertonic saline and mannitol on intraoperative brain relaxation in patients with raised intracranial pressure during supratentorial tumors resection: A randomized control trial

A Singla, P Mathew, K Jangra, S Gupta, S Soni

(2020), Vol. 68, pp. 141-145, Neurology India, Mumbai, India, C1

journal article

Impact of postoperative infarcts in determining outcome after clipping of anterior communicating artery aneurysms

A Gupta, M Tripathi, A Umredkar, R Chauhan, V Gupta, S Gupta

(2020), Vol. 68, pp. 132-140, Neurology India, Mumbai, India, C1

journal article

Level set estimation with search space warping

Manisha Senadeera, S Rana, S Gupta, S Venkatesh

(2020), Vol. 12085, pp. 827-839, PAKDD 2020 : Advances in Knowledge Discovery and Data Mining : Proceedings of the 24th Pacific-Asia Conference 2020, Singapore, E1

conference

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation

Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh

(2020), pp. 2284-2290, IJCAI-PRICAI-20 : Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, Yokohama, Japan, E1

conference

Distributionally Robust Bayesian Quadrature Optimization

Tang Thanh, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh

(2020), Vol. 108, pp. 1921-1930, AISTATS 2020 : Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, Online from Palermo, Italy, E1

conference

Accelerated Bayesian Optimization through Weight-Prior Tuning

Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Laurence Park, Cheng Li, Svetha Venkatesh, Thomas Dorin, Alessandra Sutti, David Rubin, Teo Slezak, Alireza Vahid, Murray Height

(2020), Vol. 108, pp. 1-10, AISTATS 2020 : Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, Online from Palermo, Italy, E1

conference

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning

T Karimpanal, S Rana, S Gupta, T Tran, S Venkatesh

(2020), pp. 1-10, IJCNN 2020 : Proceedings of the 2020 International Joint Conference on Neural Networks, Glasgow, Scotland, E1

conference

Unsupervised Anomaly Detection on Temporal Multiway Data

D Nguyen, P Nguyen, K Do, S Rana, S Gupta, T Tran

(2020), pp. 1059-1066, SSCI 2020 : Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, Canberra, Australian Capital Territory, E1

conference

DeepCoDA: Personalized interpretability for compositional health data

T Quinn, D Nguyen, S Rana, S Gupta, S Venkatesh

(2020), Vol. PartF168147-11, pp. 7833-7842, ICML 2020 : Proceedings of the 37th International Conference on Machine Learning, Online, E1

conference

Trading convergence rate with computational budget in high dimensional Bayesian optimization

H Tran The, S Gupta, S Rana, S Venkatesh

(2020), pp. 2425-2432, AAAI-20 : Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence, New York, N.Y., E1

conference

Bayesian optimization for categorical and category-specific continuous inputs

D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh

(2020), pp. 5256-5263, AAAI-20 : Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence, New York, N.Y., E1

conference
2019

Filtering Bayesian optimization approach in weakly specified search space

V Nguyen, S Gupta, S Rana, C Li, S Venkatesh

(2019), Vol. 60, pp. 385-413, Knowledge and Information Systems, C1

journal article

A flexible transfer learning framework for Bayesian optimization with convergence guarantee

T Theckel Joy, S Rana, S Gupta, S Venkatesh

(2019), Vol. 115, pp. 656-672, Expert Systems with Applications, C1

journal article

Optimizing a High-Entropy System: Software-Assisted Development of Highly Hydrophobic Surfaces using an Amphiphilic Polymer

S Subianto, C Li, D Rubin De Celis Leal, S Rana, S Gupta, R He, S Venkatesh, A Sutti

(2019), Vol. 4, pp. 15912-15922, ACS Omega, United States, C1

journal article

Examining conductivity, current density, and sizings applied to carbon fibers during manufacture and their effect on fiber-to-matrix adhesion in epoxy polymers

A Hendlmeier, F Stojcevski, R Alexander, S Gupta, L Henderson

(2019), Vol. 179, Composites Part B: Engineering, C1

journal article

Efficient Bayesian Function Optimization of Evolving Material Manufacturing Processes

D Rubín De Celis Leal, D Nguyen, P Vellanki, C Li, S Rana, N Thompson, S Gupta, K Pringle, S Subianto, S Venkatesh, T Slezak, M Height, A Sutti

(2019), Vol. 4, pp. 20571-20578, ACS Omega, United States, C1

journal article

The Predictive Value of Conventional Magnetic Resonance Imaging Sequences on Operative Findings and Histopathology of Intracranial Meningiomas: A Prospective Study

M Karthigeyan, S Dhandapani, P Salunke, P Singh, B Radotra, S Gupta

(2019), Vol. 67, pp. 1439-1445, Neurology India, Mumbai, India, C1

journal article

Functional and radiological parameters to assess outcome of endoscopic third ventriculostomy in shunt failure patients

R Irrinki, M Bawa, S Hegde, R Chhabra, V Gupta, S Gupta

(2019), Vol. 14, pp. 65-69, Journal of Pediatric Neurosciences, Philadelphia, Pa., C1

journal article

Spontaneous intracranial haemorrhage in children-intensive care needs and predictors of in-hospital mortality: a 10-year single-centre experience

V Williams, M Jayashree, A Bansal, A Baranwal, K Nallasamy, S Singhi, P Singhi, S Gupta

(2019), Vol. 35, pp. 1371-1379, Child's Nervous System, Berlin, Germany, C1

journal article

Hodgkin lymphoma in a case of chronic myeloid leukemia treated with tyrosine kinase inhibitors

S Gajendra, A Sharma, R Sharma, S Gupta, N Sood, R Sachdev

(2019), Vol. 35, pp. 74-78, Türk Patoloji Dergisi / Turkish Journal of Pathology, C1

journal article

Need for Grass Root Innovation in Developing Countries: Case for Stationary Binder Clips in Scalp Hemostasis

N Yagnick, R Singh, M Tripathi, S Mohindra, H Deora, A Suri, S Gupta

(2019), Vol. 121, pp. 222-226, World Neurosurgery, Amsterdam, The Netherlands, C1

journal article

Information-theoretic transfer learning framework for Bayesian optimisation

A Ramachandran, S Gupta, S Rana, S Venkatesh

(2019), Vol. 11052, pp. 827-842, ECML-PKDD 2018 : Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2018, Dublin, Ireland, E1

conference

Exploration enhanced expected improvement for Bayesian optimization

J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh

(2019), Vol. 11052, pp. 621-637, ECML-PKDD 2018 : Proceedings of the e European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2018, Dublin, Ireland, E1

conference

Incomplete conditional density estimation for fast materials discovery

P Nguyen, T Tran, S Gupta, S Rana, M Barnett, S Venkatesh

(2019), pp. 549-557, 2019 SIAM : Proceedings of the 2019 SIAM International Conference on Data Mining, Calgary, Alta., E1

conference

Bayesian functional optimisation with shape prior

Pratibha Vellanki, Santu Rana, Sunil Gupta, David Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh

(2019), pp. 1617-1624, AAAI 2019 : Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, E1

conference

Explaining black-box models using interpretable surrogates

D Kuttichira, S Gupta, C Li, S Rana, S Venkatesh

(2019), Vol. 11670, pp. 3-15, PRICAI 2019: Trends in Artificial Intelligence 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings,, Cuvu, Fiji, E1

conference

Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation

A Ramachandran, S Gupta, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 497-509, AI 2019: Advances in artificial intelligence : Proceedings of the 32nd Australasian Joint Conference on Artificial Intelligence 2019, Adelaide, South Australia, E1

conference

Bayesian Optimization with Discrete Variables

P Luong, S Gupta, D Nguyen, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 473-484, AI 2019 : Advances in Artificial Intelligence : Proceedings of the 32nd Australian Joint Conference, Adelaide, South Australia, E1

conference

Detection of Compromised Models Using Bayesian Optimization

D Kuttichira, S Gupta, D Nguyen, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 485-496, AI 2019 : Advances in Artificial Intelligence : Proceedings of the 32nd Australian Joint Conference, Adelaide, South Australia, E1

conference

Efficient bayesian optimization for uncertainty reduction over perceived optima locations

V Nguyen, S Gupta, S Rana, M Thai, C Li, S Venkatesh

(2019), Vol. 2019-November, pp. 1270-1275, ICDM 2019 : Proceedings of the 19th IEEE International Conference on Data Mining, Beijing, China, E1

conference

Bayesian optimization with unknown search space

H Ha, S Rana, S Gupta, T Nguyen, H Tran-The, S Venkatesh

(2019), Vol. 32, pp. 1-10, NeurIPS 2019 : Proceedings of the 33rd Conference on Neural Information Processing Systems, Vancouver, British Columbia, E1

conference

Multi-objective Bayesian optimisation with preferences over objectives

M Abdolshah, A Shilton, S Rana, S Gupta, S Venkatesh

(2019), Vol. 32, pp. 1-11, NeurIPS 2019 : Proceedings of the 33rd Conference on Neural Information Processing Systems, Vancouver, British Columbia, E1

conference

Sub-linear regret bounds for Bayesian optimisation in unknown search spaces

H Tran-The, S Gupta, S Rana, H Ha, S Venkatesh

(2019), Vol. 2020-December, pp. 1-25, NeurIPS 2019 : Proceedings of the 33rd Conference on Neural Information Processing Systems, Vancouver, British Columbia, E1

conference
2018

New bayesian-optimization-based design of high-strength 7xxx-series alloys from recycled aluminum

A Vahid, S Rana, S Gupta, P Vellanki, S Venkatesh, T Dorin

(2018), Vol. 70, pp. 2704-2709, JOM, New York, N.Y., C1

journal article

Comparative genetic variability in HIV-1 subtype C p24 Gene in early age groups of infants

U Sharma, S Gupta, S Venkatesh, A Rai, A Dhariwal, M Husain

(2018), Vol. 54, pp. 647-661, Virus genes, [New York, N.Y.], C1

journal article

Comparative Genetic Variability in HIV-1 Subtype C vpu Gene in Early Age Groups of Infants

U Sharma, P Gupta, S Gupta, S Venkatesh, M Husain

(2018), Vol. 16, pp. 64-76, Current HIV Research, Sharjah, United Arab Emirates, C1

journal article

Has outcome of subarachnoid hemorrhage changed with improvements in neurosurgical services? Study of 2000 patients over 2 decades from India

S Dhandapani, A Singh, N Singla, K Praneeth, A Aggarwal, H Sodhi, S Pal, S Goudihalli, P Salunke, S Mohindra, A Kumar, V Gupta, R Chhabra, K Mukherjee, M Tewari, N Khandelwal, S Mathuriya, V Khosla, S Gupta

(2018), Vol. 49, pp. 2890-2895, Stroke, Philadelphia, Pa., C1

journal article

Data of phosphoproteomic analysis of non-functioning pituitary adenoma

A Rai, B Radotra, K Mukherjee, S Gupta, P Dutta

(2018), Vol. 18, pp. 781-786, Data in Brief, Amsterdam, The Netherlands, C1

journal article

The effect of cranioplasty following decompressive craniectomy on cerebral blood perfusion, neurological, and cognitive outcome

A Shahid, M Mohanty, N Singla, B Mittal, S Gupta

(2018), Vol. 128, pp. 229-235, Journal of Neurosurgery, Rolling Meadows, Ill., C1

journal article

Independent impact of plasma homocysteine levels on neurological outcome following head injury

S Dhandapani, A Bajaj, C Gendle, I Saini, I Kaur, I Chaudhary, Jasandeep, J Kaur, G Kalyan, M Dhandapani, S Gupta

(2018), Vol. 41, pp. 513-517, Neurosurgical Review, Heidelberg, Germany, C1

journal article

Comparative evaluation of H&H and WFNS grading scales with modified H&H (sans systemic disease): A study on 1000 patients with subarachnoid hemorrhage

A Aggarwal, S Dhandapani, K Praneeth, H Sodhi, S Pal, S Gaudihalli, N Khandelwal, K Mukherjee, M Tewari, S Gupta, S Mathuriya

(2018), Vol. 41, pp. 241-247, Neurosurgical Review, Heidelberg, Germany, C1

journal article

Exploiting strategy-space diversity for batch Bayesian optimisation

S Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh

(2018), Vol. 84, pp. 538-547, AISTATS 2018 : Proceedings of the International Conference on Artificial Intelligence and Statistics, Playa Blanca, Lanzarote, Canary Islands, E1

conference

A privacy preserving bayesian optimization with high efficiency

T Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh

(2018), Vol. 10939, pp. 543-555, PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Melbourne, Victoria, E1

conference

Prescriptive analytics through constrained bayesian optimization

Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Kaimal Ramachandra, Svetha Venkatesh

