Our team and publications

Our team at PRaDA is led by Director Professor Svetha Venkatesh. We have a number of academic and support staff working hard to advance our knowledge and use of data.

Director

ARC Australian Laureate Fellow
Alfred Deakin Professor Svetha Venkatesh

Leadership

Associate Professor
Santu Rana

Associate Professor
Sunil Gupta

Associate Professor
Truyen Tran

Members

Name
Associate Professor
Dr Santu Rana
Associate Professor
Dr Sunil Gupta 
Senior Lecturer
Dr Vicky Mak 
Senior Lecturer
Dr Gang Li 
Lecturer in Mobile Computing and Apps
Dr Mohamed Abdelrazek
Research Fellow
Dr Stewart Greenhill
Associate Research Fellow
Dr Alistair Shilton
Associate Research Fellow
Dr Phuoc Nguyen
Lecturer In Computer Networks
Dr Sasan Adibi
iCetana Research Fellow
Dr Vuong Le
Associate Professor
Dr Truyen Tran
Lecturer In Information Technology
Dr Wei Luo
Research Fellow
Dr Thin Nguyen
Associate Research Fellow
Dr Adham Beykikhoshk
Project Manager, Research Grants and Contracts
Jeff Bilman
Administrative Officer
Shweta Gupta
Administrative Coordinator
Kim Ngan Pham
Associate Research Fellow
Dr David Rubin de Celis Leal
Associate Research Fellow
Mr Dang Nguyen
Research Assistant
Ms Manisha Senadeera
Research Assistant
Mr Xiaoxing Mo
Junior Programmer
Mr Uno Fang
Associate Research Fellow
Ms Haripriya Harikumar

Research Fellows

Name
Associate Research Fellow
Dr Alistair Shilton
Dr Cat Le
Associate Research Fellow
Dr Dang Nguyen
Associate Research Fellow
Dr David Rubin de Celis Leal
Dr Haripriya Harikumar
Dr Hung Tran
Dr Huong Tran
Dr Huong Ha
Research Fellow (Grade 2)
Dr Stewart Greenhill
Research Fellow (Grade 2)
Dr Thin Nguyen
Associate Research Fellow
Dr Phuoc Nguyen
Research Fellow
Dr Vuong Le

Research Assistants

Name
Stephan Jacobs
Manisha Senadeera

Administration

Name
Project Manager, Research Grants And Contracts
Jeff Bilman
Administrative Officer
Shweta Gupta
Administration Coordinator
Kim Ngan Pham

HDR Students

Name
Casual Academic
Ang (Leon) Yang
Arun Kumar Anjanapura Venkatesh
Deepthi Praveenlal Kuttichira
Scholarship Holder
Dinh Hung Nguyen
Duc Kien Do
Senior Lecturer
Duc Xuan Nguyen
Dung Nguyen
Huu Phuc Luong
Julian Maxwell Andrew Berk
Khanh Nguyen
Scholarship Holder
Majid Abdolshah
Research Assistant
Manisha Senadeera
Scholarship Holder
Romero Fernando Almeida Barata De Morais
Tang Thanh Nguyen
Casual Academic
Thai Hung Le
Thanh Dai Nguyen
Thanh Tung Hoang
Thao Minh Le
Trung Tin Pham

Alumni

Name
Monash University, Australia
Prof. Dinh Quoc Phung
University of Oxford, UK
Dr. Vu Nguyen
Dr. Cong Thuong Nguyen
Office for National Statistics, UK
Dr. Pratibha Vellanki
Phoebe Solutions, Melbourne, Australia
Dr. Iman Kamkar
Dr. Bo Dao
Dr. Thanh Binh Nguyen
Associate Research Fellow
Dr. Adham Beykikhoshk
Agersense, Melbourne, Australia
Dr. Shiva Gopakumar
Dr. Tinu T Joy
Dr. Thanh Dai Nguyen
Dr. Trang Pham Thi Minh
Monash University, Australia
Dr. Huu Viet Huynh

2019

Joy T, Rana S, Gupta S and Venkatesh S (2019), "A flexible transfer learning framework for Bayesian optimization with convergence guarantee", Expert Systems with Applications. Vol. 115, pp. 656-672. Elsevier.

