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 a senior researcher of the Analytics Research Group at Data61. He obtained his PhD on computational transportation science from University College London in 2010. His expertise lies in transport modelling and machine learning techniques. He was project leader on Sydney CBD Mobility Modelling, RMS Roads Report system, and Sydney M4 Smart Motorway evaluation. He is currently the deputy leader of the Advanced Data Analytics in Transport team at Data61. He is also a conjoint senior lecturer at UNSW.
Research & Development
Dr. Menon is a researcher in the Machine Learning Research Group at Data61. He obtained his PhD in machine learning from the University of California, San Diego in 2013. His expertise lies in the design and analysis of machine learning techniques for weakly supervised learning problems. Within the CBD Mobility Modelling and M4 Smart Motorway Evaluation projects, he invented techniques for statistical estimation of origin-destination flows. He is currently exploring machine learning techniques for reliably estimating travel times
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.
Tao obtained his bachelor's degree from TongJi University and his master's degree and Ph.D degree from the University of New South Wales. His expertise lies in transport network modelling, traffic demand forecasting and traffic assignment. He is currently focusing on large-scale transport simulation and application of machine learning in transport. Tao was involved in the CBD Mobility Modelling project and KRPR project at NICTA. He is now a research engineer working on various transport project in Data61, CSIRO.
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
Yang Zhang is a Software Engineer in the Analytics Research Group. He obtained Master Degree in Computer Science from UNSW 2013. Since then, he worked as a Software Engineer in different organisations. He is a full stack software developer with experience in both front end and backend systems. His interest is in delivering solid software solutions utilising DevOps methodologies.
Young is a researcher in the Analytics Research Group at DATA61. He completed his doctoral studies from the London School of Economics. Prior to joining Data61, he worked in the finance industry in London. Young's research interest broadly lies in the applications of stochastic processes in machine learning problems. Some specific areas include: bayesian nonparametric methods for statistical machine learning, equivalence of measure changes and duality in linear programming, and submartingale sequences and their applications in deep learning.
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.