(2018), Vol. 10937, pp. 335-347, PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Melbourne, Victoria, E1

conference

Efficient Bayesian optimisation using derivative meta-model

A Yang, C Li, S Rana, S Gupta, S Venkatesh

(2018), Vol. 11013, pp. 256-264, PRICAI 2018: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence, Nanjing, China, E1

conference

Selecting optimal source for transfer learning in Bayesian optimisation

A Ramachandran, S Gupta, S Rana, S Venkatesh

(2018), Vol. 11012, pp. 42-56, PRICAI 2018 : Trends in artificial intelligence : Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence, Nanjing, China, E1

conference

Multi-target optimisation via Bayesian optimisation and linear programming

A Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

(2018), UAI 2018: Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, Monterey, Calif., E1

conference

Expected hypervolume improvement with constraints

M Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, svetha Venkatesh

(2018), pp. 3238-3243, ICPR 2018 : Proceedings of the 24th International Conference on Pattern Recognition, Beijing, China, E1

conference

Sparse approximation for Gaussian process with derivative observations

A Yang, C Li, S Rana, S Gupta, S Venkatesh

(2018), Vol. 11320, pp. 507-518, AI 2018: Proceedings of the 31st Australasian Joint Conference on Artificial Intelligence, Wellington, N.Z., E1

conference

Accelerating experimental design by incorporating experimenter hunches

C Li, R Santu, S Gupta, V Nguyen, S Venkatesh, A Sutti, D De Celis Leal, T Slezak, M Height, M Mohammed, I Gibson

(2018), Vol. 2018-November, pp. 257-266, IEEE ICDM 2018 : International Conference on Data Mining, Singapore, E1

conference

Differentially private prescriptive analytics

H Harikumar, S Rana, S Gupta, T Nguyen, R Kaimal, S Venkatesh

(2018), Vol. 2018-November, pp. 995-1000, ICDM 2018 : Proceedings of the IEEE International Conference on Data Mining, Singapore, E1

conference

Algorithmic assurance: an active approach to algorithmic testing using Bayesian optimisation

Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Nguyen Vu, Svetha Venkatesh

(2018), Vol. 31, pp. 1-9, NeurIPS 2018 : Proceedings of the 32nd Conference on Neural Information Processing Systems, Montreal, Canada, E1

conference
2017

Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions

B Saha, S Gupta, D Phung, S Venkatesh

(2017), Vol. 53, pp. 179-206, Knowledge and Information Systems, C1

journal article

Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data

P Vellanki, T Duong, S Gupta, S Venkatesh, D Phung

(2017), Vol. 51, pp. 127-157, Knowledge and Information Systems, C1

journal article

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, T Slezak, M Height, S Venkatesh

(2017), Vol. 7, Scientific Reports, England, C1

journal article

A Framework for Mixed-Type Multioutcome Prediction with Applications in Healthcare

B Saha, S Gupta, D Phung, S Venkatesh

(2017), Vol. 21, pp. 1182-1191, IEEE Journal of Biomedical and Health Informatics, United States, C1

journal article

Comparative genetic variability in HIV-1 subtype C nef gene in early age groups of infants

U Sharma, P Gupta, M Singhal, S Singh, S Gupta, S Venkatesh, A Rai, M Husain

(2017), Vol. 89, pp. 1606-1619, Journal of medical virology, Chichester, Eng., C1

journal article

Expanding the horizons of melatonin use: An immunohistochemical neuroanatomic distribution of MT1 and MT2 receptors in human brain and retina

T Gupta, D Sahni, R Gupta, S Gupta

(2017), Vol. 66, pp. 58-66, Journal of the Anatomical Society of India, Amsterdam, The Netherlands, C1

journal article

Prevalence and trends in the neuropsychological burden of patients having intracranial tumors with respect to neurosurgical intervention

M Dhandapani, S Gupta, M Mohanty, S Gupta, S Dhandapani

(2017), Vol. 24, pp. 105-110, Annals of Neurosciences, Basel, Switzerland, C1

journal article

Regret bounds for transfer learning in Bayesian optimisation

A Shilton, S Gupta, S Rana, S Venkatesh

(2017), Vol. 54, pp. 1-9, AISTATS 2017 : Machine Learning Research : Proceedings of the 20th Artificial Intelligence and Statistics International Conference, Fort Lauderdale, Florida, E1

conference

Stable bayesian optimization

T Nguyen, S Gupta, S Rana, S Venkatesh

(2017), Vol. 54, pp. 578-591, PAKDD 2017 : Advances in Knowledge Discovery and Data Mining : Proceedings of the 21st Pacific-Asia Conference, Jeju, South Korea, E1

conference

High dimensional bayesian optimization with elastic gaussian process

S Rana, C Li, S Gupta, V Nguyen, S Venkatesh

(2017), pp. 1-9, ICML 2017 Proceedings of the International Conference in Machine Learning, Sydney, New South Wales, E1

conference

High dimensional bayesian optimization using dropout

C Li, S gupta, S Rana, V Nguyen, S Venkatesh, A Shilton

(2017), pp. 2096-2102, IJCAI 2017 : Proceedings of the 26th International Joint Confrerence on Artificial Intelligence, Melbourne, Victoria, E1

conference

Bayesian optimization in weakly specified search space

V Nguyen, S Gupta, S Rana, C Li, S Venkatesh

(2017), pp. 347-356, ICDM 2017 : Proceedings of the IEEE International Conference on Data Mining, New Orleans, La., E1

conference

Process-constrained batch Bayesian optimisation

P Vellanki, S Rana, S Gupta, D Rubin, A Sutti, T Dorin, M Height, P Sandars, S Venkatesh

(2017), Vol. 2017-December, pp. 3415-3424, NIPS 2017 : Proceedings of the 31st Conference of Neural Information Processing Systems, Long Beach, California, E1

conference

Regret for expected improvement over the best-observed value and stopping condition

V Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

(2017), pp. 1-16, ACML 2017 : Proceedings of the Ninth Asian Conference on Machine Learning, Seoul, Korea, E1

conference
2016

Flexible transfer learning framework for bayesian optimisation

T Joy, S Rana, S Gupta, S Venkatesh

(2016), Vol. 9651, pp. 102-114, Advances in knowledge discovery and data mining: 20th Pacific-Asia Conference, PAKDD 2016 Auckland, New Zealand, April 19-22, 2016 proceedings, part I, Berlin, Germany, B1

book chapter

Toxicity prediction in cancer using multiple instance learning in a multi-task framework

C Li, S Gupta, S Rana, W Luo, S Venkatesh, D Ashely, D Phung

(2016), Vol. 9651, pp. 152-164, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), B1

book chapter

Privacy aware K-means clustering with high utility

T Nguyen, S Gupta, S Rana, S Venkatesh

(2016), Vol. 9652, pp. 388-400, Advances in knowledge discovery and data mining: 20th Pacific-Asia Conference, PAKDD 2016 Auckland, New Zealand, April 19-22, 2016 proceedings, part I, Berlin, Germany, B1

book chapter

Modelling multilevel data in multimedia: A hierarchical factor analysis approach

S Gupta, D Phung, S Venkatesh

(2016), Vol. 75, pp. 4933-4955, Multimedia Tools and Applications, C1

journal article

Multiple task transfer learning with small sample sizes

B Saha, S Gupta, D Phung, S Venkatesh

(2016), Vol. 46, pp. 315-342, Knowledge and Information Systems, C1

journal article

Stabilizing l1-norm prediction models by supervised feature grouping

I Kamkar, S Gupta, D Phung, S Venkatesh

(2016), Vol. 59, pp. 149-168, Journal of Biomedical Informatics, United States, C1

journal article

A new transfer learning framework with application to model-agnostic multi-task learning