Le H, Tran T and Venkatesh S (2019), "Learning to Remember More with Less Memorization", In ICLR.

Nguyen P, Tran T, Gupta S, Rana S and Venkatesh S (2019), "Incomplete Conditional Density Estimation for Fast Materials Discovery", In SDM.

Morais R, Le V, Tran T, Saha B, Mansour M and Venkatesh S (2019), "Learning regularity in skeleton trajectories for anomaly detection in videos", In CVPR. , pp. (To appear).

Thanh-Tung H, Tran T and Venkatesh S (2019), "Improving Generalization and Stability of Generative Adversarial Networks"", In ICLR.

Vellanki P, Rana S, Gupta S, Leal DRdC, Sutti A, Height M and Venkatesh S (2019), "Bayesian functional optimisation with shape prior", In AAAI.

2018

Joy T, Rana S, Gupta S and Venkatesh S (2019), "A flexible transfer learning framework for Bayesian optimization with convergence guarantee", Expert Systems with Applications. Vol. 115, pp. 656-672. Elsevier.

Le H, Tran T and Venkatesh S (2019), "Learning to Remember More with Less Memorization", In ICLR.

Nguyen P, Tran T, Gupta S, Rana S and Venkatesh S (2019), "Incomplete Conditional Density Estimation for Fast Materials Discovery", In SDM.

Morais R, Le V, Tran T, Saha B, Mansour M and Venkatesh S (2019), "Learning regularity in skeleton trajectories for anomaly detection in videos", In CVPR. , pp. (To appear).

Thanh-Tung H, Tran T and Venkatesh S (2019), "Improving Generalization and Stability of Generative Adversarial Networks", In ICLR.

Vellanki P, Rana S, Gupta S, Leal DRdC, Sutti A, Height M and Venkatesh S (2019), "Bayesian functional optimisation with shape prior", In AAAI.

2017

Dai Nguyen T, Gupta S, Rana S and Venkatesh S (2017), "Stable Bayesian Optimization", In Pacific-Asia Conference on Knowledge Discovery and Data Mining. , pp. 578-591.

Dao B, Nguyen T, Venkatesh S and Phung D (2017), "Latent sentiment topic modelling and nonparametric discovery of online mental health-related communities", International Journal of Data Science and Analytics. Vol. 4(3), pp. 209-231. Springer.

Li C, de Celis Leal DR, Rana S, Gupta S, Sutti A, Greenhill S, Slezak T, Height M and Venkatesh S (2017), "Rapid Bayesian optimisation for synthesis of short polymer fiber materials", Scientific reports. Vol. 7(1), pp. 5683. Nature Publishing Group.

Li C, Gupta S, Rana S, Nugyen V, Venkatesh S and Alistair S (2017), "High Dimensional Bayesian Optimization Using Dropout", In International Joint Conference on Artificial Intelligence. , pp. to appear.

Nguyen P, Tran T, Wickramasinghe N and Venkatesh S (2017), "Deepr: A Convolutional Net for Medical Records", IEEE journal of biomedical and health informatics. Vol. 21(1), pp. 22-30. IEEE.

Nguyen T, Larsen ME, ODea B, Phung D, Venkatesh S and Christensen H (2017), "Estimation of the prevalence of adverse drug reactions from social media", International Journal of Medical Informatics. Vol. 102, pp. 130-137. Elsevier.
[URL]

Nguyen T, Nguyen DT, Larsen ME, O'Dea B, Yearwood J, Phung D, Venkatesh S and Christensen H (2017), "Prediction of Population Health Indices from Social Media using Kernel-based Textual and Temporal Features", In Proceedings of the 26th International Conference on World Wide Web Companion. , pp. 99-107.

