Prof. Raja Jurdak is a Senior Principal Research Scientist at CSIRO, where he leads the Distributed Sensing Systems Group. He has a PhD in Information and Computer Science at University of California, Irvine in 2005, an MS in Computer Networks and Distributed Computing from the Electrical and Computer Engineering Department at UCI (2001), and a BE in Computer and Communications Engineering from the American University of Beirut (2000). His current research interests focus on energy-efficiency and mobility in networks. Prof. Jurdak and his group have led several large scale and long-term sensing projects on sensing remote and challenging environments, in agriculture, ecology, health, manufacturing, and energy. Most recently, he has led the large Batmon project for continental scale tracking of flying foxes, delivering near-perpetual tracking of small assets. His research at CSIRO has received multiple awards, including the CSIRO medal for environmental achievement and the Endeavour Executive Award in 2011, the Queensland iAwards Merit Award in 2014, and the best paper award at the EWSN conference in 2016.
Prof Jurdak has over 120 peer-reviewed journal and conference publications, as well as a book published by Springer in 2007 titled Wireless Ad Hoc and Sensor Networks: A Cross-Layer Design Perspective. He serves on the editorial board of 3 international journals and on the Review Board of IEEE Pervasive Computing. He regularly serves on the organising and technical program committees of international conferences (DCOSS, Mobiquitous, RTSS, Sensapp, Percom, EWSN, ICDCS). Prof Jurdak is an Honorary Professor the Unversity of Queensland, and an Adjunct Professor at University of New South Wales, Macquarie University and James Cook University. He has spent time as a visiting scientist at MIT in 2011 and at University of Oxford in 2017. He is a Senior Member of the IEEE.
Dr. Brano Kusy is a principal research scientist in CSIRO and the leader of the Pervasive Computing team. He has a PhD degree in Computer Science from Vanderbilt University, Nashville, USA and an MS degree in Computer Science from Comenius University, Bratislava, Slovakia. His PhD work was on embedded wireless sensor systems, applied in various application scenarios, including acoustic sniper localization and low-power wireless localization and tracking. His main research focus was on system services that enable time and space coordination in embedded distributed systems.
Dr. Kusy worked as a postdoc with Prof. Leo Guibas in the Computer Science department at Stanford University between 2007 and 2009. His research was on low-latency delivery of sensor data to mobile users, discovery and utilization of mobility patterns in urban environments, and information discovery and brokerage in WSNs.
He moved to the Autonomous Systems Lab in Brisbane, Australia in 2009 where he currently works as a research scientist in Data61. His research interests include systems topics in distributed systems, such as reliable wireless communication, delay tolerance in sparsely connected networks, and coordination of time and space of individual sensor nodes. He has applied wireless sensing technology to efficient behavior- and energy-aware sensing of airborne animals (National Flying Fox Monitoring program); high-granularity sensing of occupancy, activity, and user comfort in commercial buildings (Advanced HVAC Control project); and spatio-temporal analysis of environmental and soil parameters in mined areas (ACARP Mine-Rehabilitation project). He is currently leading an activity that seeks to develop novel solutions to the Great Barrier Reef monitoring, focusing on the boundary between novel materials and autonomous systems.
Chris Sharman is a team leader and senior engineer with over a decade experience in developing environmental monitoring and decision support platforms. Working across several domains including marine monitoring, agriculture and aquaculture. Chris has most recently focused on building innovative platform solutions for real-time environmental observations with embedded analytics for decision support applications. Chris has experience leading delivery projects with a client and impact focus whilst working closely with specialist domain expertise. Previous projects have included innovative real-time sensing platforms, soil mapping and sampling systems, low-cost marine sensing systems, robotic sensing platforms and cloud based sensor data management with embedded analytics.
Philip Valencia is Senior Research Engineer with over a decade experience in developing low power wireless sensor network technologies for real-time tracking and measurement of physiological and behavioural characteristics of animals. Based in the Autonomous Systems program at the CSIRO, he has focussed predominately on agricultural applications which can benefit from the unprecedented spatiotemporal sensing that can be delivered by Wireless Sensor Networks (WSN). Through this research, Philip has been involved in Virtual Fencing, environmental sensing of the farm, gas concentration measurement within the rumen of cattle and sheep, location and behavioural monitoring and classification of behavioural states of various animals.
