Taste of Research Summer Scholarships

2025 Projects - School of Civil and Environmental Engineering

Civil & Environmental Engineering Projects

Project Title:	Development and application of machine learning and digital twins to water and wastewater treatment
Name of Supervisor:	David Waite
Email of Supervisor:	d.waite@unsw.edu.au
Name of Joint/Co-Supervisor:	Lina Yao, Yuan Yang
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Water and Wastewater Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	In this project, digital twins (incorporating both machine learning and deterministic models) of selected water and wastewater treatment technologies will be developed and applied for the purposes of optimising design and performance of these technologies.
Research Environment:	The candidate will work with a team of engineers and research students skilled in water and wastewater treatment and will draw on strengths in machine learning and digital twins from colleagues in computer science, CSIRO and Art & Design.
Novelty and Contribution:	.
Expected Outcomes:	The appointed ToR student will assist in development of digital twins incorporating both machine learning-based algorithms and deterministic models to optimise design and performance of selected water and wastewater treatment technologies.
Reference Material Links:	"https://doi.org/10.1016/j.watres.2022.119349, opens in a new window https://doi.org/10.1016/j.desal.2021.115482, opens in a new window"
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Development and pilot-scale testing of water desalination using Capacitive Deionisation (CDI) techno
Name of Supervisor:	David Waite
Email of Supervisor:	d.waite@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Water and Wastewater Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	A critical need exists for development of low cost, low maintenance technologies for the removal of salt and other contaminants from waters that are to be used for domestic, agricultural and industrial purposes. Interest in the use of the electrochemical technology of capacitive deionisation (CDI) for this purpose has increased dramatically in recent years with the Waite group at UNSW active in both laboratory and pilot-scale investigations of these technologies.
Research Environment:	The Waite Group is made up of higher degree research students, post-doctoral research associates and process engineers with team members located at both UNSW Sydney and at the UNSW Centre for Transformational Environmental Technologies (CTET) at Yixing in Jiangsu Province, China. This team undertakes strategic and applied research at both laboratory and pilot-scale with, in many instances, close engagement with industry partners. Studies range from development and manufacture of improved electrodes, optimisation of the CDI process using machine learning based approaches and development and use of renewable energy to power the water treatment technology.
Novelty and Contribution:	.
Expected Outcomes:	The ToR student will contribute to research activities at either (or both) laboratory and pilot scale of CDI-related desalination technologies with expected outcomes including co-authorship of peer-reviewed publications in high impact international journals, patents of new technologies and/or industry reports.
Reference Material Links:	"A variety of CDI-related outputs by the Waite Group over the last year or so is provided at the links below: https://doi.org/10.1021/acs.est.3c03477, opens in a new window https://doi.org/10.1016/j.desal.2023.116647, opens in a new window https://doi.org/10.1016/j.watres.2022.119349, opens in a new window https://doi.org/10.1016/j.watres.2023.120273, opens in a new window https://doi.org/10.1016/j.desal.2021.115482, opens in a new window https://forms.unsw.edu.au/system/files/webform/eng_advertise_a_phd_project/47972/MCDI%20brochure.pdf, opens in a new window"
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Development of innovative advanced oxidation and reduction processes for contaminant degradation and
Name of Supervisor:	David Waite
Email of Supervisor:	d.waite@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Water and Wastewater Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Professor Waite and his team are involved in a range of research activities focussed on use of oxidation and reduction technologies for both the degradation of contaminants and the recovery of resources including nutrients and high value elements that are present in wastewaters. Research activities involve both studies to improve understanding of the mechanism underpinning the technology as well as approaches to optimising the process when used at full scale.In this project, we will develop a simple yet robust synthetic strategy to chemically coat a thin layer of porous polymer on hydrogel surface that is similar as the human skin. The pores in the polymer film are exactly functioning as those in the human skin to breathe and modulate water evaporation of hydrogel by controlling their sizes. These polymer coatings will address the great challenge of uses of polymer hydrogels in multi-environment by mimicking human skin and will widen the applications of hydrogels in our real world.
Research Environment:	The Waite Group is made up of research students, Research Associates and process engineers at both UNSW Sydney and at the UNSW Centre for Transformational Environmental Technologies in Yixing, Jiangsu Province in China. This research team undertake studies at both laboratory scale but also interact with industry partners in investigations at pilot and full-scale. The research team undertake both experimental and computational studies and apply the results of these studies to the development and application of innovative treatment and resource recovery technologies.
Novelty and Contribution:	.
Expected Outcomes:	The ToR student will contribute to the collection of experimental and/or computational results that will form the basis of research output that will be published either in high quality, peer-reviewed international journals or in commercial-in-confidence reports to industry partners.
Reference Material Links:	Examples of publications arising from research by the Waite group in the area of advanced oxidation and reduction processes are provided below: https://doi.org/10.1021/acsestengg.2c00356, opens in a new window https://doi.org/10.1021/acs.iecr.3c00020, opens in a new window https://doi.org/10.1007/s10311-023-01561-x, opens in a new window https://doi.org/10.1021/acsestengg.2c00278, opens in a new window https://doi.org/10.1021/acs.est.2c06033, opens in a new window https://forms.unsw.edu.au/system/files/webform/eng_advertise_a_phd_project/47960/AOP%20Technologies.pdf, opens in a new window
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Lifting fish across a barrier with a Tube Fishway
Name of Supervisor:	Stefan Felder
Email of Supervisor:	s.felder@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr Jasmin Martino
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Water and Wastewater Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Instream barriers such as weirs and dams have contributed to the decline in fish populations worldwide. The UNSW Tube Fishway, developed by a cross-disciplinary team of hydraulic engineers and fish biologists, cyclically attracts and lifts fish with an unsteady surge across barriers. The Tube Fishway has been successfully tested at the UNSW Water Research Laboratory (WRL) and in short-term field trials in Australia. Using the lessons learnt from these field trials, this TOR project aims to advance the design of the attraction chamber of the fishway to provide a refuge for fish prior to being lifted. Specifically, the operation of a modified attraction chamber will be tested to ensure efficient and safe operation for fish by quantifying delivered surge velocity and volume, that will be used as input for numerical modelling. Weather permitting, the student may also become involved in a Tube Fishway field test.
Research Environment:	This research project will take place at the UNSW Water Research Laboratory (WRL) in Manly Vale. WRL is a vibrant part of the School of Civil and Environmental Engineering and home to the largest and most comprehensive hydraulics laboratories in Australia. WRL is a specialist fundamental and applied research organisation, focusing on issues related to water. For more than 60 years WRL has tackled complex challenges in areas of coastal, environmental and eco-engineering, hydrology, water resources, hydraulics and groundwater... More info on Faculty Taste of Research website (https://www.unsw.edu.au/engineering/student-life/undergraduate-research-opportunities/advertised-taste-research-areas)
Novelty and Contribution:	.
Expected Outcomes:	Attraction chamber with refuge zone to improve attraction of fish whilst maintaining safe lifting. Guidelines for efficient attracting and lifting of fish. Guidance for future field testing and validation data for numerical modelling.
Reference Material Links:	https://www.unsw.edu.au/research/wrl/our-research/tube-fishway-project, opens in a new window Relevant selected publications: Cox RX; Kingsford RT; Suthers I; Felder S, 2023, 'Fish Injury from Movements across Hydraulic Structures: A Review', Water (Switzerland), 15, http://dx.doi.org/10.3390/w15101888, opens in a new window Farzadkhoo M; Kingsford RT; Suthers IM; Felder S, 2023, 'Flow hydrodynamics drive effective fish attraction behaviour into slotted fishway entrances', Journal of Hydrodynamics, 35, pp. 782 - 802, http://dx.doi.org/10.1007/s42241-023-0047-6 , opens in a new window Peirson WL; Harris JH; Suthers IM; Farzadkhoo M; Kingsford RT; Felder S, 2022, 'Impacts on fish transported in tube fishways', Journal of Hydro-Environment Research, vol. 42, pp. 1 - 11, http://dx.doi.org/10.1016/j.jher.2022.03.001, opens in a new window
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Metamaterials for Sensing in Structural Health Monitoring
Name of Supervisor:	Mehri Makki Alamdari
Email of Supervisor:	m.makkialamdari@unsw.edu.au
Name of Joint/Co-Supervisor:	Shaghik Atakaramians
Email of Joint/Co-Supervisor:	s.atakaramians@unsw.edu.au
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Structural Engineering, Structures
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Metamaterials are engineered materials with unique properties that are not typically found in nature, making them highly effective for sensing applications. These materials derive their extraordinary capabilities from their precisely structured geometries, rather than their composition. In the context of sensing, metamaterials can be designed to interact with electromagnetic waves in ways that amplify or detect small changes in their environment, such as pressure, temperature, or strain. This makes them ideal for structural health monitoring, where they can provide real-time, remote insights into the integrity of infrastructure or materials by detecting subtle shifts in mechanical properties. By embedding metamaterial-based sensors within structures, it's possible to track strain, deformation, or damage with high sensitivity, offering a more efficient and scalable approach to maintaining safety in large-scale systems like bridges, buildings, and aircraft.
Research Environment:	This research will be conducted in collaboration with the School of Civil and Environmental Engineering, as well as the School of Electrical Engineering and Telecommunications at UNSW. The student will begin with an extensive literature review on the use of metamaterials in sensing, followed by detailed numerical investigations using the COMSOL environment to characterize the sensing performance of the designed metasurfaces.
Novelty and Contribution:	.
Expected Outcomes:	The expected outcomes of using metamaterials for sensing include enhanced sensitivity and precision in detecting environmental changes, such as strain, pressure, or temperature, in real time. By leveraging the unique electromagnetic properties of metamaterials, sensors can detect even minor structural deformations or material defects with high accuracy. This could lead to significant advancements in structural health monitoring systems, offering more reliable and efficient ways to assess the integrity of critical infrastructure like bridges, buildings, and aircraft. Additionally, metamaterial-based sensors are expected to be compact, scalable, and capable of operating in a wide range of environmental conditions, further expanding their potential applications in various industries.
Reference Material Links:	.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Multi-physics simulations of novel porous structures
Name of Supervisor:	Daniel Chen
Email of Supervisor:	daniel.chen7@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Advanced Materials
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Porous structures made of foams, lattices, and honeycombs are gaining traction in various industrial sectors, and are featured with light weight, high specific stiffness, good energy absorption, and novel thermal, electrical, biological, acoustic characteristics. They give unique flexibility in performance-tailoring and possess great potential in the multi-functional applications across structural, mechanical, material, biomedical, and aerospace engineering. Highlighted by non-uniform cellular geometries, functionally graded porous structures are an important extension of the existing porous structural forms and potentially provide enhanced properties. This study aims to investigate the multi-physics properties of novel porous structures by using numerical simulations, with a focus on the interactions between porous geometries and fluids (air or water). The findings will offer valuable insights into their applications across diverse fields, including energy-efficient buildings, floating platforms, biomedical implants, and more.
Research Environment:	Numerical simulations; Smart composite materials; Multi-physics analysis; Porous structures
Novelty and Contribution:	.
Expected Outcomes:	High-performing computation workstations, numerical simulation software, and sufficient research guidance will be provided.
Reference Material Links:	https://www.sciencedirect.com/science/article/pii/S0263823123005244
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Physics Informed Neural Network for Indirect Structural Health Monitoring
Name of Supervisor:	Mehri Makki Alamdari
Email of Supervisor:	m.makkialamdari@unsw.edu.au
Name of Joint/Co-Supervisor:	Elena Atroshchenko
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Structural Engineering, Structures
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Physics-Informed Neural Networks (PINNs) are an emerging approach in structural health monitoring (SHM), combining machine learning with the principles of physics to provide accurate and efficient models for assessing structural integrity. Unlike traditional data-driven neural networks, PINNs integrate governing physical laws, such as partial differential equations (PDEs), directly into the training process. This allows the network to make predictions that are not only guided by the available data but also constrained by the underlying physics of the system. For SHM, PINNs can be used to model complex structural behaviors, detect anomalies, and predict damage with reduced reliance on extensive sensor data. By embedding physics into the neural network, they provide a robust framework for real-time monitoring of infrastructure, improving prediction accuracy and generalization, while ensuring that the solutions remain physically meaningful. The advantages of using Physics-Informed Neural Networks (PINNs) for Structural Health Monitoring (SHM) are significant. First, PINNs incorporate the fundamental physical laws governing structural behavior, directly into the learning process. This reduces the need for large amounts of training data, as the model is guided by known physics rather than solely relying on empirical data. Second, PINNs provide more accurate and reliable predictions, as they ensure that the solutions adhere to real-world physical constraints, minimizing the risk of unrealistic or non-physical results. ... More info on Faculty Taste of Research website (https://www.unsw.edu.au/engineering/student-life/undergraduate-research-opportunities/advertised-taste-research-areas)
Research Environment:	This research will be conducted in the School of Civil and Environmental Engineering at UNSW. The student will begin with an extensive literature review, followed by extensive numerical investigations
Novelty and Contribution:	.
