Dr Haowen Xu
Postdoctoral Fellow
Ph.D., Civil Engineering
2015 - 2019
The University of Iowa, Iowa City, IA
Cumulative GPA: 3.90/4.00
Dissertation Title: “Data-Driven Framework for Forecasting Sedimentation at Culverts”
Focus Area: Hydroinformatics and Environmental Informatics
Passed the final thesis defense (on December 5th, 2018)
- Received multiple travel grants and research fellowship from NSF, UCGIS, and CGRER
- UI SETP (the University of Iowa Student Employee of the Year) Nominee
Graduate Certificate in Geoinformatics,
2014 to 2016
The University of Iowa, Iowa City, IA
Cumulative GPA: 3.94/4.00
MS, Civil and Environmental Engineering
2013 - 2015
The University of Iowa, Iowa City, IA
Cumulative GPA: 4.00/4.00
Dissertation Title: “Prototype Hydroinformatics-based System for Supporting Decision Making in Culvert Design and Monitoring”
- Received a Full-tuition Scholarship
B.S.E., Civil Engineering
2009 to 2013
The University of Iowa, Iowa City, IA
Cumulative G.P.A.: 3.54/4.00; Dean’s List
Thesis Title: “Search Engine for Iowa Watershed Data Information System”
- Graduated with Honors in Civil Engineering
Arts, Design & Architecture (ADA)
School of Built Environment
Dr. Haowen Xu
Research Fellow | School of Built Environment | UNSW Sydney
Dr. Haowen Xu is an internationally experienced computational scientist and engineering researcher, currently serving as a Research Fellow (Level B) in the School of Built Environment at the University of New South Wales (UNSW Sydney), Australia. Prior to joining UNSW, he spent approximately six years as a Research Scientist at Oak Ridge National Laboratory (ORNL), a U.S. Department of Energy (DOE) national laboratory, and held an appointment as an Adjunct Associate Professor in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville (UTK). He maintains an active international research network and ongoing collaborations with researchers at U.S. national laboratories, government-funded research institutions, and universities.
Dr. Xu received his PhD from the University of Iowa, USA, where he also completed his bachelor's and master's degrees, and holds a Graduate Certificate in Informatics. His interdisciplinary research spans computational engineering, intelligent transportation systems, connected and autonomous vehicles, high-performance scientific computing, artificial intelligence, digital twins, cyber-physical systems, and large-scale simulation and optimization. His work focuses on developing advanced computational technologies and AI-enabled decision-support systems for intelligent infrastructure, transportation, and urban resilience.
An IEEE Senior Member and ACM member, Dr. Xu has authored more than 30 peer-reviewed journal articles and over 30 conference papers, technical reports, and book chapters. His publications have attracted over 1,680 citations, with an h-index of 21 on Google Scholar. His recent research achievements include a paper receiving in-principle acceptance at Nature Communications and recognition as a finalist for the prestigious R&D 100 Awards, which recognise significant technological innovations worldwide. He is also an inventor on multiple U.S. patents related to intelligent transportation, smart cities, and infrastructure technologies.
Throughout his research career, Dr. Xu has served as a Technical Lead and Co-Principal Investigator on multiple competitively funded U.S. federal research projects, including projects supported by the U.S. Department of Energy and ARPA-E. His contributions have been recognised through numerous international research and innovation awards, including Best Paper, Best Research, and Best Poster Awards from IEEE, IBPSA, CIE, and AWRA, as well as recognition through the ORNL Significant Event Award.
As an Australian permanent resident, Dr. Xu relocated from the United States to Australia in 2025, bringing extensive experience from U.S. federal research laboratories and academia to contribute to Australia's research, innovation, and engineering sectors. Building on his international research experience and established collaborations with U.S. government laboratories and universities, he is committed to advancing Australia's capabilities in artificial intelligence, high-performance scientific computing, computational engineering, and intelligent infrastructure. His research aims to bridge fundamental computational innovation with practical engineering applications, fostering international research collaboration and supporting the development of more intelligent, efficient, and resilient infrastructure and urban systems in Australia and beyond.
Further information about Dr. Xu’s academic background, research contributions, teaching experience, and scholarly activities, together with selected examples of his work, is available through his academic website:
- Academic Profile & Publications: https://haowenxu-phd.github.io/homepage/
- Interactive Teaching & Learning Resources: https://haowenxu-phd.github.io/homepage/learning
- Selected Research Projects & Demonstrations: https://haowenxu-phd.github.io/homepage/portfolio
- Student Mentoring & Research Co-supervision: https://haowenxu-phd.github.io/homepage/teaching
- Research Funding & Competitive Grants: https://haowenxu-phd.github.io/homepage/grants
- Google Scholar: https://scholar.google.com/citations?user=WdKOUGcAAAAJ&hl=en
E-mail
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
Title: A Cognitive Freight Transportation Digital Twin for Resiliency and Emission Control Through Optimizing Intermodal Logistics (RECOIL) Role: Co-Principal Investigator (Co-PI) Duration: Fiscal Year 2023-Present Project URL: https://recoil.utk.edu/ URL: https://arpa-e.energy.gov/technologies/exploratory-topics/intermodal-freight
Title: ML-Assisted Atmospheric Hazard Modeling for Effective Geospatial Risk Analysis Role: Co-Investigator Duration: Fiscal Year 2023-Present
Title: Scaling up the Realtime Data, Simulation and Artificial Intelligence (AI) and Control for Optimizing Regional Mobility Role: Task Lead for developing Digital Twins Duration: Fiscal Year 2021-2023 URL: https://www.energy.gov/eere/vehicles/articles/regional-mobility-chattanooga
Title: Forecasting and Mitigation of Sedimentation at Culverts Role: Co-Investigator Duration: 01/2015-12/2015 |
2024 | Best Research Paper Award from the 51st International Conference on Computers & Industrial Engineering (CIE51), UNSW, Australia |
2022 | Best Poster Award from the 19th IEEE International Conference on Mobile Ad-hoc and Smart Systems (MASS) |
2022 | Award for the Most Creative Demonstration from IBPSA HackSimBuild 2022 competition in conjunction with Building Performance Analysis Conference and SimBuild 2022 |
2021 | Invited presenter at the 1st GeoScale Workshop |
2020 | Significant Event Award (SEA) – ORNL, USDOE Release of Real-time Ctwin v1.1 -- The Chattanooga Digital Twin for Mobility/Transportation |
2018 | Wayne L. Paulson Scholarship Award (1000 USD) |
2018 | Graduate College Post-Comprehensive Research Fellowship (9000 USD) |
2017 | UCGIS & NSF Travel Awards (2000 USD) |
2017 | CGRER Travel Award (600 USD) |
2017 | UI SETP (the University of Iowa Student Employee of the Year) Nominee |
2016 | Invited presenter at the United States Environmental Protection Agency (USEPA) headquarters |
2016 | Best Student Oral Presentation Award from the American Water Resources Association (AWRA) |
2015 | CGRER Travel Award (750 USD) |
2013 | Study Abroad International Student Merit-based Scholarship |
2013 | Segal Family Foundation Scholarship |
2013 | The University of Iowa Engineering College Merit-based Scholarship
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His research focuses on the development and application of Generative AI, Agentic AI, Digital Twins, Scientific Computing, High-Performance Computing, Geospatial AI, and Physics-Informed Voxel Simulation for urban, environmental, transportation, and infrastructure systems. His work aims to bridge artificial intelligence, computational modelling, operations resaerch and decision support systems to address complex challenges in smart cities, environmental sustainability, infrastructure resilience, and emergency management.