
phD (Purdue University)
Professor Alexander Paz is the Transport and Main Roads Chair at the Queensland University of Technology. Before joining QUT, he was an Associate Professor of Civil Engineering and the director of the Transportation Research Center at the University of Nevada. He is a Chartered Professional and a Fellow Engineer in Australia, a Registered Professional Engineer in Queensland, and a Professional Engineer Licensed in the State of Nevada. Professor Paz has a strong background in transport engineering, travel behavior, transport planning, and road safety. He has significant experience developing methods, algorithms and software tools for the management of highway infrastructure, the analysis and evaluation of transport systems, and the deployment of Intelligent Transportation Systems. His work including data warehouses and software applications has been adopted by industry at an international scale. Two of his inventions are presently being used by industry; one presently patented, and the second is under review by the U.S. Patent and Trademark Office. A third invention in the field of traffic safety received a patent from the U.S. Patent and Trademark Office and was licensed for commercialization. Professor Paz received his Ph.D. in Transportation and Infrastructure Systems Engineering from Purdue University. Professor Paz' broad interests include the application of operations research, network modelling, statistics and econometric methods, informatics integrated into modelling, analysis, operations, safety and control of large-scale dynamic transport, and logistic systems. His research has been sponsored by the National Science Foundation, the Federal Highway Administration, the Nevada Office of Traffic Safety, the Regional Transportation Commission of Southern Nevada, the City of Las Vegas, the Nevada Governor's Office of Economic Development, the FACE Foundation, the Nevada Office of Traffic Safety, Verizon, Parsons, the Nevada Department of Transportation, the Queensland Department of Transport and Main Roads, iMOVE CRC, the Brisbane City Council, and the Australian Department of Infrastructure, Transport, Regional Development and Communication.
Research achievements:
Published more than 100 scholarly publications, including a book, book chapters and journal and conference papers. Received more than $17 million in research funding from the public and the corporate sector organizations for undertaking over 60 research projects. Supervised more than 18 doctoral and research Masters students.
Research areas:
- Traffic Safety
- Congestion Management
- Infrastructure Management
- Intelligent Transportation Systems
- Travel Demand
His research entails field investigations, modelling, simulation, statistics, and optimization.
Traffic Safety
- Development of methods and tools for crash data collection including mobile, visualization, GIS and GPS based applications.
- Advanced analytics and new algorithms for crash estimation, network screening, and diagnosis as well as countermeasure selection.
- Development and field testing of emerging and advanced traffic safety devices to alert drivers and minimize risk.
Congestion Management
Development of large-scale dynamic traffic flow models for the study and evaluation of strategies to manage vehicular congestion. Development and implementation of optimization frameworks for the calibration and validation of network models.
Infrastructure Management
Development of software systems for the management and visualization of roadway infrastructure. Advanced analytics for generation of deterioration and network screening models and systems.
Intelligent Transportation Systems
Generation of framework for the deployment of real-time traveler information. Evaluation of Intelligent Transportation Systems (ITS) technologies using network and traffic flow models. Field testing of emerging ITS products.
Travel Demand
Study of travel demand and behavior using statistics and econometric methods. Development of optimization frameworks for model estimation and validation.
Additional information
- Professor and Transport and Main Roads Chair, 2018-Present, Queensland University of Technology, Brisbane, Australia
- Associate Professor, 2014-2018, University of Nevada, Las Vegas, Nevada, USA
- Director, 2013-2018, Transportation Research Center, University of Nevada, Las Vegas, USA
- Assistant Professor, 2008-2014, University of Nevada, Las Vegas, Nevada, USA
- Senior Professional, 2007-2008, Cambridge Systematics, Oakland, California, USA
Industry:
Before becoming a university professor at the University of Nevada, Las Vegas (UNLV), Professor Paz worked for one year as Senior Professional for a major consulting firm, Cambridge Systematics. He worked on multiple projects for clients, including Federal Highway Administration, California Department of Transportation (CalTrans), and local Metropolitan Planning Organizations. Results from this work were used at the operational level to select strategies to deploy intelligent transportation systems throughout the San Francisco metropolitan area. The work was innovative at that time in terms of using and expanding capabilities provided by Dynamic Traffic Assignment to evaluate multiple intelligent transportation system technologies for a real-work traffic system. The evaluation was performed with the final objective of making decisions that would result in integration of multiple traffic systems and modes of transportation.
Academia:
Business Intelligence and Advanced Analytics
Professor Paz' major industry experience is a large Business Intelligence project that involved data warehousing, software development, advanced analytics, dashboard implementation, and training to the sponsor/client. He was the principal investigator (PI) for this $US 2.8 million project, with a share of 80%. Key innovations from this project are listed below, with non-provisional applications for patents filed for the first two innovations:
- A workflow and software system that integrates ESRI ArcMap and Oracle Business Intelligence Enterprise Edition for reporting analytics on interactive maps. Deployed in 2014 and in use since then by the Nevada Department of Transportation.
- A workflow and software system that uses data from the National Bridge Inventory to generate and report color-coded three-dimensional renderings of key bridge elements. Deployed in 2014 and in use since then by the Nevada Department of Transportation.
- A workflow and software system that uses data from the Highway Performance Monitoring System (HPMS) to generate capacity analyses using the Highway Capacity Manual Methodology. The software reports capacities by means of interactive maps, tables, and drilldowns. Deployed in 2016 and in use since then by the Nevada Department of Transportation.
In addition to these key software systems, the project involved designs and deployment of a data warehouse, development and implementation of regression models for financial and traffic systems, and implementation of hundreds of interactive dashboards.
Infrastructure Management
This project involved the design, development, implementation, and testing of a Utility Data Management Software System. This included a geo-spatial database, a web portal for data visualization and management, many feature code libraries for multiple vendors of data collection equipment, and a website for data loading and interaction with external contractors who collect field data. This system was developed and implemented in the first phase of the project with a cost of $US 610,000, and my share was 80%. A second phase of this project involved moving the system into production. The cost of this second phase was $ US 130,000.
Traffic Safety
Professor Paz' most exciting project that is currently underway involves the design, prototyping, and field test of a couple of traffic safety devices, which details are still confidential due to intellectual property restrictions by UNLV. A local startup, Rebel Roadway Systems LLC, licensed the technology from the university, and currently is working on commercializing it. UNLV is completing field testing at a local campus roadway facility. In parallel, we are working on optimizing and improving our design as well as adding capabilities for data collection; we also are about to secure resources for major field testing in Las Vegas.