Taste of Research Summer Scholarships

2027 Projects - School of Computer Science and Engineering

Computer Science & Engineering Research Areas

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Computer Science & Engineering Projects

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Project Title:	Agentic AI for Assessment in Experiential Learning Environments
Name of Supervisor:	Dr. Basem Suleiman
Email of Supervisor:	b.suleiman@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr. May Lim, Dr Khalegh Barati
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	This project investigates the development of an AI system for assessment within experiential, project-based learning environments. The system will leverage modern AI architectures to support learning activities and tasks and assess them. Emphasis will be placed on modelling core computing knowledge, and evaluation beyond traditional assessments. Key research challenges include designing reliable evaluation mechanisms, ensuring fairness and consistency, and supporting meaningful human–AI interaction. The outcomes aim to advance scalable, AI-driven assessment frameworks applicable to education and other experiential learning contexts.
Research Environment:	Interns will work closely with academic supervisors and research staff, with access to environment that support open research, regular technical discussions, and engagement with ongoing projects in modern AI frameworks and it's application. Interns will also gain hands-on experience in designing, implementing, and evaluating advanced AI systems, while contributing to research outcomes with potential for publication in leading venues.
Novelty and Contribution:	.
Expected Outcomes:	Working prototype of an agentic AI system Research report including review of existing work, method, evaluation of proposed solution Source code and technical documentation
Reference Material Links:	To be discussed with selected interns.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Automated Oral Assessments at Scale for Safeguarding Academic Integrity
Name of Supervisor:	Dr Rachid Hamadi
Email of Supervisor:	r.hamadi@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Generative AI has made it increasingly difficult for conventional programming assignments to establish whether submitted code reflects a student’s own understanding. The proposed project addresses this challenge through assessment redesign rather than AI detection. It will extend an existing prototype that automatically conducts structured oral assessments based on each student’s submitted program, asking them to explain, justify, and reason about their own implementation decisions. The current system ingests programming submissions, generates personalised questions tied to each student’s code, collects spoken or written responses, and provides provisional evaluation against a transparent two-dimensional rubric: correctness (factual and technical accuracy of the response) and understanding (depth of reasoning, justification of design choices, and ability to explain consequences or alternatives).
Research Environment:	1. Research at the intersection of Artificial Intelligence, Education, and Academic Integrity. 2. Develop and evaluate an AI-powered oral assessment prototype using conversational AI and speech technologies. 3. Gain experience in machine learning, natural language processing, and educational technology. 4. Conduct user testing and data analysis to assess effectiveness and usability.
Novelty and Contribution:	.
Expected Outcomes:	1. A working prototype 2. A peer-reviewed conference paper 3. Pilot study involving one large-enrolment course 4. Evidence of improved assessment authenticity and integrity 5. A roadmap for institution-wide deployment
Reference Material Links:	1. R. Hamadi and M. O’Dea, "WIP: Automated Oral Assessments at Scale for Safeguarding Academic Integrity", IEEE Frontiers in Education Conference, 2026. 2. S. Kannam, Y. Yang, A. Dharm, and K. Lin, "Code interviews: Design and evaluation of a more authentic assessment for introductory programming assignments", Proceedings of the 56th ACM Technical Symposium on Computer Science Education, 2025, pp. 554-560. https://doi.org/10.1145/3641554.3701806
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Automated Testing and Verification of Neural Networks and LLMs
Name of Supervisor:	Yulei Sui
Email of Supervisor:	ysui@cse.unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Deep learning models are now used in many important applications, including transport, finance, supply chains, communications, and space systems. However, these models can behave unpredictably when their inputs change slightly, which raises concerns about whether they can be trusted in safety- or security-critical settings. This project will investigate practical techniques for testing and verifying the robustness of neural networks. Robustness means that small changes to an input should not cause unexpected or significantly different outputs. The project will explore how fuzz testing, abstract interpretation, and optimisation-based verification can be used to find incorrect behaviours, generate counterexamples, and provide stronger guarantees about model behaviour. The work will build on ACT (https://github.com/SVF-tools/ACT), an open-source framework for neural network analysis developed by the SVF research team. Depending on the student's interests, the project may involve implementing new analysis techniques, extending ACT to support additional neural network layers or properties, designing new fuzzing strategies, or evaluating existing methods on standard neural network benchmarks. This project is suitable for students interested in software analysis, machine learning, testing, or formal verification. It provides an opportunity to work with a research prototype, conduct experiments, and contribute to an active open-source research project.
Research Environment:	Based on the open-source tool: https://github.com/SVF-tools/ACT
Novelty and Contribution:	.
