Professor Saman Halgamuge

  • Room: Level: 04 Room: E407
  • Building: Mechanical Engineering
  • Campus: Parkville

Research interests

  • Biomedical Engineering (Neural Engineering, Gate analysis, Metabolomics, Metagenomics, Cancer Data Anlytics and Neural Engineering)
  • Data Engineering (Unsupervised Deep Learning and Hardware based data interrogation)
  • Mechatronics (Networked Control and Smart Grids)

Personal webpage


Saman Halgamuge has been appointed as Director/Head, Research School of Engineering at the Australian National University since August 2016.
He remains associated with the Department of Mechanical Engineering at The University of Melbourne in an honorary capacity. 

He is an IEEE Fellow and a member of Australian Research Council (ARC) College of Experts for Engineering, Information and Computing Sciences.  He was the Director of the PhD training centre Melbourne India Postgraduate Program (MIPP) of University of Melbourne and contributed as Associate Dean (2013-15) and Assistant Dean (2008-13) in International Engagement in the School of Engineering. He is also a member of various International advisory committees including Research Advisory Council of University of Technology PETRONAS.
Professor Halgamuge’s research interests are in Data Engineering including Active data gathering sensor systems,  Unsupervised Deep Learning, Big Data Analytics focusing on applications in Mechanical Engineering and Bioengineering. These applications vary from Sensor Networks in Irrigation, Smart Grids, and Sustainable Energy generation to Bioinformatics and Neuro-Engineering.

Since arriving in Australia in 1996, Professor Halgamuge has obtained research grants totalling over $8.3 million. These grants include funds worth $4.3 million from 17 Australian Research Council grants (4 Discovery projects and 8 Linkages) and 2 NHMRC project grant, local and European industry, contracts and grants from other research funding agencies and large scale ARC network and infrastructure grants worth about $4 million. He has completed supervision of 35 PhD students and currently supervises a group of 11 PhD students. He published over 250 research papers including a research book, 5 edited books, 20 book chapters, 90 journal articles, and over 130 refereed conference papers attracting 7300 Google Scholar (h-factor: 34).

He completed several projects/contracts for local and international industry including Robert Bosch Germany, YourGene Bioscience Australia and POSCO South Korea.

Google Scholar profile is at:

Academia profile is at:

Research Gate profile is at:

His fundamental research contributions are in Big Data Analytics with Unsupervised and Near Unsupervised type learning as well as Unsupervised Deep Learning and Bioinspired Optimization.

His applied research contributions in collaboration with industry and other organizations include:

1) Mechatrionics including Sensor Networks
2) Bioinformatics and Computational Biology: Metabolomics, Metagenomics, Cancer Data Analytics and Neural Engineering
3) Sustainable Energy
4) Modelling and Optimization of Smart Grids
5) Business Analytics

Recent keynote presentations:
16th InCoB (Shenzhen, China, 2017), 26th IJCAI: Workshop BAI (Melbourne, 2017), ICOCB 2017, (Jakarta, 2017), ICVARS 2017, (Sydney, 2017), EBDTS (Melbourne, 2016), MERCON (Moratuwa, 2016), ICIT (Melbourne, 2016), 3rd ISCBI (Bali, 2015), 6th CSBio (Bangkok, 2015), 11th ICIUS (Bali, 2015), IMEC (Hong Kong, 2015), ICCCS (IEEE Sponsored) (Greater Noida, 2015), 9th IEEE ICCE (Vancouver, 2014),  IEEE ICIIS (Gwalior, 2014), CENET (Shanghai, 2014), ICAEIE (Galle, 2014), ISCBI (New Delhi, 2013), IEEE ICIAfS (Beijing, 2012) His profile at Australian National University is at

Recent publications

  1. Sun Y, Kirley M, Halgamuge S. A memetic cooperative co-evolution model for large scale continuous optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2017, Vol. 10142 LNAI.
  2. Habibi Khalaj A, Halgamuge S. A Review on efficient thermal management of air- and liquid-cooled data centers: From chip to the cooling system. APPLIED ENERGY. Elsevier. 2017, Vol. 205.
  3. Herath D, Jayasundara D, Ackland D, Saeed I, Tang SL, Halgamuge S. Assessing Species Diversity Using Metavirome Data: Methods and Challenges. Computational and Structural Biotechnology Journal. 2017, Vol. 15.
  4. Abdulla K, De Hoog J, Steer K, Wirth A, Halgamuge S. Multi-resolution Dynamic Programming for the Receding Horizon Control of Energy Storage. IEEE Transactions on Sustainable Energy. Institute of Electrical and Electronics Engineers. 2017.
  5. Davey N, Dunstall S, Halgamuge S. Optimal road design through ecologically sensitive areas considering animal migration dynamics. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. Pergamon-Elsevier Science. 2017, Vol. 77.
  6. Hameed P, Verspoor C, Kusljic S, Halgamuge S. Positive-Unlabeled Learning for inferring drug interactions based on heterogeneous attributes. BMC BIOINFORMATICS. Biomed Central. 2017, Vol. 18, Issue 1.
  7. Sun Y, Kirley M, Halgamuge S. Quantifying Variable Interactions in Continuous Optimization Problems. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION. IEEE - Institute of Electrical and Electronic Engineers. 2017, Vol. 21, Issue 2.
  8. Premaratne U, Halgamuge S, Mareels I. Traffic Reduction in Packet Switched Networked Control Systems Using Deadband Error Modulation. IEEE TRANSACTIONS ON AUTOMATIC CONTROL. IEEE - Institute of Electrical and Electronic Engineers. 2017, Vol. 62, Issue 8.
  9. Wahid M, Begg R, Lythgo N, Hass CJ, Halgamuge S, Ackland D. A Multiple Regression Approach to Normalization of Spatiotemporal Gait Features. JOURNAL OF APPLIED BIOMECHANICS. Human Kinetics. 2016, Vol. 32, Issue 2.
  10. Wahid M, Begg R, McClelland JA, Webster KE, Halgamuge S, Ackland D. A multiple regression normalization approach to evaluation of gait in total knee arthroplasty patients. CLINICAL BIOMECHANICS. Elsevier Science. 2016, Vol. 32.
  11. Sun Y, Hameed P, Verspoor C, Halgamuge S. A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning. 15th International Conference On Bioinformatics (InCoB) - Systems Biology. Biomed Central. 2016, Vol. 10.
  12. Abdulla K, Steer K, Wirth A, Halgamuge S, De Hoog J. Accounting for Forecast Uncertainty in the Optimized Operation of Energy Storage. 2016 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA). IEEE. 2016.
  13. Habibi Khalaj A, Scherer T, Halgamuge S. Energy, environmental and economical saving potential of data centers with various economizers across Australia. APPLIED ENERGY. Elsevier. 2016, Vol. 183.
  14. Sun Y, Halgamuge S. Fast Algorithms Inspired by Physarum Polycephalum for Node Weighted Steiner Tree Problem with Multiple Terminals. 2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC). IEEE. 2016.
  15. Abdulla K, Steer K, Wirth A, Halgamuge S. Improving the on-line control of energy storage via forecast error metric customization. JOURNAL OF ENERGY STORAGE. Elsevier Science. 2016, Vol. 8.

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile