Charles Sturt University
Charles Sturt University

Dr Michael Antolovich

Dr Michael Antolovich

BSc PhD

Michael obtained his BSc and PhD from UNSW in 1983 and 1988. He was a Research Associate at Princeton University in 1988/9 and a Research Fellow at the Australian Institute of Nuclear Science and Engineering (AINSE) located at James Cook University from 1989-1991.

He started at CSU in January 1992 on the Wagga Wagga Campus in the School of Science and Technology, was a visiting Professor at the University of California, Davis in Jun-Dec 1995 (SSP), then moved to the Environment Studies Unit (ESU) in Bathurst in 2001. He was Acting Head of the ESU until it was closed down in 2002 and later in that year moved into the School of Information Technology. In 2007 the School merged with Accounting to form the School of Accounting and Computer Science. Michael was a visiting Fellow at the University of NSW from Jan-Jun 2009 (SSP). In July 2009, he moved into the newly formed cross campus School of Computing and Mathematics as Associate Head of School.  He later became Course Director for the BIT, BCompSc, Grad Cert/Dip Maths and Grad Cert Stats. He has had PhD students in various areas of interest including phenolics in olives, games technology, spiking Neural Networks, radar image analysis, robotics, manifolds in computer vision, and analysing EEG signals.  He has also brought in over $2.4M in industry research grants and has published over 70 papers.

Michael began flying in 2005, obtained his Private Pilots Licence in 2007 and began Aerobatics in 2016.  He now regularly participates in State and National Aerobatic Competitions.

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Teaching Responsibilities

  • ITC262 Operating Systems
  • ITC560 Internet of Things

Administrative Responsibilities

Course Director for the:

  • Bachelor of Information Technology (BIT)
  • Bachelor of Computer Science (BCompSc)
  • Graduate Certificate / Diploma of Mathematics
  • Graduate Certificate of Statistics
  • Diploma of Information Technology

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Research

Research Focus
  • Current research interests involve robotics, sensor networks, visualisation, and computational modelling.
Research Project Supervision
  • Coordination Chemistry
  • Macrocyclic Chemistry
  • Porphyrin Chemistry
  • Analytical Chemistry
  • Antioxidant Chemistry
  • Environmental Chemistry
  • Radiopharmaceuticals
  • Single Crystal X-ray Crystallography
  • Single Crystal Neutron Crystallography
  • Molecular Modelling
  • Environmental Modelling
  • Computer Simulations
  • 3D Visualisation
  • Networking
  • Wireless Networks
  • Embedded Systems
  • Sensor Networks
  • Robotics
Current Research Students
  • James Bekkema (PhD)
  • Rohan McAdam (PhD)
  • David Car (PhD)
  • Dwaine Bailey (PhD)

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Professional Activities

  • Practicing Computer Professional (PCP)

Grants

  • Development of an efficient ventilation system for grain silos (Aussie-Grains $62,000 (2018-2019): Looking at silo venting to improve grain storage conditions by reducing temperature and humidity conditions inside grain silos.
  • Adjunct at UTS (2015-2018): Worked within the School of Computing and Communications at the University of Technology, Sydney. Projects include Computer Vision Systems based on the Deep Learning and Virtual Reality Video Camera systems.
  • Drawbell Boulder Detection (MMT3, University of Queensland US$634,000 (2014-2016)): Team Leader for research group. Extending work from Newcrest Project to detect boulders higher up the draw bell.

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Selected Publications

  1. Islam, MR; Paul, M; Antolovich, M (2019) Rain Streak Removal with Well-Recovered Moving Objects from Video Sequences Using Photometric Correlation Pacific-Rim Symposium on Image and Video Technology, 3-13
  2. Wang, P; He, Z; Xie, K; Gao, J; Antolovich, M; Tan, B (2019) A hybrid algorithm for low-rank approximation of nonnegative matrix factorization Neurocomputing 364, 129-137
  3. Islam, MR; Paul, M; Antolovich, M; Kabir A (2019) Sports Highlights Generation using Decomposed Audio Information 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 579-584
  4. Ali, M; Gao, J; Antolovich, M (2019) Parametric Classification of Bingham Distributions Based on Grassmann Manifolds IEEE Transactions on Image Processing 28(12), 5771-5784
  5. Ju, F; Sun, Y; Gao, J; Antolovich, M; Dong, J; Yin, B (2019) Tensorizing restricted Boltzmann machine ACM Transactions on Knowledge Discovery from Data (TKDD) 13(3), 1-16
  6. Wang, P; He, Z; Xie, K; Gao, J; Antolovich, M (2017) A Nonnegative Projection Based Algorithm for Low-Rank Nonnegative Matrix Approximation. In: Liu D., Xie S., Li Y., Zhao D., El-Alfy ES. (eds) Neural Information Processing. ICONIP. Lecture Notes in Computer Science10634, Springer, Cham
  7. Ali, M; Antolovich, M (2016) Classification on Grassmann Manifold via Scheiddegger-Watson Distribution using Bayesian Approach 3rd International Conference on Soft Computing & Machine Intelligence (ISCMI) 28-32
  8. Ali, M; Gao, J; Antolovich, M (2016) MLE-Based Learning on Grassmann Manifolds Digital Image Computing: Techniques and Applications (DICTA) 1-7
  9. Ali, M; Antolovich, M (2016) Learning on Fisher-Bingham Model Based on Normalizing Constant 3rd International Conference on Soft Computing & Machine Intelligence (ISCMI) Dubai 33-37
  10. Ali, M; Antolovich, M (2016) Recognition on Matrix Angular Central Gaussian Distribution 3rd International Conference on Soft Computing & Machine Intelligence (ISCMI) Dubai, 38-42
  11. Ali, M; Antolovich, M; Wang, B (2016) Recognition on Grassmann manifolds via parametric modelling 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Datong 2014-2019
  12. Ali, M; Antolovich, M; Wang, B (2016) Density estimation on Stiefel manifolds using matrix-Fisher model 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Datong 66-71
  13. Ali, M; Gao, J; Antolovich, M (2016) Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions, International Joint Conference on Neural Networks (IJCNN) 3751-3757
  14. Benter, A; Moore, W; Antolovich, M (2016) GPR signal attenuation through fragmented rock Mining Technology 1-7
  15. Ge, F; Moore, W; Antolovich, M (2015) Learning from Demonstration Using GMM, CHMM and DHMM: A Comparison AI 2015: Advances in Artificial Intelligence, 204-217
  16. Parvez, MZ; Paul, M; Antolovich, M (2015) Detection of Pre-stage of Epileptic Seizure by Exploiting Temporal Correlation of EMD Decomposed EEG Signals Journal of Medical and Bioengineering 4(2) 110-116

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