S Gupta, S Rana, B Saha, D Phung, S Venkatesh

(2016), Vol. 49, pp. 933-973, Knowledge and Information Systems, C1

journal article

Nonparametric discovery of movement patterns from accelerometer signals

T Nguyen, S Gupta, S Venkatesh, D Phung

(2016), Vol. 70, pp. 52-58, Pattern Recognition Letters, C1

journal article

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, J Yearwood, N Dimitrova, T Ho, S Venkatesh, M Berk

(2016), Vol. 18, Journal of Medical Internet Research, Canada, C1

journal article

Molecular epidemiological analysis of three hepatitis c virus outbreaks in Jammu and Kashmir state, India

S Chadha, U Sharma, A Chaudhary, C Prakash, S Gupta, S Venkatesh

(2016), Vol. 65, pp. 804-813, Journal of Medical Microbiology, England, C1-1

journal article

Flattened sheet-like fornix forming a "Cobra Hood" deformity: A previously unreported variant of fornix anatomy and its implication for surgical approaches to the third ventricle

T Gupta, D Sahni, R Tubbs, S Gupta

(2016), Vol. 64, pp. 943-946, Neurology India, Mumbai, India, C1

journal article

Newly established stem cell transplant program: 100 days follow-up of patients and its comparison with published Indian literature

A Tiwari, D Arora, R Dara, P Dorwal, N Sood, R Misra, S Gupta, V Raina, A Vaid

(2016), Vol. 37, pp. 168-173, Indian Journal of Medical and Paediatric Oncology, Mumbai, India, C1

journal article

Focusing on the delayed complications of fusing occipital squama to cervical spine for stabilization of congenital atlantoaxial dislocation and basilar invagination

P Salunke, S Sahoo, S Sood, K Mukherjee, S Gupta

(2016), Vol. 145, pp. 19-27, Clinical Neurology and Neurosurgery, Amsterdam, The Netherlands, C1

journal article

Differentially private multi-task learning

S Rana, S Rana, S Gupta, S Gupta, S Venkatesh, S Venkatesh

(2016), Vol. 9650, pp. 101-113, PAISI 2016 : Intelligence and Security Informatics : Proceedings of the 11th Pacific-Asia Workshop, Auckland, New Zealand, E1

conference

Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model

B Saha, S Gupta, Q Phung, S Venkatesh

(2016), pp. 537-542, 2016 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, E1

conference

Extracting key challenges in achieving sobriety through shared subspace learning

H Harikumar, T Nguyen, S Rana, S Gupta, R Kaimal, S Venkatesh

(2016), Vol. 10086, pp. 420-433, ADMA 2016 : Proceedings of the 12th Advanced Data Mining and Applications International Conference, Gold Coast, Queensland, E1

conference

Understanding behavioral differences between short and long-term drinking abstainers from social media

H Harikumar, T Nguyen, S Gupta, S Rana, R Kaimal, S Venkatesh

(2016), Vol. 10086, pp. 520-533, ADMA 2016 : Proceedings of the 12th Advanced Data Mining and Applications International Conference, Gold Coast, Queensland, E1

conference

Cascade Bayesian optimization

T Nguyen, S Gupta, S Rana, V Nguyen, S Venkatesh, K Deane, P Sanders

(2016), Vol. 9992, pp. 268-280, AI 2016: Advances in Artificial Intelligence : Proceedings of the Australasian Joint Conference, Hobart, Tasmania, E1

conference

Budgeted batch Bayesian optimization

V Nguyen, S Rana, S Gupta, C Li, S Venkatesh

(2016), pp. 1107-1112, ICDM 2016: Proceedings of the 16th IEEE International Conference on Data Mining, Barcelona, Spain, E1

conference

Hyperparameter tuning for big data using Bayesian optimisation

T Theckel Joy, S Rana, S Gupta, S Venkatesh

(2016), pp. 2574-2579, ICPR 2016: Proceedings of the 23rd International Conference on Pattern Recognition, Cancun, Mexico, E1

conference

Multiple adverse effects prediction in longitudinal cancer treatment

C Li, S Gupta, S Rana, T Nguyen, S Venkatesh, D Ashley, P Livingston

(2016), pp. 3156-3161, ICPR 2016: Proceedings of the 23rd International Conference on Pattern Recognition, Cancun, Mexico, E1

conference

Bayesian nonparametric Multiple Instance Regression

S Subramanian, S Rana, S Gupta, S Venkatesh, P Sivakumar, C Velayutham

(2016), pp. 3661-3666, ICPR 2016: Proceedings of the 23rd International Conference on Pattern Recognition, Cancun, Mexico, E1

conference

A bayesian nonparametric approach for multi-label classification

T Nguyen, S Gupta, S Rana, C Li, S Venkatesh

(2016), Vol. 63, pp. 254-269, ACML 2016: Proceedings of the 8th Asian Conference on Machine Learning, Hamilton, New Zealand, E1

conference

Stable clinical prediction using graph support vector machines

I Kamkar, S Gupta, C Li, D Phung, S Venkatesh

(2016), pp. 3332-3337, 2016 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, E1

conference
2015

Collaborating differently on different topics: a multi-relational approach to multi-task learning

S Gupta, S Rana, Q Phung, S Venkatesh

(2015), Vol. 9077, pp. 303-316, Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Vietnam, B1

book chapter

Prediciton of emergency events: a multi-task multi-label learning approach

B Saha, S Gupta, S Venkatesh

(2015), Vol. 9077, pp. 226-238, 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I, Vietnam, B1

book chapter

Stable feature selection with support vector machines

I Kamkar, S Gupta, Q Phung, S Venkatesh

(2015), Vol. 9457, pp. 298-308, AI 2015: Advances in artificial intelligence. 28th Australasian Joint Conference Canberra, ACT, Australia, November 30 - December 4, 2015 Proceedings, Berlin, Germany, B1

book chapter

Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso

I Kamkar, S Gupta, D Phung, S Venkatesh

(2015), Vol. 53, pp. 277-290, Journal of biomedical informatics, Amsterdam, The Netherlands, C1

journal article

Continuous discovery of co-location contexts from Bluetooth data

T Nguyen, S Gupta, S Venkatesh, Q Phung

(2015), Vol. 16, pp. 286-304, Pervasive and mobile computing, Amsterdam, The Netherlands, C1

journal article

Web search activity data accurately predict population chronic disease risk in the USA