Expected Outcomes:	Analyzing and verifying modern AI models
Reference Material Links:	https://github.com/SVF-tools/ACT
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Defence-to-Civilian Language Translation using LLMs
Name of Supervisor:	Dr. Aditya Joshi
Email of Supervisor:	aditya.joshi@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr. Bao Doan
Email of Joint/Co-Supervisor:	bao.doan1@unsw.edu.au
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	This project explores how defence-specific terminology and phrasing can be translated into civilian, academic, or general English and vice versa. The goal is to build a bidirectional natural language translation layer that bridges domain-specific language used by defence and national security personnel with general-purpose language models and user interfaces. The outcome will support improved interoperability and accessibility of AI systems within defence and national security contexts. The expected activities will involve collecting and aligning paired examples of defence and civilian terminology, developing an approach to fine-tune or prompt-tune existing large language models, and evaluating translation accuracy and contextual fidelity. This work sits within a broader collaboration between UNSW and Cyndr on AI capability intelligence, funded by Defence Trailblazer. The translation layer will contribute to Cyndr’s ontology transformer concept, which seeks to interpret user intent across different technical and cultural domains (e.g. military, research, industry). Australian citizens and permanent residents will be given preference due to project context. This project suits candidates with strong, hands-on technical skills in pre-training and post-training language models, along with good foundation in natural language processing.
Research Environment:	The project will be supervised by Dr Aditya Joshi and Dr. Bao Doan with collaboration from Cyndr. The student will be embedded within the natural language processing research group in the School of Computer Science and Engineering. Weekly progress meetings and monthly group meetings will provide ongoing peer feedback.
Novelty and Contribution:	.
Expected Outcomes:	Expected Outcomes: - Develop a prototype model capable of translating between defence and civilian language. - Create a structured dataset of parallel terminology. - Produce a technical report or paper summarising the model’s performance and potential applications within defence AI systems.
Reference Material Links:	https://arxiv.org/abs/2606.06942 https://arxiv.org/html/2604.17943v1
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Deployable firewall based on seL4
Name of Supervisor:	Courtney Darville
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Peter Chubb
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	The TS group has just developed a proof-of-concept of a secure network firewall running on the verified seL4 microkernel and LionsOS. Currently the firewall supports the transmission of traffic between two network interfaces, and is able to apply simple filtering rules to a subset of IP traffic (TCP, UDP, ICMP). Filtering rules and forwarding routes may be viewed and updated through a rudimentary web interface. Presently it has a number of missing features that prevent its practical use, with each feature requiring a varying degree of work to implement. While we are happy to leave most of them to the open-source community, we are looking for interns for the higher priority ones. These are: * Support for IPv6, as well as more IP protocols and ethernet types * A collection of optimised, concurrency-safe data structures which can be used by firewall components for reading and updating shared network state (e.g. NAT port mappings, TCP connection) If there is sufficient time left after the above, the rest can be spent on improvements to existing features or adding further functionality, with the ultimate aim of enabling the firewall to be deployed on the TS network.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. functional firewall that can be deployed 2. report describing design and implementation.
Reference Material Links:	https://sel4.systems/ https://trustworthy.systems/projects/LionsOS/ https://lionsos.org/docs/examples/firewall/contributing/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Design and Development of an Agentic AI System for Education
Name of Supervisor:	Dr. Basem Suleiman
Email of Supervisor:	b.suleiman@unsw.edu.au
Name of Joint/Co-Supervisor:	Prof. Fethi Rabhi
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	This project focuses on the design, development, and evaluation of an agentic AI system to enhance teaching and learning in higher education. The system is intended to support both students and academics by providing intelligent academic advising, personalized learning support, and assistance with a range of teaching and learning activities. The project investigates the application of agentic AI principles, leveraging existing large language models, AI frameworks, and orchestration tools to develop an autonomous, context-aware learning assistant. The research involves review of AI Agent solutions and frameworks, the design of the system architecture and agent workflows, the implementation of a functional prototype platform, and the experimental evaluation of the system's effectiveness, usability, and impact through a series of research-driven experiments and user studies. More details will be discussed with the candidates who have knowledge, skills and/or experience in the required research areas.
Research Environment:	Interns will work closely with academic supervisors and research staff, with access to environment that support open research, regular technical discussions, and engagement with ongoing projects in modern AI frameworks and it's application. Interns will also gain hands-on experience in designing, implementing, and evaluating advanced AI systems.
Novelty and Contribution:	.
Expected Outcomes:	Working prototype of an agentic AI system Research report including review of existing work, method, evaluation of ppropsoed solution Source code and technical documentation
Reference Material Links:	To be discussed with the selected intern.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Device Manager for Djawula
Name of Supervisor:	Gernot Heiser
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Szymon Duchniewicz
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Djawula is an seL4-based fully dynamic, general-purpose operating system under development at TS. Unlike the reasonably mature LionsOS, which has a static architecture, Djawula supports the security policy and system architecture to evolve at runtime. This requires support for enabling, disabling and configuring device drivers at runtime. > The aim of this project is to develop a device manager, similar to the one of Haiku OS, for dynamically managing seL4 device drivers. It needs to be integrated with Djawula's security enforcement and dynamically connect and disconnect clients to drivers.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	• design, implementation and evaluation of a device manager for seL4 device drivers in Djawula; • report describing the above.
Reference Material Links:	Please check with project lead.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	DocDML: Declarative Manipulation of Unstructured Data with LLM
Name of Supervisor:	Jianwei Wang
Email of Supervisor:	jianwei.wang1@unsw.edu.au
Name of Joint/Co-Supervisor:	Wenjie Zhang
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Modern organisations increasingly store valuable information as unstructured text: reports, support tickets, policies, scientific notes, web content, and AI-generated reasoning traces. While databases provide declarative operations for structured data—such as INSERT, UPDATE, DELETE, and SELECT—manipulating unstructured data still usually requires manually writing document-by-document Large Language Model(LLM) workflows. This project explores DocDML, a system for declarative manipulation of unstructured data with LLMs. Instead of writing a separate procedure for each document, users specify what content should be selected, how it should be changed, and what conditions must remain true after the change. For example, a user may ask the system to find explanations that are unnecessarily confusing, replace only the unclear part with a simpler explanation, and keep the final conclusion unchanged. The system identifies the relevant text, makes a small targeted update, checks that the result is still correct, and applies the change efficiently across a large collection. The student will contribute to the DocDML prototype by designing and evaluating declarative operators for selecting, updating, deleting, and querying textual data. The work will investigate how LLMs can act as semantic predicates, patch generators, and validators, while database techniques provide batching, versioning, provenance, and efficient execution.
Research Environment:	The student will work within the DKR group at UNSW Computer Science and Engineering, supported through regular meetings with the supervisory team. The project provides hands-on experience in database systems, language-model applications, experimental evaluation, and research software development. The student will have access to relevant computing infrastructure, language models, research datasets, and existing open-source declarative AI systems. Experience with Python is desirable; prior research experience is not required.
Novelty and Contribution:	.
Expected Outcomes:	- New declarative operators for manipulating unstructured textual chunks. - A prototype for semantic selection and local text updates using LLMs. - Support for constraints such as preserving specified content, maintaining verified answers, and limiting the size of an update. - A batching and caching strategy for applying one high-level observation across many textual records efficiently. - An evaluation comparing local semantic updates with full-document LLM rewriting, including correctness, update locality, model cost, and throughput. - Reproducible implementation, technical report, and poster/demo.
Reference Material Links:	'- DocDML project: https://github.com/T-Lab/DocDML - DocETL: https://github.com/ucbepic/docetl - LanceDB: https://docs.lancedb.com/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Enhancing Pancake parser with more PEG features
Name of Supervisor:	Miki Tanaka
Email of Supervisor:	miki.tanaka@unsw.edu.au
Name of Joint/Co-Supervisor:	Thomas Sewell, Michael Norrish
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Pancake is a research programming language currently under development at UNSW, Chalmers University, ANU, and Gothenburg University. It comes with a compiler that is verified correct using the HOL4 theorem prover, and is built from the ground up for predictable compilation and ease of verification. PEG (parsing expression grammar) is an expressive formalism for defining machine-oriented syntax that allows for parser generation. The current frontend, i.e., the parser for the concrete syntax, of the Pancake compiler uses the PEG as its core, but it does not leverage all of the features that PEG provides. This project is to reimplement the Pancake parser to use more of the PEG advantages to improve the parser performance and the maintainability, possibly by improving the HOL4 PEG library.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Report outlining the approach taken, tradeoffs considered and work done; 2. Pull request to the HOL4 and/or the CakeML/Pancake github repositories with an implementation and HOL4 formalisation.
Reference Material Links:	https://trustworthy.systems/projects/pancake/ https://github.com/CakeML/cakeml/tree/master/pancake https://github.com/hol-theorem-prover/hol
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Faithful LLM Persona Synthesis with Multi-Distribution Matching
Name of Supervisor:	Dr. Aditya Joshi
Email of Supervisor:	aditya.joshi@unsw.edu.au
Name of Joint/Co-Supervisor:	Haokai Zhao
Email of Joint/Co-Supervisor:	haokai.zhao@student.unsw.edu.au
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Using sets of LLM personas as stand-ins for real human populations is a key challenge in LLM-based social simulation. Recent methods use LLMs to generate personas from real social media histories or via structured sampling, and align them to a reference distribution such as Big Five psychometrics. But imagine a synthetic population whose Big Five personality profile is statistically indistinguishable from that of a real survey population. Ask these personas for their opinions on a policy, or observe how they actually behave in a simulated decision, and the match may fall apart: aligning a persona set to one reference distribution guarantees nothing about the others, and recent evidence shows that a persona's self-reported traits often dissociate from its behaviour. Instead of aligning the persona set to a single psychometric distribution, we aim to align it to multiple reference distributions simultaneously — spanning psychometric, opinion, and behavioural responses — and study whether jointly aligned persona sets generalize better to distributions and simulation tasks they were never aligned on. The team is co-led by Dr. Aditya Joshi, a Senior Lecturer in Natural Language Processing (NLP), and Haokai Zhao, a PhD student, in the UNSW-NLP research group. The ideal student will have strong programming skills in Python. A good grounding in statistics would be highly regarded.