Nguyen T, Venkatesh S and Phung D (2017), "Academia versus social media: A psycho-linguistic analysis", Journal of Computational Science. Elsevier.

Nguyen V, Gupta S, Rana S, Li C and Venkatesh S (2017), "Regret for Expected Improvement over the Best-Observed Value and Stopping Condition", In Asian Conference on Machine Learning. , pp. 279-294.

Nguyen V, Gupta S, Rane S, Li C and Venkatesh S (2017), "Bayesian optimization in weakly specified search space", In Data Mining (ICDM), 2017 IEEE International Conference on. , pp. 347-356.

Pham T, Tran T, Phung D and Venkatesh S (2017), "Predicting healthcare trajectories from medical records: A deep learning approach", Journal of biomedical informatics. Vol. 69, pp. 218-229. Elsevier.

Pham T, Tran T, Phung DQ and Venkatesh S (2017), "Column Networks for Collective Classification", In AAAI. , pp. 2485-2491.

Rana S, Li C, Gupta S, Nguyen V and Venkatesh S (2017), "High dimensional bayesian optimization with elastic gaussian process", In International Conference on Machine Learning. , pp. 2883-2891.

Shilton A, Gupta S, Rana S and Venkatesh S (2017), "Regret Bounds for Transfer Learning in Bayesian Optimisation", In Artificial Intelligence and Statistics. , pp. 307-315.

Thin N, Hung N, Venkatesh S and Phung D (2017), "Estimating Support Scores of Autism Communities in Large-Scale Web Information Systems", In International Conference on Web Information Systems Engineering. , pp. 347-355.

Tran T, Phung D, Bui H and Venkatesh S (2017), "Hierarchical semi-Markov conditional random fields for deep recursive sequential data", Artificial Intelligence. Vol. 246, pp. 53-85. Elsevier.

Vellanki P, Duong T, Gupta S, Venkatesh S and Phung D (2017), "Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data", Knowledge and information systems. Vol. 51(1), pp. 127-157. Springer.

Vellanki P, Rana S, Gupta S, Rubin D, Sutti A, Dorin T, Height M, Sanders P and Venkatesh S (2017), "Process-constrained batch Bayesian optimisation", In Advances in Neural Information Processing Systems. , pp. 3417-3426.

Vu H, Nguyen TD, Travers A, Venkatesh S and Phung D (2017), "Energy-Based Localized Anomaly Detection in Video Surveillance", In Pacific-Asia Conference on Knowledge Discovery and Data Mining. , pp. 641-653.

2016

Arandjelović O, Pham DS and Venkatesh S (2016), "CCTV Scene Perspective Distortion Estimation From Low-Level Motion Features", IEEE Transactions on Circuits and Systems for Video Technology., May, 2016. Vol. 26(5), pp. 939-949.

Beykikhoshk A, Arandjelović O, Venkatesh S and Phung D (2016), "Analysing the History of Autism Spectrum Disorder using Topic Models", In Proceedings of the 3rd International Conference on Data Science and Advanced Analytics (DSAA '16)., Oct., 2016. , pp. TO APPEAR.

Budhaditya S, Gupta S, Phung D and Venkatesh S (2016), "Effective Sparse Imputation of Patient Conditions in Electronic Medical Records for Emergency Risk Predictions", Knowledge and Information Systems (KAIS).

Dao B, Nguyen T, Venkatesh S and Phung D (2016), "Effect of Social Capital on Emotion, Language Style and Latent Topics in Online Depression Community", In 12th IEEE-RIVF International Conference on Computing and Communication Technologies., November, 2016.

Dao B, Nguyen T, Venkatesh S and Phung D (2016), "Discovering Latent Affective Dynamics among Individuals in Online Mental Health-related Communities", In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME).

Do K, Tran T, Phung D and Venkatesh S (2016), "Outlier Detection on Mixed-Type Data: An Energy-based Approach", In International Conference on Advanced Data Mining and Applications (ADMA 2016). , pp. to appear.

