Dr Aravinda Sridhara Rao
- Computer Vision (Video Analytics)
- Internet of Things
- Machine Learning (Deep Learning)
- Manifold Learning (Nonlinear Dimensionality Reduction)
Dr Aravinda Sridhara Rao is a Postdoctoral Research Fellow since 2016, in the Department of Electrical and Electronic Engineering.
Dr Rao received his B.E. degree in Electronics and Communication from Visvesvaraya Technological University, India, in 2006, the M.E. degree in Electronics and Telecommunications from Deakin University, Australia, in 2010. He received his PhD degree (in Computer Vision) from the Department of Electrical and Electronic Engineering, The University of Melbourne, in 2016.
He is associated with the ARC Research Networks on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) lab.
His PhD focused on developing automated crowd behavior analysis framework for crowded scenarios from networked cameras using unsupervised and semi-supervised learning for providing real-time video surveillance and analytics. The framework was developed considering several cameras across the cities deployed for public safety and surveillance.
He introduced a novel nonlinear dimensionality reduction framework for analyzing large amounts of video data in a manner suitable for real-time video applications and analytics.
His research is applicable to wide-ranging crowd monitoring and video surveillance applications, including crowd density estimation, people counting, people tracking, detecting suspicious individuals and overall crowd behavior. The models introduced are useful to monitor situations at public places, transport hubs, airports, traffic intersections, shopping malls, stadiums, sporting events, etc.
During 2006-2007, he worked as a Deputy Engineer in the Development and Engineering division of Naval Systems at Bharat Electronics Limited, India, focusing on designing and developing embedded systems and high-speed PCB designs for sonar systems.
He is currently working on new Machine Learning (ML) and Deep Learning (DL) techniques for real time applications.
His research interests include Computer Vision, Machine Learning, Deep Learning, and Internet of Things (IoT).
For more information on research activities, visit full academic homepage.
- Rathore P, Sridhara Rao A, Rajasegarar S, Vanz E, Gubbi J, Palaniswami M. Real-time Urban Microclimate Analysis Using Internet of Things. IEEE Internet of Things Journal. 2017.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Palaniswami M, Wong E. A Vision-Based System to Detect Potholes and Uneven Surfaces for Assisting Blind People. 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC). IEEE. 2016.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Palaniswami M. An Improved Approach to Crowd Event Detection by Reducing Data Dimensions. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS). Springer. 2016, Vol. 425. Editors: Thampi SM, Bandyopadhyay S, Krishnan S, Li KC, Mosin S, Ma M.
- Yang M, Rajasegarar S, Sridhara Rao A, Leckie C, Palaniswami M. Anomalous Behavior Detection in Crowded Scenes Using Clustering and Spatio-Temporal Features. 9th IFIP TC 12 International Conference on Intelligent Information Processing (IIP). 2016, Vol. 486. Editors: Shi Z, Vadera S, Li G.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Palaniswami M. Anomalous Crowd Event Analysis Using Isometric Mapping. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS). Springer. 2016, Vol. 425. Editors: Thampi SM, Bandyopadhyay S, Krishnan S, Li KC, Mosin S, Ma M.
- Gubbi Lakshminarasimha J, Kusmakar S, Sridhara Rao A, Yan B, O'Brien T, Palaniswami M. Automatic Detection and Classification of Convulsive Psychogenic Nonepileptic Seizures Using a Wearable Device. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS. IEEE - Institute of Electrical and Electronic Engineers. 2016, Vol. 20, Issue 4.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Marusic S, Palaniswami M. Crowd Event Detection on Optical Flow Manifolds. IEEE TRANSACTIONS ON CYBERNETICS. Institute of Electrical and Electronics Engineers. 2016, Vol. 46, Issue 7.
- Sridhara Rao A, Gubbi J, Ngo T, Mendis P, Palaniswami M. Internet of Things for Structural Health Monitoring. Structural Health Monitoring Technologies and Next-Generation Smart Composite Structures. CRC Press. 2016. Editors: Epaarachchi A, Chanaka Kahandawa G.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Palaniswami M, Wong E. Non-Protruding Hazard Detection for the Aged Vision-Impaired. 2016 IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS). IEEE. 2016, Vol. 2016-September.
- Kusmakar S, Gubbi Lakshminarasimha J, Sridhara Rao A, Yan B, O'Brien T, Palaniswami M. Classification of Convulsive Psychogenic Non-epileptic Seizures Using Histogram of Oriented Motion of Accelerometry Signals. 2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC). Institute of Electrical and Electronics Engineers. 2015, Vol. 2015-November.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Rajasegarar S, Marusic S, Palaniswami M. Detection of anomalous crowd behaviour using hyperspherical clustering. 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014. 2015.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Marusic S, Palaniswami M. Estimation of crowd density by clustering motion cues. VISUAL COMPUTER. Springer. 2015, Vol. 31, Issue 11.
- Sridhara Rao A, Gubbi Lakshminarasimha J, Marusic S, Palaniswami M. Probabilistic detection of crowd events on riemannian manifolds. 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014. 2015.
- Gubbi Lakshminarasimha J, Marusic S, Sridhara Rao A, Law Y, Palaniswami M. A pilot study of urban noise monitoring architecture using wireless sensor networks. 2nd International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE Explore. 2013.
- Gubbi Lakshminarasimha J, Kumar D, Sridhara Rao A, Yan B, Palaniswami M. A Pilot Study on the Use of Accelerometer Sensors for Monitoring Post Acute Stroke Patients. 35th Annual International Conference of the IEEE EMBS. IEEE Explore. 2013.
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Electrical and Electronic Engineering, Parkville
University of Melbourne
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