T Nguyen, T Tran, W Luo, S Gupta, S Rana, Q Phung, M Nichols, L Millar, S Venkatesh, S Allender

(2015), Vol. 69, pp. 693-699, Journal of epidemiology and community health, London, Eng., C1

journal article

A predictive framework for modeling healthcare data with evolving clinical interventions

S Rana, S Gupta, Q Phung, S Venkatesh

(2015), Vol. 8, pp. 162-182, Statistical analysis and data mining, London, Eng., C1

journal article

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset

W Luo, T Nguyen, M Nichols, T Tran, S Rana, S Gupta, Q Phung, S Venkatesh, S Allender

(2015), Vol. 10, pp. 1-13, PLoS One, San Francisco, Calif., C1

journal article

Survival and failure patterns in atypical and anaplastic meningiomas: A single-center experience of surgery and postoperative radiotherapy

N Kumar, R Kumar, D Khosla, P Salunke, S Gupta, B Radotra

(2015), Vol. 11, pp. 735-739, Journal of Cancer Research and Therapeutics, India, C1-1

journal article

Serum lipid profile spectrum and delayed cerebral ischemia following subarachnoid hemorrhage: Is there a relation?

S Dhandapani, A Aggarwal, A Srinivasan, R Meena, S Gaudihalli, H Singh, M Dhandapani, K Mukherjee, S Gupta

(2015), Vol. 6, pp. S543-S548, Surgical Neurology International, United States, C1-1

journal article

Study of trends in anthropometric nutritional indices and the impact of adiposity among patients of subarachnoid hemorrhage

S Dhandapani, A Kapoor, S Gaudihalli, M Dhandapani, K Mukherjee, S Gupta

(2015), Vol. 63, pp. 531-536, Neurology India, India, C1-1

journal article

Is acetazolamide really useful in the management of traumatic cerebrospinal fluid rhinorrhea?

J Gosal, T Gurmey, G Kursa, P Salunke, S Gupta

(2015), Vol. 63, pp. 197-201, Neurology India, India, C1-1

journal article

Retrospective analysis of perioperative factors on outcome of patients undergoing surgery for Moyamoya disease

N Samagh, H Bhagat, V Grover, N Sahni, A Agarwal, S Gupta

(2015), Vol. 6, pp. 262-265, Journal of Neurosciences in Rural Practice, United States, C1-1

journal article

Prospective study of the correlation between admission plasma homocysteine levels and neurological outcome following subarachnoid hemorrhage: A case for the reverse epidemiology paradox?

S Dhandapani, S Goudihalli, K Mukherjee, H Singh, A Srinivasan, M Danish, S Mahalingam, M Dhandapani, S Gupta, N Khandelwal, S Mathuriya

(2015), Vol. 157, pp. 399-407, Acta Neurochirurgica, Austria, C1-1

journal article

Immunohistochemical profile of breast cancer patients at a tertiary care hospital in New Delhi, India

D Doval, A Sharma, R Sinha, K Kumar, A Dewan, H Chaturvedi, U Batra, V Talwar, S Gupta, S Singh, V Bhole, A Mehta

(2015), Vol. 16, pp. 4959-4964, Asian Pacific Journal of Cancer Prevention, Bangkok, Thailand, C1-1

journal article

Improved risk predictions via sparse imputation of patient conditions in electronic medical records

B Saha, S Gupta, S Venkatesh

(2015), pp. 1-10, DSAA 2015: IEEE International Conference on Data Science and Advanced Analytics, Paris, France, E1

conference

Differentially private random forest with high utility

S Rana, S Gupta, S Venkatesh

(2015), pp. 955-960, ICDM 2015: Proceedings of the 15th IEEE International Conference on Data Mining, Atlantic City, New Jersey, E1

conference

What shall i share and with whom? A multi-task learning formulation using multi-faceted task relationships

S Gupta, S Rana, Q Phung, S Venkatesh

(2015), pp. 703-711, SDM 2015: Proceedings of the 15th SIAM International Conference on Data Mining, Vancouver, British Columbia, E1

conference
2014

Learning latent activities from social signals with hierarchical dirichlet processes

D Phung, T Nguyen, S Gupta, S Venkatesh

(2014), pp. 149-174, Plan, activity, and intent recognition : theory and practice, Boston, Mass., B1

book chapter

Intervention-driven predictive framework for modeling healthcare data

S Rana, S Gupta, D Phung, S Venkatesh

(2014), Vol. 8443 Part 1, pp. 497-508, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Berlin, Germany, B1

book chapter

A matrix factorization framework for jointly analyzing multiple nonnegative data sources

S Gupta, S Gupta, Q Phung, Q Phung, B Adams, B Adams, S Venkatesh, S Venkatesh

(2014), Vol. 3, pp. 151-170, Data mining for service, Berlin, Germany, B1-1

book chapter

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, R Kennedy, A Broad, D Campbell, D Kipp, M Singh, M Khasraw, L Matheson, D Ashley, S Venkatesh

(2014), Vol. 4, pp. 1-7, BMJ open, London, England, C1

journal article

A framework for feature extraction from hospital medical data with applications in risk prediction

T Truyen, W Luo, P Dinh, S Gupta, S Rana, R Kennedy, A Larkins, S Venkatesh

(2014), Vol. 15, pp. 1-9, BMC Bioinformatics, London, Eng., C1

journal article

Cystic spinal schwannomas: A short series of six cases. Can we predict them preoperatively?

A Savardekar, N Singla, S Mohindra, C Ahuja, S Gupta

(2014), Vol. 5, pp. S349-S353, Surgical Neurology International, United States, C1-1

journal article

Histopathology of subcutaneously preserved autologous bone flap after decompressive craniectomy: A prospective study

N Singla, S Parkinson Singh, S Gupta, M Karthigeyan, B Radotra

(2014), Vol. 156, pp. 1369-1373, Acta Neurochirurgica, Austria, C1-1

journal article

The clinical profile, management, and overall outcome of aneurysmal subarachnoid hemorrhage at the neurosurgical unit of a tertiary care center in India

H Sodhi, A Savardekar, S Mohindra, R Chhabra, V Gupta, S Gupta

(2014), Vol. 5, pp. 118-126, Journal of Neurosciences in Rural Practice, United States, C1-1

journal article

Anatomy of the tentorial segment of the trochlear nerve in reference to its preservation during surgery for skull base lesions

T Gupta, S Gupta, D Sahni

(2014), Vol. 36, pp. 967-971, Surgical and Radiologic Anatomy, Germany, C1-1

journal article

Long-term outcome in surviving patients after clipping of intracranial aneurysms

S Gupta, R Chhabra, S Mohindra, A Sharma, S Mathuriya, A Pathak, M Tewari, K Mukherji, N Singla, P Salunke, A Umredkar, V Khosla

(2014), Vol. 81, pp. 316-321, World Neurosurgery, United States, C1-1

journal article

Fixed-lag particle filter for continuous context discovery using Indian Buffet Process

C Nguyen, S Gupta, S Venkatesh, Dinh Phung

(2014), pp. 20-28, PerCom 2014 : proceedings of the IEEE Pervasive Computing and Communications 2014 international conference, Budapest, Hungary, E1

conference

A bayesian nonparametric framework for activity recognition using accelerometer data

T Nguyen, S Gupta, S Venkatesh, D Phung

(2014), pp. 2017-2022, ICPR 2014 : Proceedings of the 22nd International Conference on Pattern Recognition, Stockholm, Sweden, E1

conference

Keeping up with innovation: a predictive framework for modeling healthcare data with evolving clinical interventions

S Gupta, S Rana, Q Phung, S Venkatesh

(2014), pp. 235-243, SDM 2014: Proceedings of the 14th SIAM International Conference on Data Mining 2014, Philadelphia, Pennsylvania, E1-1

conference
2013

Regularized nonnegative shared subspace learning

S Gupta, D Phung, B Adams, S Venkatesh

(2013), Vol. 26, pp. 57-97, Data mining and knowledge discovery, Boston, Mass., C1-1

journal article

Connectivity, online social capital, and mood : a Bayesian nonparametric analysis

D Phung, S Gupta, T Nguyen, S Venkatesh

(2013), Vol. 15, pp. 1316-1325, IEEE transactions on multimedia, Piscataway, N.J., C1

journal article

Treatment of ruptured saccular aneurysms of the fenestrated vertebrobasilar junction with balloon remodeling technique: A short case series and review of the literature

V Gupta, C Ahuja, N Khandelwal, A Kumar, S Gupta

(2013), Vol. 19, pp. 289-298, Interventional Neuroradiology, United States, C1-1

journal article

Vasospasm following aneurysmal subarachnoid hemorrhage: Thrombocytopenia a marker

A Aggarwal, P Salunke, H Singh, S Gupta, R Chhabra, N Singla, A Sachdeva

(2013), Vol. 4, pp. 257-261, Journal of Neurosciences in Rural Practice, United States, C1-1

journal article

Is ligation and division of anterior third of superior sagittal sinus really safe?

P Salunke, H Sodhi, A Aggarwal, C Ahuja, S Dhandapani, R Chhabra, S Gupta

(2013), Vol. 115, pp. 1998-2002, Clinical Neurology and Neurosurgery, Netherlands, C1-1

journal article

Isolated tumorous Langerhans cell histiocytosis of the brainstem: A diagnostic and therapeutic challenge

A Savardekar, M Tripathi, D Bansal, K Aiphei, S Gupta

(2013), Vol. 12, pp. 258-261, Journal of Neurosurgery: Pediatrics, United States, C1-1

journal article

Home based neuropsychological rehabilitation in severe traumatic brain injury: A case report

M Mohanty, S Gupta

(2013), Vol. 20, pp. 31-35, Annals of Neurosciences, United States, C1-1

journal article

Epidermal growth factor receptor mutation in lung adenocarcinoma in India: A single center study

D Doval, S Azam, U Batra, K Choudhury, V Talwar, S Gupta, A Mehta

(2013), Vol. 12, pp. 1-8, Journal of Carcinogenesis, Mumbai, India, C1-1

journal article

Interactive browsing system for anomaly video surveillance

T Nguyen, D Phung, S Gupta, S Venkatesh

(2013), pp. 384-389, ISSNIP 2013 : Sensing the future : Proceedings of the IEEE 8th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Victoria, E1

conference

Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes

T Nguyen, D Phung, S Gupta, S Venkatesh

(2013), pp. 47-55, PerCom 2013 : Proceedings of the 11th IEEE International Conference on Pervasive Computing and Commmunications, San Diego, California, E1

conference

Factorial multi-task learning : a Bayesian nonparametric approach

S Gupta, Q Phung, S Venkatesh

(2013), pp. 1694-1702, ICML 2013 : Proceedings of the Machine Learning 2013 International Conference, Atlanta, Ga., E1-1

conference
2012

The Possibility of Symbolic Violence in Interviews With Young People Experiencing Homelessness

D Farrugia, D Farrugia

(2012), pp. 109-121, Negotiating Ethical Challenges in Youth Research, London, Eng., C1

journal article

Linezolid: An effective, safe and cheap drug for patients failing multidrug-resistant tuberculosis treatment in India

R Singla, J Caminero, A Jaiswal, N Singla, S Gupta, R Bali, D Behera

(2012), Vol. 39, pp. 956-962, European Respiratory Journal, England, C1-1

journal article

A bayesian nonparametric joint factor model for learning shared and individual subspaces from multiple data sources

S Gupta, D Phung, S Venkatesh

(2012), pp. 200-212, SDM 2012 : Proceedings of the 12th SIAM International Conference on Data Mining, Anaheim, Calif., E1

conference

A nonparametric Bayesian Poisson Gamma model for count data

S Gupta, D Phung, S Venkatesh

(2012), pp. 1815-1818, ICPR 2012 : Proceedings of 21st International Conference on Pattern Recognition, Tsubuka Science City, Japan, E1

conference

A slice sampler for restricted hierarchical beta process with applications to shared subspace learning

S Gupta, D Phung, S Venkatesh

(2012), pp. 316-325, UAI 2012 : Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, Catalina Island, California, E1

conference
2011

A Bayesian framework for learning shared and individual subspaces from multiple data sources

S Gupta, D Phung, B Adams, S Venkatesh

(2011), pp. 136-147, PAKDD 2011 : Advances in knowledge discovery and data mining : 15th Pacific-Asia Conference, Shenzhen, China, May 24-27, 2011, proceedings, part II, Shenzhen, China, E1-1

conference

A matrix factorization framework for jointly analyzing multiple nonnegative data source