Gopakumar S, Tran T, Luo W, Phung D and Venkatesh S (2016), "Forecasting patient outflow from wards having no real-time clinical data", In Proceedings of IEEE International Conference on Health Informatics (ICHI).

Gopakumar S, Tran T, Luo W, Phung D and Venkatesh S (2016), "Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data", JMIR Med Inform., Jul, 2016. Vol. 4(3), pp. e25.

Gopakumar S, Tran T, Phung D and Venkatesh S (2016), "Stabilizing Linear Prediction Models using Autoencoder", In 12th International Conference on Advanced Data Mining and Applications (ADMA). , pp. to appear.

Gupta S, Rana S, Saha B, Phung D and Venkatesh S (2016), "A new transfer learning framework with application to model-agnostic multi-task learning", Knowledge and Information Systems. , pp. 1-41.

Gupta SK, Rana S and Venkatesh S (2016), "Differentially Private Multi-task Learning", In Intelligence and Security Informatics: 11th Pacific Asia Workshop. PAISI 2016, Auckland, New Zealand, April 19, 2016, Proceedings. , pp. 101-113. Springer International Publishing.

Harikumar H, Nguyen T, Rana S, Gupta S, Kaimal R and Venkatesh S (2016), "Extracting Key Challenges in Achieving Sobriety through Shared Subspace Learning", In 12th International Conference on Advanced Data Mining and Applications (ADMA). , pp. to appear.

Harikumar H, Nguyen T, Rana S, Gupta S, Kaimal R and Venkatesh S (2016), "Understanding Behavioral Differences between Short and Long-term Drinking Abstainers from Social Media", In 12th International Conference on Advanced Data Mining and Applications (ADMA). , pp. to appear.

Huynh V, Phung D, Svetha V, Long N, Hoffman M and Bui H (2016), "Scalable Nonparametric Bayesian Multilevel Clustering", In The 32th Conference on Uncertainty in Artificial Intelligence., June, 2016.

Joy TT, Rana S, Gupta S and Venkatesh S (2016), "Multiple Recommendation for Bayesian optimization via Multi-Scale Search", In Proceedings of NIPS Workshop on Bayesian Optimization: Black-box Optimization and Beyond, BayesOpt 2016. , pp. 5.

Joy TT, Rana S, Gupta SK and Venkatesh S (2016), "Flexible Transfer Learning Framework for Bayesian Optimisation", In Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I. , pp. 102-114. Springer International Publishing.

Kamkar I, Gupta S, Li C, Phung D and Venkatesh S (2016), "Stable Clinical Prediction using Graph Support Vector Machines", In 23rd International Conference on Pattern Recognition (ICPR 2016)., Dec., 2016.

Kamkar I, Gupta SK, Phung D and Venkatesh S (2016), "Stabilizing l1-norm prediction models by supervised feature grouping", Journal of Biomedical Informatics . Vol. 59, pp. 149 - 168.

Karmakar C, Luo W, Tran T, Berk M and Venkatesh S (2016), "Predicting Risk of Suicide Attempt Using History of Physical Illnesses From Electronic Medical Records", JMIR Mental Health., Jul, 2016. Vol. 3(3), pp. e19.

Li C, Gupta S, Rana S, Nguyen V and Venkatesh S (2016), "Multiple Adverse Effects Prediction in Longitudinal Cancer Treatment", In Proceedings of the 23rd International Conference on Pattern Recognition. Cancun, Mexico , pp. (to appear).

Li C, Gupta Sunil Kand Rana S, Luo W, Venkatesh S, Ashely D and Phung D (2016), "Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework", In Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I. , pp. 152-164. Springer International Publishing.

Li C, Rana S, Gupta S, Nguyen V and Venkatesh S (2016), "High Dimensional Bayesian Optimization with Elastic Gaussian Process", In Proceedings of NIPS Workshop on Bayesian Optimization: Black-box Optimization and Beyond, BayesOpt 2016.

