Dr. Fang Chen has an outstanding track record in innovation. In the past 20 years, she has created many world-class solutions while working at organizations like the Beijing Jiaotong University, Intel, Motorola and NICTA. She leads many taskforces with the goal of using data analytics with national and international scale and impact. She has led the work with TMC for the past ten years, from decision support for incident management, to incident prediction through social media, as well as incident clearance duration prediction. She also has a long history of working with RMS. Dr. Chen leads Data61's team of Advanced Data Analytics in Transport, which won the ITS Australia National Research Award in 2014. She has more than 160 refereed publications and has filed more than 30 patents in multiple countries. She also holds conjoint professorship with the University of New South Wales.
Dr. Cai is the leader of the Advanced Data Analytics in Transport (ADAIT) group at Data61|CSIRO, and the manager of Data61’s business in ITS. Data61 is Australia’s leading data innovation group which currently partners with 29 universities in Australia and more than 90 corporate and 30 government structures in order to create Australia’s data-driven future. Its ADAIT group is an international front runner in applying state-of-the-art artificial intelligence, machine learning and cloud computing in the ITS industry. Dr. Cai co-founded the group in 2013 and led it to win the ITS Australia National Award on Research in 2014 and 2015 consecutively. The group won the prestigious NSW Premier’s Innovation Initiative in 2015 to deliver predictive modelling capabilities for congestion management in Sydney. The group became a core partner in the TfNSW initiative for On-Demand Public Transport in 2017, with responsibilities on predictive data modelling.
Research & Development
Dr. Adriana Simona MIHAITA has joined the Advanced Data Analytics in Transport as a Researcher in September 2015. She obtained her PhD from the University of Grenoble, France, in 2012 and continued to work as a teaching assistant and researcher in the ERPI laboratory from Nancy, France on problems related to the mesoscopic traffic simulation and traffic plan optimization inside ecological neighborhoods. Her current research focuses on large-scale traffic simulations using machine learning techniques to assist traffic planners and traffic engineers to evaluate the impact of their modifications in the entire urban traffic system in Sydney.
Ben Itzstein has worked as a research and software engineer within Human-Computer Interaction and Machine Learning projects at NICTA since 2009. His past work includes multi-device remote collaboration, aggregated real-time sensor data visualization, multi-modal psychometric monitoring and testing, road traffic visualization, and data-driven decision support solutions for control rooms. He holds a Bachelor of Engineering in Mechatronics and a Bachelor of Advanced Science in Physics and Computer Science, from the University of Sydney.
Dr. Hoang Nguyen is a Research Engineer / Data Scientist at the ITL and Machine Learning Research Group at ATP lab, Data61. In 2013, he completed his PhD on data mining research at the University of Sydney and started to work for NICTA since July-2013. His research interests include machine learning, active learning and natural languages processing. He was product owner of Traffic Watch, a project with NSW Transport Management Centre to detect incidents reported by social media. Hoang also contributed to most major projects of Advanced Data Analytics in Transport team at Data61.
Dr. Kieu has been a researcher at ADAIT from October 2016. He holds a Master Degree from Linkoping University, Sweden and a PhD in Transportation Engineering from Queensland University of Technology, Australia. His expertise lies in the use of Big Data in Public Transport, Behavioural Modelling and Traffic Simulation. He is currently exploring a machine learning approach to behavioural modelling, and a smart interface to online large scale traffic simulation.
Tuo Mao is a PhD candidate in University of New South Wales (UNSW), a research assistant at the Analytics Research Group at Data61. His PhD research focuses on Highway Traffic Signal Control and Management including transit signal priority (TSP), coordinated ramp metering (CRM), route guidance and variable speed limit (VSL). He took part in RMS Roads Report system project and implemented innovative CRM in PARAMICS.
Weihong Wang received Ph.D. degree in the area of machine learning at the University of New South Wales, Sydney, Australia in 2016. He received M.E. degree in computer science from the University of New South Wales in 2006, and B.S. degree in computer science from the University of Sun Yat-Sen in 2003. His research interests include image processing, pattern recognition, machine learning and deep learning. The projects he took part in include Sydney CBD Mobility Modelling project and RMS Roads Report system project
Dr. Yuming is a Data Scientist in the Analytics Research Group at DATA61. He obtained his PhD in Computer Science from University of Technology Sydney in 2010. He is passionate about developing scalable computing platforms driven by Big Data Analytics to discover deep insights from large and diverse data sets. Before joining Data61, he has successfully completed seven data analytics projects for well-known organisations in banking, insurance, IT, education and government sectors. Now he is focusing on transport data analytics and building a transport data analytic platform for urban transport management.
Zelin Li is a research engineer working in Data61 Analytics Research group and pursuing his Ph.D in the University of New South Wales. His researches focus on machine learning, intelligent network, computer vision and pattern recognition. His expertise lies in large-scale system development and project management. He has been involved in the projects of water pipes failure prediction for 23 water utilities throughout the world.