Professor Saman Halgamuge
- 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)
Saman Halgamuge has moved to Australian National University.
He remains as a honorary Professor in the Department of Mechanical Engineering at The University of Melbourne.
He is an IEEE Fellow and a member of Australian Research Council (ARC) College of Experts for Engineering, Information and Computing Sciences. He is 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. He is also appointed as the VK Samaranayake Endowed Visiting Professor of University of Colombo (2016).
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 a 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 30 PhD students and currently supervises a group of 15 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 6000 Google Scholar (h-factor: 32).
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: http://scholar.google.com.au/citations?user=9cafqywAAAAJ
Academia profile is at: http://unimelb.academia.edu/SamanHalgamuge
Research Gate profile is at: http://www.researchgate.net/profile/Saman_Halgamuge/
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:
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), IAIDIS Conference on Wireless Sensor Networks, (Rome, 2011), Hybrid Intelligent Systems (Malacca, 2011), International Symposium on Green Manufacturing and Applications (ISGMA), (Seoul, 2011), International Conferences on Construction Machinery and Vehicle Engineering (Shanghai, 2011)
- 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.
- 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.
- Hameed PN, 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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. 2016, Vol. 8.
- Abdulla K, Steer K, Wirth A, De Hoog J, Halgamuge S. Integrating Data-Driven Forecasting and Optimization to Improve the Operation of Distributed Energy Storage. 18th IEEE International Conference on High Performance Computing and Communications (HPCC) / 14th IEEE International Conference on Smart City (Smart City) / 2nd IEEE International Conference on Data Science and Systems (DSS). IEEE. 2016. Editors: Chen J, Yang LT.
- Abdulla K, De Hoog J, Muenzel V, Suits F, Steer K, Wirth A, Halgamuge S. Optimal Operation of Energy Storage Systems Considering Forecasts and Battery Degradation. IEEE Transactions on Smart Grid. 2016, Vol. PP, Issue 99.
- Mendis G, Morrisroe E, Petrou S, Halgamuge S. Use of adaptive network burst detection methods for multielectrode array data and the generation of artificial spike patterns for method evaluation. JOURNAL OF NEURAL ENGINEERING. Institute of Physics Publishing. 2016, Vol. 13, Issue 2.
- Mendis G, Morrisroe E, Reid C, Halgamuge S, Petrou S. Use of Local Field Potentials of Dissociated Cultures Grown on Multi-Electrode Arrays for Pharmacological Assays. 2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC). Institute of Electrical and Electronics Engineers. 2016, Vol. 2016-October. Editors: Patton J, Barbieri R, Ji J, Jabbari E, Dokos S, Mukkamala R, Guiraud D, Jovanov E, Dhaher Y, Panescu D, Vangils M, Wheeler B, Dhawan AP.
View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile