PhD (Monash), OELP (Oxford), PCMAI (MIT), HETC (Harvard), GCTE (VU)
Dr Anwaar Ulhaq is serving as a senior lecturer and deputy leader, Machine Vision and Digital Health Research in the School of Computing, Mathematics and Engineering, Charles Sturt University. Anwaar holds a PhD (Artificial Intelligence) from Monash University, Australia. He has completed professional education in machine learning and artificial intelligence from the Massachusetts Institute of Technology (MIT). He has extensive teaching and research experience from reputed Australian universities including Victoria University, Swinburne University of Technology and Central Queensland University. He has also worked as a research fellow at the Institute for Sustainable Industries & Liveable Cities, Victoria University, Australia. He received Faculty Research Award in 2021 and Teaching Excellence Award in 2019 at Charles Sturt. His research interests include artificial creativity, deep learning, data analytics and computer vision. He has published more than 50 peer-reviewed papers in reputed journals and conferences.
Anwaar's Google Scholar profile can be found at: https://scholar.google.com/citations?user=2p4PBrkAAAAJ&hl=en
Douglas Pinto Gomes (PhD):
Douglas (2020) Vegetation High-Impedance Fault Detection and Characterization using Machine Learning. Ph.D. thesis, Victoria University
Ravinder Singh (PhD):
Singh, Ravinder (2021) Extracting Human Behaviour and Personality Traits from Social Media. Ph.D. thesis, Victoria University
Khan, A., Asim, W., Anwaar Ulhaq, Robinson, R.W. A Multiview Semantic Vegetation Index for Robust Estimation of Urban Vegetation Cover. Remote Sens. 2022, 14, 228. https://doi.org/10.3390/rs14010228
Anwaar Ulhaq Adams, P., Cox, T. E., Khan, A., Low, T. & Paul, M., Automated detection of animals in low-resolution airborne thermal imagery 19 Aug 2021, In Remote Sensing. 13, 16, p. 1-14 14 p., 3276.
Horry, M., Chakraborty, S., Pradhan, B., Paul, M., Gomes, D., Anwaar Ulhaq & Alamri, A., Deep Mining Generation of Lung Cancer Malignancy Models from Chest X-ray Images., In Sensors. p. 6655 1(19).
Islam, M. R., Abdul Kader Jilani, M. M., Miah, S. J., Akter, S. & Anwaar Ulhaq.,, Discovering Tourist Preference for Electing Destinations: A Pattern Mining based Approach 2021, (In Asia Pacific Journal of Tourism Research.
Anwaar Ulhaq & Wahlstrom, K., 2021. Exploring co-design considerations for embedding privacy in holochain apps: A value-sensitive design perspective Burmeister, O., d'Aoust, P., Fernando, A., 4 p.
Gomes, D., Anwaar Ulhaq Paul, M., Horry, M. J., Chakraborty, S., Saha, M., Debnath, T. & Rahaman, M., Features of ICU admission in x-ray images of COVID-19 patients, 2021, IEEE ICIP 2021 Proceedings. IEEE Xplore, 5 p.
Poulsen, A. & Anwaar Ulhaq., 2021 Fundamental rights and smart health technologies, , Smart technologies and fundamental rights. Gordon, J-S. (ed.). 1st ed. Leiden, The Netherlands: Brill, Vol. 350. p. 127-153 27 p.
Khan, A., Asim, W., Anwaar Ulhaq., Ghazi, B. & Robinson, R. W., Health assessment of Eucalyptus trees using Siamese network from Google Street and ground truth images. 01 Jun 2021, In: Remote Sensing. 13, 11, p. 1-24 24 p., 2194.
Anwaar Ulhaq, “Deep Learning, Past Present and Future: An Odyssey.” engrXiv. May 7, 2021.doi:10.31224/osf.io/vrmk4
Anwaar Ulhaq, “ On Deep Research Problems in Deep Learning", engrXiv. May 12. 2021.doi:10.31224/osf.io/r78ds.
Anwaar Ulhaq, Jannis Borne, Asim Khan, Douglas Gomes, and Manoranjan Paul, COVID-19 Control by Computer Vision Approaches A Survey.”, IEEE Access, (2020), Impact factor 4.6, SJR Rank Q1
Horry, Michael, Chakraborty S, Paul M, Anwaar Ulhaq, Pradhan B, Saha M, Shukla N. COVID-19 Detection Through Transfer Learning Using Multimodal Imaging Data. IEEE Access,(2020), Impact factor 4.6, 2020 Aug 14;8:149808-24., SJR Rank Q1
Khan, A., Nawaz, U., Anwaar Ulhaq, and Robinson, R.W., Real-time Plant Health Assessment via implementing Cloud-based scalable transfer learning on AWS DeepLens. 2020 arXiv:2009.04110, PLOS ONE 2020, SJR Rank Q1.
Anwaar Ulhaq et al., Active Contours with Local and Global Energy Based-on Fuzzy Clustering and Maximum a Posterior Probability for Retinal Vessel Detection, Concurrency and Computation: Practice and Experience,(2020), Impact factor 1.72, SJRRANK: Q2
Anwaar Ulhaq, ”The role of information fusion in transfer learning of obscure human activities during night”, ISIF Journal of Advances in Information Fusion,(2020), Impact factor 1.38, SJRRANK: Q2
Kirsten Wahlstrom, Anwaar Ulhaq, Oliver Burmeister, ”Privacy by design: a Holochain exploration” Australasian Journal of Information Systems,(2020)„ Impact factor 1.0, SJR RANK: Q2
Jenni Greig, Anwaar Ulhaq , Greg Dresser , Oliver K. Burmeister , Sabih-Ur Rehman, Intelligent Monitoring of Chronic Illness for the Ageing Rural Population: Opportunities and Cautions, HCC14: Human Choice and Computers Conference, Faculty of Global Informatics (iTL), Japan 2020.
Anwaar Ulhaq, Mike Horry, Ammar Haider and Oliver Burmeister, COVID-19 Imaging Data Privacy by Federated Learning Design: A Theoretical Framework. arXiv preprint arXiv:2010.06177, 8th Conference of the Australasian Institute of Computer Ethics, AiCE 2020, Adelaide, Australia.
Oliver Burmeister, Paul d’Aoust, Anwaar Ulhaq and Kirsten Wahlstrom, Holochain and Privacy. 8th Conference of the Australasian Institute of Computer Ethics, AiCE 2020, Adelaide, Australia.
Douglas Pinto, Anwaar Ulhaq, Manoranjan Paul, Michael J. Horry, Subrata Chakraborty, Manas Saha, Tanmoy Debnath, D.M. Motiur Rahaman, Potential Features of ICU Admission in X-ray Images of COVID-19 Patient 2020,arXiv arXiv:2009.12597.
Douglas P. S. Gomes, Michael J. Horry, Anwaar Ulhaq, Manoranjan Paul, Subrata Chakraborty, Manash Saha, Tanmoy Debnath, D.M. Motiur Rahaman, MAVIDH Score: A Corona Severity Scoring using Interpretable Chest X-Ray Pathology Features.”, arXiv:2011.14983.
Douglas Gomes, Cagil Ozansoy, Anwaar Ulhaq. Vegetation High-Impedance Faults’ High-Frequency Signatures via Sparse Coding. IEEE Transactions on Instrumentation & Measurement, DOI: 10.1109/TIM.2019.2950822, (2019), Impact Factor 2.79,SJR RANK: Q1
Douglas Gomes, Cagil Ozansoy, Anwaar Ulhaq, José Carlosde Melo Vieira Júniorc, The effectiveness of different sampling rates in vegetation high-impedance fault classification, Electric Power Systems Research, Volume 174, (2019), Impact Factor 2.85, SJR RANK: Q1
Adam Poulsen, Anwaar Ulhaq, A Post Publication Review of ”Emerging Insights of Health Informatics Research: A Literature Analysis for Outlining New Themes”, Australasian Journal of Information Systems,(2019), Impact factor 1.0, SJR RANK: Q2
Anwaar Ul-Haq et al.” Automated Face Detection, Recognition and Gender Estimation Applied to Person Identification.” Journal of Computer Science, (2019): 395-415.
Anwaar Ulhaq, Kirsten Wahlstrom and Oliver K. Burmeister, Privacy and the Blockchain, 8th Conference of the Australasian Institute of Computer Ethics 2019.
Asim Khan, Anwaar Ulhaq and Randall Robinson, Multi-temporal Registration of Environmental Imagery using Affine Invariant Convolutional Features, The 9th Pacific-Rim Symposium on Image and Video Technology, Sydney, Australia, 2019
Anwaar Ulhaq, Asim Khan and Randall Robinson, Evaluating Faster-RCNN and YOLOv3 for Multi-sensor Imaging Data, Applied Statistics and Policy Analysis Conference, 2019.
Anwaar Ulhaq, Can Data Fusion increase the Performance of Action Detection and Recognition in the Dark? Applied Statistics and Policy Analysis Conference, 2019.
Asim Khan, Anwaar Ulhaq and Randall Robinson, Semantic Vegetation Detection in Repeat Photography for Environmental Data Analysis, Applied Statistics, and Policy Analysis Conference, 2019 BEST PAPER AWARD.
Jenni Greig, SabihUr Rehman, Anwaar Ulhaq, Greg Dresser and Oliver K. Burmeister, Transforming Ageing in Community: addressing global aging vulnerabilities through smart communities, In proceedings of the 9th International Conference on C&T Transforming Communities, 2019.
R. Singh, Anwaar Ulhaq, A Framework for Early Detection of Antisocial Behavior on Twitter Using Natural Language Processing, (Accepted) Complex, Intelligent, and Software Intensive Systems, Springer Nature, (2019)
Anwaar Ulhaq, Xiaoxia Yin, Jing He, and Yanchun Zhang, On Space-time filtering framework for matching human actions across multiple viewpoints, IEEE Transactions on Image Processing, 27(3):1230-1242,(2018), Impact Factor 6.79, SJR RANK: Q1
Douglas Gomes, Cagil Ozansoy, Anwaar Ulhaq, High-Sensitivity Vegetation High Impedance Fault Detection based on Signal’s High-Frequency Contents, IEEE Transactions on Power Delivery, TPWRD-00795-2018,(2018), Impact factor 4.42. SIR RANK: Q1
Md Rafiqul Islam, Arshad Kabir, Ashir Ahmad, Abu Rehan, Anwaar Ulhaq and Hua Wang Depression detection from social network data using machine learning techniques, Springer Health Information Science and Systems,(2018), 6:8, Impact Factor 4.5, SJR RANK: Q1
Md Rafiqul Islam, Xiaoxia Yina, Anwaar Ulhaq, Yanchun Zhang, Hua Wang, Tomas Kron, A comprehensive survey of graph-based complex brain network analysis using functional and diffusion MRI, The American Journal of Applied Sciences, Volume 14, Issue 12,(2018), Impact factor 0.52.
Anwaar Ulhaq, Action Recognition in The Dark via Deep Multi-view Learning, international conference on Image Processing Applications and System, Inria Sophia Antipolis, France,2018.
Anwaar Ulhaq, Deep Cross-view Convolutional Features for View-invariant Action Recognition, international conference on Image Processing Applications and System, Inria Sophia Antipolis, France, 2018.
Islam, MR, Yin, X, Ul-Haq, A, Zhang, Y, Wang, H, Anjum, N & Kron, T 2017, ‘A survey of graph-based complex brain network analysis using functional and diffusional MRI’ American Journal of Applied Sciences, vol. 14, no. 12, pp. 1186-1208. https://doi.org/10.3844/ajassp.2017.1186.1208.
Anwaar Ulhaq, Jing He and Yanchun Zhang, Deep Actionlet proposals for driver’s behaviour monitoring, IEEE Image and Vision Computing New Zealand, Christchurch, New Zealand, 2017.
Douglas Pinto Gomes, Cagil Ozansoy, Anwaar Ulhaq, High-Frequency Spectral Analysis of High Impedance Vegetation Faults on a Three-wire System, IEEE Australasian Universities Power Engineering Conference, November 2017, Melbourne, Australia.
Ul-Haq, A, Yin, X, Zhang, Y & Gondal, I, Action-02MCF: A robust space-time correlation filter for action recognition in clutter and adverse lighting conditions. in J Blanc-Talon, C Distante, W Philips, D Popescu & P Scheunders (eds), Advanced Concepts for Intelligent Vision Systems. vol. 10016, Lecture Notes in Computer Science, no. 10016, Springer, Champagne, Il., pp. 465-476, 2016. https://doi.org/10.1007/978-3-319-48680-2_41.
Ul-Haq, A, Yin, X, He, J & Zhang, Y, ‘FACE: Fully Automated Context Enhancement for night-time video sequences’ Journal of Visual Communication and Image Representation, vol. 40, no. B, pp. 682-693, 2016. https://doi.org/10.1016/j.jvcir.2016.08.008.
Ul-Haq, A, Gondal, I & Murshed, M, ‘On temporal order invariance for view-invariant action recognition’ IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 2, pp. 203-211, 2013.
Ul-Haq, A, ‘Visual cues for view-invariant action recognition’, Doctor of Philosophy Thesis, Monash University, Australia, 203.
Ul-Haq, A, Gondal, I & Murshed, M , On dynamic scene geometry for view-invariant action matching: CVPR 2011. In CVPR 2011. IEEE, Colorado Springs, CO., pp. 3305-3312, 2011. https://doi.org/10.1109/CVPR.2011.5995690
Ul-Haq, A, Contextual Action Recognition in Night-time video sequences. in The International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011.
Anwaar Ulhaq, I. Gondal and M. Murshed, Action recognition using spatio-temporal distance classifier correlation filters, In Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA), Noosa Resort, 2011.
Ul-Haq, A, A novel color image fusion QoS measure for multi-sensor night vision applications. in A novel color image fusion QoS measure for multi-sensor night vision applications: In Proc. IEEE International Symposium on Comput. And Comm. (ISCC). IEEE 2010.
Ul-Haq, A, Automated multi-sensor color video fusion for night-time video surveillance. in Automated multi-sensor color video fusion for night-time video surveillance: In Proc. IEEE International Symposium on Comput. and Comm (ISCC), . IEEE, 2010.
Ul-Haq, A, SCARF: semi-automatic colorization and reliable image fusion. in SCARF: semi-automatic colorization and reliable image fusion: In Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2010.
Ul-Haq, A, VSAM: video stabilization for multiple sensors: In Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA), . in VSAM: video stabilization for multiple sensors: In Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2010.
Anwaar Ulhaq, I. Gondal and M. Murshed, SCENT: a system for colour exploitation at night-time, In Proc. ARCHER, Melbourne, 2010 [CSIRO OVERALL BEST PAPER AWARD].
Malik, M, Gillani, MA & Ul-Haq, A , ‘Adaptive image fusion scheme based on Contourlet Transform and Machine Learning’ International Review on Computers and Software, vol. 3, no. 1, 2008.
Ul-Haq, A, Wavelet-Based Exposure Fusion: In Proc. World Congress on Engineering . in Wavelet-Based Exposure Fusion: In Proc. World Congress on Engineering, July 2 - 4, 2008, London, U.K, 2008.
Ul-Haq, A , Adaptive Image Fusion Scheme Based on Contourlet Transform, Kernel PCA and Support Vector Machine: In Proc. International Joint Conferences on Computer, Information, and Systems Sciences, Bridgeport, USA, 2007.
Ul-Haq, A, Image Fusion for Effective Night Vision through Contourlet Transform and Kernel Principle Component Analysis, In Proc. WAMUS’06 Proceedings of the 6th WSEAS international conference on wavelet analysis & multi-rate systems, Bucharest, Romania, 2006.
Ul-Haq, A, An optimized image fusion algorithm for night-time surveillance and navigation: In Proc. IEEE International Conference on Emerging Technologies ., Islamabad, Pakistan, 2005.
Ul-Haq, A , A novel image fusion algorithm based on Kernel PCA, DWT and structural similarity: In Proc. IASTED International Conference on Visualization, Imaging, and Image Processing, Benidorm, SPAIN,2005.
Ul-Haq, A structural similarity-based image fusion algorithm for night vision applications, In Proc. IEEE International Conference on Systems, Signals and Image Processing, pp. 179 – 183, 2005.