Philip has 3 patents, authored 4 book chapters, 50+ publications with more than 1100 citations and a H-index of 15. His vision is to embed machine learning capabilities into the highly constrained devices used for WSNs to facilitate intelligent pervasive sensing and decision making. As a result this will enable the autonomous management of complex systems, that previously required significant human involvement.
Peter is a senior software engineer and international leader in hydrological data exchange systems. He is the lead author of WaterML2.0 part 1 (time-series) and part 2 (ratings and gaugings), which are now both adopted international standards for data exchange. He chaired the WaterML2.0 Standards Working Group, a collaboration involving many large environmental organisations, including the US Geological Survey, the US National Oceanic & Atmospheric Administration, and the Australian Bureau of Meteorology.
Peter has led a range of projects using real-time sensor data and models to inform environmental decision-making. Before working at CSIRO Peter worked for KISTERS and Hydro Tasmania, where he consulted international firms in environmental monitoring and modelling. He is an active member of the Open Geospatial Consortium.
Dr Arkady Zaslavsky is a Senior Principal Research Scientist in Data61. He led and leads a number of national and international initiatives in the Internet of Things science area. Main research interests include the Internet of Things (IoT), IoT-enabled context- and situation-awareness, prediction and validation, IoT middleware platforms, mobile analytics
John is a research engineer currently working in CSIRO’s Data61 business. He has a robotics background and has previously developed and commissioned autonomous catamarans and submarines. For the last few years John has been managing CSIRO projects in the marine and pond aquaculture space. Currently John is leading a project developing situational awareness and decision support systems for mollusc aquaculture. Under this project CSIRO has developed and deployed a data management and visualisation system for the Tasmanian Shellfish Quality Assurance Program (TSQAP). This system ingests data from several different organisations, including some CSIRO developed environmental monitoring nodes and provides information relevant to public health in the context of each of the State’s shellfish growing zones. This information is used by TSQAP to assist their closure decision making.
More widely, the team John works closely with, have been developing mollusc and salmon bio-sensors. The current generation of salmon biosensors are archival, and the current mollusc sensors are real-time. CSIRO’s telemetry units are providing oyster physiology (heart rate & gaping) as well as water quality (temperature, salinity, DO, depth, chlorophyll) in real-time from farms in southern Tasmania.
Joe Pasanen is a Senior Software Engineer with almost 15 years experience in building commercial applications. He has worked as team lead, solution architect, and senior software engineer both locally and abroad for international clients. His time in the UK saw him help develop an airline booking system, lead the front end development of an online interactive ad for Intel’s Ultrabook, and build a portal for Germany’s national culture and science which included an interactive kids game. Returning home he worked for Hydro Tasmania developing their wholesale energy spot trading platform and led the redevelopment of Momentum Energy’s key retail assets. Having worked closely with CSIRO during 2016 while in partnership with Sense-T, he has now joined the team full time to continue his work on developing an IoT platform, analysis services, and various supporting systems.
Reza’s current research interest are in hyperspectral/image processing, statistical machine learning and deep neural networks. His previous research has mostly been around adaptive and distributed signal processing.
He has BSc and MSc degrees both in electrical engineering and a PhD degree in telecommunications engineering received from the University of South Australia in 2013. Before joining CSIRO in 2015, he worked as a research fellow at the University of South Australia.
Dr Khalifa is currently a researcher at Data61|CSIRO, Australia and a casual academic staff at School of Computer Science and Engineering (CSE), University of New South Wales (UNSW), Sydney, Australia. Her current research interests include smart wearables, Internet of Things, energy harvesting, pattern recognition, human activity recognition and indoor positioning. She is a Technical Program Committee Member in the Work in Progress Session (IEEE PerCom, 2016) and IEEE Workshop on Internet of Things 2016 (WIoT 2016).
She received a postdoctoral writing fellowship from NICTA (Dec 2015-Mar 2016) and worked as a research assistant (Sep 2015-Nov 2015) at CSE, UNSW. She received many awards including”2016 NASSCOM Highly Commended Award” and “2015 Canon Information Systems Research Australia (CISRA) Best Research Paper Award at UNSW”. She has authored more than 10 papers in the area of pervasive computing and pattern recognition. She has been a reviewer of a number of conference papers and journals.