Li C, Rana S, Phung D and Venkatesh S (2016), "Data clustering using side information dependent Chinese restaurant processes", Knowledge and Information Systems. Vol. 47(2), pp. 463-488.

Li C, Rana S, Phung D and Venkatesh S (2016), "Dirichlet Process Mixture Models with Pairwise Constraints for Data Clustering", Annals of Data Science. Vol. 3(2), pp. 205-223.

Li C, Rana S, Phung D and Venkatesh S (2016), "Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records ", Knowledge-Based Systems . Vol. 99, pp. 168 - 182.

Luo W, Harvey R, Tran T, Phung D, Venkatesh S and Connor JP (2016), "Consistency of the Health of the Nation Outcome Scales (HoNOS) at inpatient-to-community transition", BMJ open. Vol. 6(4), pp. e010732. British Medical Journal Publishing Group.

Luo W, Huning EY, Tran T, Phung D and Venkatesh S (2016), "Screening for post 32-week preterm birth risk: how helpful is routine perinatal data collection?", Heliyon. Vol. 2(6), pp. e00119.

Nguyen D, Luo W, Phung D and Venkatesh S (2016), "Exceptional Contrast Set Mining: Moving beyond the deluge of the obvious", In Proceedings of the 29th Australasian Joint Conference on Artificial Intelligence (AI 2016), Hobart, Australia, December,. , pp. TO APPEAR.

Nguyen D, Luo W, Phung D and Venkatesh S (2016), "Control Matching via Discharge Code Sequences", In NIPS 2016 Workshop on Machine Learning for Health. , pp. 5.

Nguyen T, Borland R, Yearwood J, Yong H, Venkatesh S and Phung D (2016), "Discriminative cues for different stages of smoking cessation in online community", In Proceedings of the International Conference on Web Information Systems Engineering (WISE). Springer International Publishing.

Nguyen T, Gupta S, Venkatesh S and Phung D (2016), "Nonparametric discovery of movement patterns from accelerometer signals ", Pattern Recognition Letters . Vol. 70, pp. 52 - 58.

Nguyen T, Venkatesh S and Phung D (2016), "Large-scale stylistic analysis of formality in academia and social media", In Proceedings of the International Conference on Web Information Systems Engineering (WISE). Springer International Publishing.

Nguyen T, Venkatesh S and Phung D (2016), "Textual Cues for Online Depression in Community and Personal Settings", In 12th International Conference on Advanced Data Mining and Applications (ADMA). , pp. to appear.

Nguyen TD, Gupta S, Rana S, Nguyen V and Venkatesh S (2016), "Cascade Bayesian Optimization", In 29th Australasian Joint Conference on Artificial Intelligence (AI 2016), Hobart., December, 2016.

Nguyen TD, Gupta S, Rana S and Venkatesh S (2016), "Privacy Aware K-Means Clustering with High Utility", In Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part II. , pp. 388-400. Springer International Publishing.

Nguyen TD, Tran T, Phung D and Venkatesh S (2016), "Graph-induced restricted Boltzmann machines for document modeling ", Information Sciences . Vol. 328, pp. 60 - 75.

Nguyen T-B, Nguyen V, Venkatesh S and Phung D (2016), "Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes", In Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF, Auckland, New Zealand, April 19, 2016, Revised Selected Papers. , pp. 128-140. Springer International Publishing.

Nguyen T-B, Nguyen V, Venkatesh S and Phung D (2016), "MCNC: Multi-channel Nonparametric Clustering from Heterogeneous Data", In 23rd International Conference on Pattern Recognition (ICPR 2016)., Dec., 2016.

Nguyen V, Gupta S, Rana S, Li C and Venkatesh S (2016), "A Bayesian Nonparametric Approach for Multi-label Classification", In Proceedings of The 8th Asian Conference on Machine Learning. , pp. 254-269.