S Gupta, D Phung, B Adams, S Venkatesh

(2011), pp. 6-15, Proceedings of the 9th Workshop on Text Mining, in conjunction with the 11th SIAM International Conference on Data Mining, Mesa, Ariz., E1-1

conference

Automatic summarization of broadcast cricket videos

Y Kumar, S Gupta, B Kiran, K Ramakrishnan, C Bhattacharyya

(2011), pp. 222-225, ISCE 2011 : Proceedings of the IEEE International Symposium on Consumer Electronics, Singapore, E1-1

conference
2010

A child with suprasellar mass and ascites

S Das, A Bhansali, V Upreti, P Dutta, S Gupta, R Ananthraman, R Walia

(2010), Vol. 2010, pp. bcr0620092030-bcr0620092030, BMJ Case Reports, England, C1-1

journal article

Nonnegative shared subspace learning and its application to social media retrieval

S Gupta, D Phung, B Adams, T Tran, S Venkatesh

(2010), pp. 1169-1178, KDD 2010 : Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, D. C., E1-1

conference
2009

Risk factors for new pulmonary tuberculosis patients failing treatment under the revised national tuberculosis control programme, India

R Singla, D Srinath, S Gupta, P Visalakshi, U Khalid, N Singla, U Gupta, S Bharty, D Behera

(2009), Vol. 13, pp. 521-526, International Journal of Tuberculosis and Lung Disease, France, C1-1

journal article
2008

Learning feature trajectories using Gabor Filter Bank for human activity segmentation and recognition

S Gupta, Y Kumar, K Ramakrishnan

(2008), pp. 111-118, ICVGIP 2008 : Proceedings of the 6th Indian Conference on Computer Vision, Graphics and Image Processing, Bhubaneswar, India, E1-1

conference
2006

Gabapentin versus nortriptyline in post-herpetic neuralgia patients: A randomized, double-blind clinical trial - The GONIP Trial

K Chandra, N Shafig, P Pandhi, S Gupta, S Malhotra

(2006), Vol. 44, pp. 358-363, International Journal of Clinical Pharmacology and Therapeutics, Germany, C1-1

journal article

Cerebellar aspergillosis in an infant: Case report

S Mohindra, R Gupta, S Mohindra, S Gupta, K Vaiphei

(2006), Vol. 58, pp. E587-E587, Neurosurgery, United States, C1-1

journal article
2005

A multicenter phase II study of gemcitabine, paclitaxel, and cisplatin in chemonaïve advanced ovarian cancer

S Gupta, S John, R Naik, R Arora, B Selvamani, J Fuloria, N Ganesh, B Awasthy

(2005), Vol. 98, pp. 134-140, Gynecologic Oncology, Amsterdam, The Netherlands, C1-1

journal article
2004

Laboratory markers associated with progression of HIV infection

V Gupta, S Gupta

(2004), Vol. 22, pp. 7-15, Indian Journal of Medical Microbiology, C1-1

journal article
2001

Haemophilic pseudotumour of the paranasal sinuses: Management with radiotherapy and factor replacement therapy

S Gupta, B Mohapatra, S Ghai, A Seith, R Kashyap, R Sharma, V Choudhry

(2001), Vol. 7, pp. 595-599, Haemophilia, England, C1-1

journal article

Anaesthetic and intensive care aspects of spinal injury

V Grover, M Tewari, S Gupta, K Kumar

(2001), Vol. 49, pp. 11-18, Neurology India, India, C1-1

journal article
2000

New grading system to predict resectability of anterior clinoid meningiomas

A Goel, S Gupta, K Desai, V Dolenc, T Kawase

(2000), Vol. 40, pp. 610-617, Neurologia Medico-Chirurgica, Japan, C1-1

journal article

Quantitative anatomy of the lateral masses of the atlas and axis vertebrae

S Gupta, A Goel

(2000), Vol. 48, pp. 120-125, Neurology India, India, C1-1

journal article
1989

Spondylometaphyseal dysplasia with hypercalcemia

A Bagga, R Srivastava, S Gupta, A Gupta

(1989), Vol. 19, pp. 551-552, Pediatric Radiology, Germany, C1-1

journal article
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TRF: Learning Kernels with Tuned Random Features

Alistair Shilton, Sunil Gupta, Santu Rana, Arun Venkatesh, Svetha Venkatesh

(), Vol. 36, pp. 8286-8294, Proceedings of the AAAI Conference on Artificial Intelligence, E1

conference

Funded Projects at Deakin

Australian Competitive Grants

ARC Research Hub for Digital Enhanced Living

Prof Kon Mouzakis, Prof Svetha Venkatesh, Prof Anthony Maeder, Prof Alison Hutchinson, Prof Michael Berk, Prof Ralph Maddison, Prof Abbas Kouzani, Prof Rajesh Vasa, Prof Helen Christensen, Prof Patricia Williams, Prof John Yearwood, Prof Susan Gordon, Prof David Powers, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, Prof Truyen Tran, Prof Sunil Gupta, Dr Wei Luo, A/Prof Mohamed Abdelrazek, Dr Felix Tan, Prof Henning Langberg, A/Prof Lars Kayser, Prof Finn Kensing, Prof Freimut Bodendorf, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Fonda Voukelatos, Mr John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, Nicole Cockayne, David Varley, Dr Leonard Hoon, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Prof Deborah Parker, Dr Scott Barnett, Ms Sharon Grocott, Dr Tom McClean, Prof Jean-Guy Schneider, Dr Jessica Rivera Villicana, Prof Nilmini Wickramasinghe, A/Prof Carsten Rudolph, Mr Fernando Escorcia, Dr Gnana Bharathy

ARC Industrial Transformation Research Hubs

  • 2023: $18,750
  • 2021: $388,477
  • 2020: $385,381
  • 2019: $399,716
  • 2018: $449,083
  • 2017: $601,698

A Generic Framework for Verifying Machine Learning Algorithms

Prof Svetha Venkatesh, Prof Sunil Gupta, A/Prof Santu Rana, Prof Truyen Tran

ARC - Discovery Projects

  • 2023: $133,116
  • 2022: $125,478
  • 2021: $122,286

Optimising treatments in mental health using AI

Prof Helen Christensen, Prof Svetha Venkatesh, Prof Henry Cutler, Ms Ros Knight, Dr Martin Laverty, Prof Sunil Gupta, A/Prof Santu Rana, Prof Truyen Tran, Dr Thomas Quinn, Prof Rajesh Vasa, Prof Kon Mouzakis

MRFF (DISER) - Applied Artificial Intelligence Research in Health

  • 2023: $690,221
  • 2022: $999,770
  • 2021: $1,431,416

Other Public Sector Funding

Al Algorithmic Assurance

Prof Svetha Venkatesh, Prof Sunil Gupta, A/Prof Santu Rana, Prof Truyen Tran, Dr Anh Cat Le Ngo, Dr Phuoc Nguyen, Mr Stephan Jacobs, Dr Dang Nguyen

Department of Defence

  • 2021: $248,140
  • 2020: $208,820
  • 2019: $80,640

Defence Applied Al Experiential CoLab

Prof Svetha Venkatesh, Prof Sunil Gupta, A/Prof Santu Rana, Prof Truyen Tran

DSTO Grant - Research - Defence Science & Technology Organisation

  • 2021: $100,000
  • 2020: $873,495

In relation to Assuring an off-the-shelf AI algorithm

Prof Sunil Gupta, Prof Truyen Tran, A/Prof Santu Rana, Prof Svetha Venkatesh, Dr Phuoc Nguyen, Mr Tiep-Trong Nguyen, Mr Stephan Jacobs

Defence Science and Technology Group - Department of Defence

  • 2022: $85,000
  • 2021: $168,034

Coupled self-supervised learning and deep reasoning for improved processing of noisy and dynamic multimodal data from multiple sources.