She completed a PhD in Computer Science and Engineering from UNSW in February 2016. She obtained MSc and BSc in Computer Science from Zagazig University, Egypt in 2011 and 2007, respectively. She has secured First Class with Distinction throughout her studies. She was a Lecturer Assistant in the Faculty of Computers and Informatics, Zagazig University, Egypt from September 2007- January 2012. During this period, Sara taught various Computer Science subjects and worked as a co-Supervisor for several undergraduate student projects. Read More
Dr Jessica Liebig is a Postdoctoral Research Fellow at Data61, CSIRO. She is part of the Distributed Sensing Systems Group, that is led by Professor Raja Jurdak, where she works on the spread of vector-borne diseases in Australia.
Jessica received her PhD in January 2017 from RMIT University where she worked under the supervision of Professors Asha Rao and Kathy Horadam in the area of network science. The work presented in her thesis was directed towards the study of large complex bipartite networks with the aim to uncover significant behaviour in real world networks.
Dr. Yiran Shen is a postdoctoral research fellow at Data 61, CSIRO. He obtained his PhD degree from University of New South Wales under the supervision of Prof. Chun Tung Chou and Dr. Wen Hu. His research interests include realtime machine learning on embedded systems, IoTs security, mobile/wearable computing. He published regularly on top conferences like SenSys, IPSN, Ubicomp, Percom and top journals like IEEE TMC, IEEE TDSC, Computer Networks.
Dr. Frank De Hoog is a Post-retirement Fellow at CSIRO. Dr de Hoog is recognized internationally as having made highly original and insightful contributions to the advancement of applied, computational and industrial mathematics, and has contributed substantially to the mathematics profession. He is the recipient of the 2017 Hannan Medal. The importance and significance of his theoretical and applied contributions, and their flow‐on contributions to the advancement of science and to improving the efficiency of industrial processes, have been recognised by various awards. The impact of his industrial research has been exceptional in terms of the speed of implementation by industry and the subsequent contributions to Australia’s export economy.
Mac Coombe is a Mechatronics Engineer with a focus on real-time acquisition and processing of environmental sensor data. Since joining the CSIRO in 2011, he has been involved in a diverse range of projects, including projects in e-health, environmental sensing, geophysical sensor systems, and machine learning in oceanography. His current work involves development of middleware systems for real-time ingestion, processing, storage and visualisation of time-series sensor data, and on development of machine-learning systems for identifying and visualising features of interest in time-series and gridded data. This work provides a platform for realising a vision of cheap, simple and ubiquitous environmental data accessibility for individuals, businesses and governments.
David Biggins is a Software Engineer with a background in electronic engineering. Davids most recent work with CSIRO has been working with the mining industry to develop a UAV platform for mapping inaccessible areas in underground mines using UAVs as a robotic platform and photogrammetry. The maps created consist of 3D textured point clouds and will result in more profitable and safer mining by giving mine planners information they have not had access to in the past. David is a member of the CSIRO Data61, Cyber Physical Systems research program and is located at Sandy Bay, Tasmania.
I am an electronics engineer with almost ten years experience of contributing my skills to CSIRO’s research projects across various scientific domains. My work typically involves the electronics design, firmware/software development, integration, testing, production, and ultimately deployment of autonomous systems. These have included terrestrial and marine wireless sensor networks, standalone remote telemetry units, miniaturised data-loggers, and marine robotic platforms. These systems have helped our scientists and industrial partners to enhance Australia’s terrestrial agriculture, salmon and shellfish aquaculture, and coastal water monitoring practices. I have also contributed to embedded operating systems, and components of CSIRO’s SensorCloud middleware.
Jace started working at CSIRO during 2015 as an undergraduate, where he worked and also completed his thesis around low power indoor localisation on Android phones using Bluetooth. Jace has recently been working on the VPDaD (Vertebrate Pest Detect and Deter) project where he has mainly been responsible for the server back end, mobile phone application and infrastructure for long range communication and configuration of remote nodes.
Lachlan is an Embedded engineer with over 2 years of experience with embedded systems development, PCB, and CAD design. Lachlan graduated with a Bachelor of Electronic and Computer Systems Engineering and a BSc in Physics from Griffith University. Lachlan is currently working on developing the next generation wireless sensor network hardware platform with long-range communications, applied to wildlife tracking and agricultural projects. Lachlan previously worked with the State Library to designing Printed Circuit boards and Embedded Software, and delivering workshops teaching basic science and electronics skills.
John is an embedded engineer working in conjunction with Ceres Tag to create a smart ear tag for animals. He graduated with first class honours from the University of Queensland in 2017 with Bachelor’s degrees in Electrical Engineering and Physics. Aside from PCB design and embedded programming, John is interested in machine learning, and working with large amounts of data to come to unique conclusions.