Nguyen V, Gupta S, Rana S, Li C and Venkatesh S (2016), "Think Globally, Act Locally: a Local Strategy for Bayesian Optimization", In Proceedings of NIPS Workshop on Bayesian Optimization: Black-box Optimization and Beyond, BayesOpt 2016. , pp. 5.

Nguyen V, Nguyen T, Le T, Phung D and Venkatesh S (2016), "One-pass Logistic Regression for Label-drift and Large-scale Classification on Distributed Systems", In IEEE International Conference on Data Mining (ICDM)., December, 2016. , pp. TO APPEAR.

Nguyen V, Rana S, Gupta S, Li C and Venkatesh S (2016), "Budgeted Batch Bayesian Optimization", In IEEE International Conference on Data Mining (ICDM)., December, 2016.

Pham D, Arandjelovic O and Venkatesh S (2016), "Achieving stable subspace clustering by post-processing generic clustering results", In International Joint Conference on Neural Networks.

Pham T, Tran T, Phung D and Venkatesh S (2016), "DeepCare: A Deep Dynamic Memory Model for Predictive Medicine", In Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part II. , pp. 30-41. Springer International Publishing.

Pham T, Tran T, Phung D and Venkatesh S (2016), "Faster Training of Very Deep Networks Via p-Norm Gates", In Proceedings of International Conference on Pattern Recognition. , pp. to appear.

Saha B, Gupta S, Phung D and Venkatesh S (2016), "Multiple task transfer learning with small sample sizes", Knowledge and Information Systems. Vol. 46(2), pp. 315-342. Springer.

Saha B, Gupta S, Phung D and Venkatesh S (2016), "Transfer Learning for Rare Cancer Problems via Discriminative Sparse Gaussian Graphical Model", In 23rd International Conference on Pattern Recognition (ICPR 2016).

Saha B, Nguyen T, Phung D and Venkatesh S (2016), "A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression", IEEE Journal of Biomedical and Health Informatics., July, 2016. Vol. 20(4), pp. 1008-1015.

Shilton A, Rana S, Gupta SK and Venkatesh S (2016), "A Simple Recursive Algorithm for calculating Expected Hypervolume Improvement", In Proceedings of NIPS Workshop on Bayesian Optimization: Black-box Optimization and Beyond, BayesOpt 2016.

Subramanian S, Rana S, Gupta S, Sivakumar PB, Velayutham S and Venkatesh S (2016), "Bayesian Nonparametric Multiple Instance Regression", In Proceedings of the 23rd International Conference on Pattern Recognition. Cancun, Mexico , pp. (to appear).

Tran T, Luo W, Phung D, Morris J, Rickard K and Venkatesh S (2016), "Preterm Birth Prediction: Deriving Stable and Interpretable Rules from High Dimensional Data", In Machine Learning in Healthcare.

Tran T, Phung D and Venkatesh S (2016), "Collaborative filtering via sparse Markov random fields", Information Sciences. Vol. 369, pp. 221237.

Tran T, Phung D and Venkatesh S (2016), "Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach", Knowledge and Information Systems. Vol. 47(1), pp. 157-188.

Tran T, Phung D and Venkatesh S (2016), "Neural Choice by Elimination via Highway Networks", In 5th PAKDD Workshop on Biologically Inspired Data Mining Techniques., April, 2016.

Vellanki P, Duong T, Gupta S, Venkatesh S and Phung D (2016), "Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data", Knowledge and Information Systems. , pp. 1-31.

Vellanki P, Greenhill S, Duong T, Phung D, Venkatesh S, Godwin J, Achary KV and Varkey B (2016), "Computer assisted autism interventions for India", In Proceedings of the 28th Australian Conference on Computer-Human Interaction. , pp. 618-622.

Venkatesh S and Christensen H (2016), "Using life's digital detritus to feed discovery", The Lancet Psychiatry. , pp. to appear.

2015

Arandjelović O, Pham D and Venkatesh S (2015), "Two maximum entropy based algorithms for running quantile estimation in non-stationary data streams", IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)., Sept, 2015. Vol. 25(9), pp. 1469-1479.