Prof Truyen Tran, A/Prof Shannon Ryan, Prof Sunil Gupta, A/Prof Santu Rana, Prof Svetha Venkatesh

Department of Defence

  • 2022: $105,364

Machine-learning based trajectory modelling.

A/Prof Shannon Ryan, Prof Sunil Gupta, Mr Stephan Jacobs, Mr Mahad Rashid

Department of Defence

  • 2022: $44,828

Coupled self-supervised learning and deep reasoning for improved processing of noisy and dynamic multimodal data from multiple sources

Prof Truyen Tran, A/Prof Shannon Ryan, Prof Sunil Gupta, A/Prof Santu Rana, Prof Svetha Venkatesh

Defence Science and Technology Group - Department of Defence

  • 2023: $423,000

Industry and Other Funding

ARC Research Hub for Digital Enhanced Living

Prof Kon Mouzakis, Prof Svetha Venkatesh, Prof Anthony Maeder, Prof Alison Hutchinson, Prof Michael Berk, Prof Ralph Maddison, Prof Abbas Kouzani, Prof Rajesh Vasa, Prof Helen Christensen, Prof Patricia Williams, Prof John Yearwood, Prof Susan Gordon, Prof David Powers, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, Prof Truyen Tran, Prof Sunil Gupta, Dr Wei Luo, A/Prof Mohamed Abdelrazek, Dr Felix Tan, Prof Henning Langberg, A/Prof Lars Kayser, Prof Finn Kensing, Prof Freimut Bodendorf, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Fonda Voukelatos, Mr John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, Nicole Cockayne, David Varley, Dr Leonard Hoon, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Prof Deborah Parker, Dr Scott Barnett, Ms Sharon Grocott, Dr Tom McClean, Prof Jean-Guy Schneider, Dr Jessica Rivera Villicana, Prof Nilmini Wickramasinghe, A/Prof Carsten Rudolph, Mr Fernando Escorcia, Dr Gnana Bharathy

Uniting AgeWell, Dementia Australia (Alzheimer's Australia) Vic Inc, Aged Care & Housing Group Inc, goAct, Health Metrics, NeoProducts Pty Ltd, Unisono Pty Ltd, Interrelate Limited, Black Dog Institute, Uniting NSW.ACT, Cancer Council Victoria Grant - Research

  • 2022: $793,130
  • 2020: $553,025
  • 2019: $378,745

iCetana - Phase 1 Examine and compare state-of-art methods in background/foreground separation

Prof Svetha Venkatesh, A/Prof Santu Rana, Prof Sunil Gupta, Dr Budhaditya Saha

iCetana Pty Ltd

  • 2020: $50,000
  • 2018: $100,000
  • 2017: $200,000

Identification of Blood RNA Biomarkers to Measure Disease Progression in Parkinson's Disease.

Prof Sunil Gupta, Prof Svetha Venkatesh, Dr Thin Nguyen

Parkinson's NSW Limited

  • 2021: $42,500
  • 2020: $42,500

Scale up of Boron Nitride Nanosheet manufacturing and validation of commercial applications.

Prof Svetha Venkatesh, Prof Sunil Gupta, Dr Julian Berk

White Graphene Limited

  • 2024: $174,655
  • 2023: $318,148

Other Funding Sources

The CRC-P for Advanced Hybrid Batteries

Prof Patrick Howlett, Prof Maria Forsyth, A/Prof Robert Kerr, Prof Svetha Venkatesh, Prof Sunil Gupta, A/Prof Santu Rana

Cooperative Research Centres (CRC) Projects Program, Department of Industry, Innovation and Science.

  • 2024: $10,000
  • 2023: $522,192
  • 2022: $189,722
  • 2021: $295,583
  • 2020: $170,546

Supervisions

Executive Supervisor
2021

Deepthi Praveenlal Kuttichira

Thesis entitled: Tackling Practical Challenges in Neural Network Model Deployment

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Tang Thanh Nguyen

Thesis entitled: On Practical Reinforcement Learning: Provable Robustness, Scalability, and Statistical Efficiency

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Huu Phuc Luong

Thesis entitled: Bayesian Optimization for Discrete, Missing and Cost-sensitive Inputs

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2020

Julian Maxwell Andrew Berk

Thesis entitled: A Distributional Approach towards Efficient and Versatile Bayesian Optimisation

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Anil Ramachandran

Thesis entitled: Harnessing Auxiliary Knowledge Towards Efficient Bayesian Optimisation

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2019

Thanh Dai Nguyen

Thesis entitled: Addressing Practical Challenges of Bayesian Optimization

Doctor of Philosophy (Information Technology), School of Information Technology

2016

Iman Kamkar

Thesis entitled: Building Stable Predictive Models for Healthcare Applications: A Data-Driven Approach

Doctor of Philosophy (Information Technology), School of Information Technology

Co-supervisor
2020

Majid Abdolshah

Thesis entitled: Multi-objective Bayesian Optimisation and Its Applications

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Ang (Leon) Yang

Thesis entitled: Scalable Bayesian Optimization with Sparse Gaussian Process Models

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2019

Tinu Theckel Joy

Thesis entitled: Efficient Hyperparameter Tuning using Bayesian Optimization

Doctor of Philosophy (Information Technology), School of Information Technology

2018

Haripriya Harikumar

Thesis entitled: Machine learning to fight addiction using social media

Doctor of Philosophy (Information Technology), School of Information Technology

Associate Supervisor
2024

Xuan Duc Nguyen

Thesis entitled: Learning Dependency Structures Through Time Using Neural Networks

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2022

Arun Kumar Anjanapura Venkatesh

Thesis entitled: Accelerating Bayesian Optimisation with Advanced Kernel Learning Methods

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2015

Cong Thuong Nguyen

Thesis entitled: Bayesian nonparametric learning of contexts and activities from pervasive signals

Doctor of Philosophy (Information Technology), School of Information Technology