Expected Outcomes:	The expected outcomes of using Physics-Informed Neural Networks (PINNs) in Structural Health Monitoring (SHM) are substantial improvements in the accuracy, efficiency, and robustness of structural assessments. By embedding physical laws directly into the neural network, PINNs can provide more reliable predictions even with limited or noisy sensor data. This leads to more precise identification of structural anomalies in real-time, enhancing the safety and longevity of infrastructure such as bridges, buildings, and aircraft.
Reference Material Links:	n/a
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Safe fish transport across hydraulic structures
Name of Supervisor:	Stefan Felder
Email of Supervisor:	s.felder@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr Jasmin Martino
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Water and Wastewater Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Hydraulic structures in rivers and waterways, such as dams and weirs provide important functions to society including flood mitigation, drinking and irrigation water supply and hydropower. The safety of the structure is paramount even under the most extreme conditions, while hydraulic structures should consider sustainability. Safety considerations for fish are often secondary in design and are often opposed to the most efficient hydraulic design. Fish can get injured by impeller blades of turbines, by rapid pressure changes at sluice gate or during transport along the spillway or in the downstream energy dissipator. Research at the UNSW Water Research Laboratory (WRL) is combining the expertise of hydraulic engineers and fish biologists to design hydraulic structures that operate efficiently without injuring fish. This research project will focus on fish transport along a spillway and the downstream hydraulic jump stilling basin to better understand the hydraulic stressors that cause fish injuries, and which hydraulic conditions can be considered safe for fish.
Research Environment:	This research project will take place at the UNSW Water Research Laboratory (WRL) in Manly Vale. WRL is a vibrant part of the School of Civil and Environmental Engineering and home to the largest and most comprehensive hydraulics laboratories in Australia. WRL is a specialist fundamental and applied research organisation, focusing on issues related to water. For more than 60 years WRL has tackled complex challenges in areas of coastal, environmental and eco-engineering, hydrology, water resources, hydraulics and groundwater... More info on Faculty Taste of Research website (https://www.unsw.edu.au/engineering/student-life/undergraduate-research-opportunities/advertised-taste-research-areas)
Novelty and Contribution:	.
Expected Outcomes:	This project aims to achieve the following outcomes: Better understanding of fish transport in high-speed flows and hydraulic jumps. Identify hydrodynamic thresholds to prevent fish injury. Guidelines for safe fish transport in spillways and energy dissipators.
Reference Material Links:	This project aims to achieve the following outcomes: Better understanding of fish transport in high-speed flows and hydraulic jumps. Identify hydrodynamic thresholds to prevent fish injury. Guidelines for safe fish transport in spillways and energy dissipators.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Transport Data Driven Analytics for Big Telematics Data
Name of Supervisor:	Elnaz Irannezhad
Email of Supervisor:	e.irannezhad@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Are you interested in applying data analytics and machine learning to real-world transport challenges? We are seeking motivated students to join an exciting research project on Transport Data-Driven Analytics for Big Telematics Data. Using four years of longitudinal telematics data from heavy vehicles across Australia and New Zealand, this project will apply supervised and unsupervised machine learning techniques to: (i) identify trip ends and segment heavy vehicle trips; (ii) infer the type of stops and categorize activity stops in a tour; and (iii) provide insights into freight transport tour trip patterns and major activity points. Why Join? - Work with large-scale transport datasets and cutting-edge machine learning techniques. - Gain valuable experience in transport data analytics, telematics, and freight transport research. - Contribute to research with real-world industry and policy implications.
Research Environment:	This research will be undertaken jointly at the Research Centre for Integrated Transport Innovations (rCITI) and our telematic industry partner, Euclidic Systems at their CBD Office. rCITI is housed in the School of Civil and Environmental Engineering at UNSW Sydney. rCITI was established in 2011 as a strategic initiative to consolidate and expand the diverse landscape of transport research across the university. rCITI has continued to make remarkable strides since its inception. rCITI aims to reshape the field of multi-modal transport engineering and planning by introducing new innovative techniques and technologies, which enhance society, by integrating across methodological disciplines and contextual considerations.
Novelty and Contribution:	.
Expected Outcomes:	More info on Faculty Taste of Research website (https://www.unsw.edu.au/engineering/student-life/undergraduate-research-opportunities/advertised-taste-research-areas)
Reference Material Links:	https://www.euclidic.com/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Vehicle Optimisation for Drive-by-Bridge Inspection
Name of Supervisor:	Mehri Makki Alamdari
Email of Supervisor:	m.makkialamdari@unsw.edu.au
Name of Joint/Co-Supervisor:	Elena Atroshchenko
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Structural Engineering, Structures
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	Drive-by bridge inspection is an innovative technique that uses vehicles equipped with sensors to assess the structural condition of bridges as they pass over them. Unlike traditional bridge inspection methods, which often require lane closures, scaffolding, or specialized equipment, this approach allows for continuous monitoring without disrupting traffic flow. The vehicles—often regular cars, trucks, or specialized inspection vehicles—are fitted with accelerometers, GPS, and other sensors that record vibrations and dynamic responses as the vehicle crosses the bridge. These data are then analyzed to detect changes in the bridge's dynamic behavior, such as stiffness variations or frequency shifts, which can indicate structural damage or degradation. This method offers several advantages, including the ability to inspect multiple bridges quickly and cost-effectively. It also enables real-time or frequent monitoring, making it easier to track the progression of structural issues and prioritize maintenance. Although drive-by inspections may not yet replace traditional methods for detailed assessments, they provide a valuable, scalable tool for early damage detection and routine health monitoring of bridge networks. The performance of indirect SHM or drive by bridge inspection highly depends on the characteristics of the sensing vehicle. This project aims to gain knowledge on the best-performing vehicle to maximise the amount of bridge-related information from the vehicle-bridge interaction system.
Research Environment:	This research will be conducted in the School of Civil and Environmental Engineering at UNSW. The student will begin with an extensive literature review, followed by extensive numerical investigations and experimental testing.
Novelty and Contribution:	.
Expected Outcomes:	By optimizing the vehicle design and sensor placement, inspections can achieve higher levels of data quality and reliability. Specifically, optimized vehicles can enhance the collection of dynamic response data, allowing for more precise identification of structural anomalies and potential defects in bridges. Ultimately, these advancements can facilitate proactive maintenance strategies, extend the lifespan of bridge infrastructure, and enhance overall public safety by ensuring timely detection and response to structural issues.
Reference Material Links:	n/a
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Water Infrastructure in the Solomon Islands
Name of Supervisor:	Bojan Tamburic
Email of Supervisor:	b.tamburic@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Civil and Environmental Engineering
Faculty Research Area (Theme):	Water and Wastewater Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Term 2
Abstract:	This project aims to document, map and analyse recent WASH (water, sanitation and hygiene) infrastructure projects in the Solomon Islands. By assessing these initiatives, we seek to compare their effectiveness, impact and sustainability. The insights gained from this research will help identify best practices, highlight challenges, and inform strategies for improving future WASH interventions. Ultimately, this study will contribute to building a stronger foundation for evidence-based decision-making and the development of more efficient and impactful WASH programs in the Solomon Islands.
Research Environment:	Part of the Pacific Water Security ChallENG project, where students work on real-world WASH challenges and design sustainable solutions that empower disadvantaged communities and improve lives.
Novelty and Contribution:	.
Expected Outcomes:	1. Interactive map of WASH infrastructure projects in the Solomon Islands 2. Infographic to compare effectiveness, impact and sustainability of WASH projects
Reference Material Links:	https://www.unsw.edu.au/challeng/student-projects/explore-student-projects/Pacific-Water-Security
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No