Arandjelović O, Pham D-S and Venkatesh S (2015), "The adaptable buffer algorithm for high quantile estimation in non-stationary data streams", In 2015 International Joint Conference on Neural Networks (IJCNN). , pp. 1-7.

Arandjelović O, Pham D-S and Venkatesh S (2015), "Efficient and accurate set-based registration of time-separated aerial images", Pattern Recognition. Vol. 48(11), pp. 3466-3476. Elsevier.

Arandjelovic O, Pham D-S and Venkatesh S (2015), "Groupwise Registration of Aerial Images", In Twenty-Fourth International Joint Conference on Artificial Intelligence., July, 2015.

Arandjelovic O, Pham D-S and Venkatesh S (2015), "Viewpoint distortion compensation in practical surveillance systems", In International Conference on Multimedia & Expo (ICME). [URL]

Beykikhoshk A, Arandjelović O, Phung D, Venkatesh S and Caelli T (2015), "Using Twitter to learn about the autism community", Social Network Analysis and Mining. Vol. 5(1), pp. 1-17.

Dao B, Nguyen T, Venkatesh S and Phung D (2015), "Nonparametric Discovery of Online Mental Health-Related Communities", In International Conference on Data Science and Advanced Analytics (DSAA2015). Paris, France , pp. 1-10.

Gopakumar S, Nguyen TD, Tran T, Phung D and Venkatesh S (2015), "Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records", In Advances in Knowledge Discovery and Data Mining. Vol. 9078, pp. 331-343. Springer International Publishing.

Gopakumar S, Tran T, Nguyen TD, Phung D and Venkatesh S (2015), "Stabilizing high-dimensional prediction models using feature graphs.", IEEE journal of biomedical and health informatics. Vol. 19(3), pp. 1044-1052.

Gupta S, Rana S, Phung D and Venkatesh S (2015), "What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships", In SIAM International Conference on Data Mining. Vancouver, Canada , pp. 703-711.

Gupta SK, Rana S, Phung D and Venkatesh S (2015), "Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning", In Advances in Knowledge Discovery and Data Mining. , pp. 303-316. Springer.

Huynh V, Phung D, Nguyen L, Venkatesh S and Bui HH (2015), "Learning Conditional Latent Structures from Multiple Data Sources", In Advances in Knowledge Discovery and Data Mining. , pp. 343-354. Springer.

Kamkar I, Gupta S, Phung D and Venkatesh S (2015), "Stable Feature Selection for Clinical Prediction: Exploiting ICD tree structure using Tree-Lasso", The Journal of Biomedical Informatics. , pp. 277-290.

Kamkar I, Gupta S, Phung D and Venkatesh S (2015), "Stable Feature Selection with Support Vector Machines", In The 28th Australasian Joint Conference on Artificial Intelligence. Paris, France , pp. 298-308.

Kamkar I, Gupta S, Phung D and Venkatesh S (2015), "Exploiting Feature Relationships Towards Stable Feature Selection", In International Conference on Data Science and Advanced Analytics (DSAA2015). Paris, France , pp. 1-10.

Li C, Rana S, Phung D and Venkatesh S (2015), "Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints", In Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Ho Chi Minh City, Vietnam , pp. 92-105.

Luo W, Nguyen T, Nichols M, Tran T, Rana S, Gupta S, Phung D, Venkatesh S and Allender S (2015), "Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset", PLoS ONE., 05, 2015. Vol. 10(5), pp. e0125602. Public Library of Science.

Nguyen D, Luo W, Phung D and Venkatesh S (2015), "Understanding toxicities and complications of cancer treatment: A data mining approach", In 28th Australasian Joint Conference on Artificial Intelligence. , pp. 431-443.

Nguyen T, Duong T, Venkatesh S and Phung D (2015), "Autism Blogs: Expressed Emotion, Language Styles and Concerns in Personal and Community Settings", IEEE Transactions on Affective Computing., July, 2015. Vol. 6(3), pp. 312-323.

Nguyen T, Gupta S, Venkatesh S and Phung D (2015), "Continuous discovery of co-location contexts from Bluetooth data", Pervasive and Mobile Computing. Vol. 16, pp. 286-304. Elsevier.

Nguyen T, O'Dea B, Larsen M, Phung D, Venkatesh S and Christensen H (2015), "Differentiating sub-groups of online depression-related communities using textual cues", In International Conference on Web Information Systems Engineering. Springer International Publishing.

Nguyen T, Tran T, Luo W, Gupta S, Rana S, Phung D, Nichols M, Millar L, Venkatesh S and Allender S (2015), "Web search activity data accurately predict population chronic disease risk in the USA", Journal of Epidemiology and Community Health. Vol. 69(7), pp. 693-699.

Nguyen TD, Tran T, Phung D and Venkatesh S (2015), "Tensor-variate Restricted Boltzmann Machines", In AAAI Conference on Artificial Intelligence. Austin Texas, USA, January 25-30, 2015. , pp. 2887-2893.

Nguyen V, Phung D, Pham D-S and Venkatesh S (2015), "Bayesian Nonparametric Approaches to Abnormality Detection in Video Surveillance", Annals of Data Science. , pp. 1-21. Springer Berlin Heidelberg.

Nguyen V, Phung D and Venkatesh S (2015), "Topic Model Kernel Classification With Probabilistically Reduced Features", Journal of Data Science. Vol. 13(2), pp. 323-340.

Nguyen V, Phung D, Venkatesh S and Bui HH (2015), "A Bayesian Nonparametric Approach to Multilevel Regression", In Advances in Knowledge Discovery and Data Mining. , pp. 330-342. Springer.

Pham D, Arandjelović O and Venkatesh S (2015), "Detection of dynamic background due to swaying movements from motion features.", IEEE Transactions on Image Processing (TIP).

Rana S, Gupta S, Phung D and Venkatesh S (2015), "A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions", Statistical Analysis in Data Mining. Vol. 8(3), pp. 162-182. Wiley Online Library.

Rana S, Gupta S and Venkatesh S (2015), "Differentially private random forest with high utility", In IEEE International Conference on Data Mining. Atlantic City, USA , pp. (accepted).

Saha B, Gupta S and Venkatesh S (2015), "Improved Risk Predictions via Sparse Imputation of Patient Conditions in Electronic Medical Records", In IEEE International Conference on Data Science and Advanced Analytics. , pp. 1-10.

Saha B, Gupta SK and Venkatesh S (2015), "Prediciton of Emergency Events: A Multi-Task Multi-Label Learning Approach", In Advances in Knowledge Discovery and Data Mining. , pp. 226-238. Springer.

Tran T, Nguyen TD, Phung D and Venkatesh S (2015), "Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)", Journal of biomedical informatics. Vol. 54, pp. 96-105. Elsevier.

Tran T, Phung D and Venkatesh S (2015), "Tree-based iterated local search for Markov random fields with applications in image analysis", Journal of Heuristics. Vol. 21(1), pp. 25-45. Springer.

Zhang X, Pham D-S, Phung D, Liu W, Saha B and Venkatesh S (2015), "Visual Object Clustering via Mixed-Norm Regularization", In IEEE Winter Conference on Applications of Computer Vision (WACV). , pp. 1030-1037.

Zhang X, Pham D-S, Venkatesh S, Liu W and Phung D (2015), "Mixed-norm sparse representation for multi view face recognition", Pattern Recognition. Vol. 48(9), pp. 2935-2946. Elsevier.

Zhang X, Phung D, Venkatesh S, Pham D-S and Liu W (2015), "Multi-View Subspace Clustering for Face Images", In Digital Image Computing: Techniques and Applications (DICTA), 2015 International Conference on. , pp. 1-7.

2014

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2012

Theses