Research Environment:	The student will be a part of the natural language processing (NLP) research group consisting of postdocs, software engineers and PhD students. The student will have access to typical computing facilities at UNSW.
Novelty and Contribution:	.
Expected Outcomes:	1. Reproduction of existing persona synthesis pipelines. 2. A benchmark of existing persona sets on survey and behavioural response distributions. 3. Develop new methods for synthesizing persona sets that generalize to unseen survey and behavioral distributions. 4. Well-documented code with accompanying documentation. 5. A report in a form suitable for a research paper.
Reference Material Links:	1. Population-Aligned Persona Generation for LLM-based Social Simulation (https://arxiv.org/abs/2509.10127) 2. LLM Generated Persona is a Promise with a Catch (https://arxiv.org/abs/2503.16527) 3. Will Scaling Improve Social Simulation with LLMs? (https://arxiv.org/abs/2607.02464) 4. Scaling Synthetic Data Creation with 1,000,000,000 Personas?https://arxiv.org/abs/2406.20094) 5. The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs (https://arxiv.org/abs/2509.03730) 6. Synthia: Scalable Grounded Persona Generation from Social Media Data (https://arxiv.org/abs/2507.14922)
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Feasibility of seL4 implemented in Pancake
Name of Supervisor:	Gernot Heiser
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Julia Vassiliki
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	The verified seL4 microkernel is implemented mostly in C (with a small amount of assembler code). Pancake is a new systems language developed by an international collaboration centered at Trustworthy Systems. Pancake's unique advantage is that it has a verified compiler that guarantees correct code generation, while having a much simpler (and thus more verification-friendly) semantics than C. It is mature enough to allow implementing much of LionsOS without a need for foreign function calls (FFIs) while performing close to C. This opens up an exciting possibility: Would it be possible to re-implement seL4 in Pancake, and potentially reducing the cost of maintaining seL4's proofs (to which the complexities of the C semantics are a major contributor)? This project is to evaluate the use of Pancake for implementing seL4. It does not require a formal-verification background, but deep experience in low-level programming in general and strong familiarity with kernel code in particular, as covered in COMP9242.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Prototype implementation of critical parts of the seL4 kernel, at least the IPC, Notification and interrupt fastpath, with missing functionality provided by C code (invoked via FFI). 2. Evaluation of fastpath performance compared to the original C version. 3. Report describing experience and performance.
Reference Material Links:	https://trustworthy.systems https://sel4.systems https://trustworthy.systems/projects/pancake/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Formalising and verifying device controllers
Name of Supervisor:	Miki Tanaka
Email of Supervisor:	miki.tanaka@unsw.edu.au
Name of Joint/Co-Supervisor:	Hammond Pearce, Gernot Heiser
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	The Trustworthy Systems (TS) group is working on verifying device drivers for LionsOS using the Pancake language. This work is inevitably dependent on a correct formalisation of the HW interface. We have established a workflow to take an open-source hardware designs of device controllers (from the OpenTitan project, for example) and formalise its software interface in the theorem prover HOL4. We then validate the formalised model against the origial hardware design by showing the equivalence/refinement between them. The project is to apply this workflow to produce more use cases, possibly by taking part in the on-going formalisation of devices such as I2C and SPI.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	• Report outlining the approach taken, tradeoffs considered and work done. - Pull request to the Trustworthy Systems Group's github repository with formalization and proofs.
Reference Material Links:	https://trustworthy.systems/projects/LionsOS/ https://trustworthy.systems/projects/pancake/ https://hol-theorem-prover.org/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Implementing and verifying Pancake compiler improvements
Name of Supervisor:	Miki Tanaka
Email of Supervisor:	miki.tanaka@unsw.edu.au
Name of Joint/Co-Supervisor:	Thomas Sewell
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Pancake is a research programming language for systems programming currently under development at UNSW, Chalmers University, ANU, and Gothenburg University. It comes with a compiler that is verified correct using the HOL4 theorem prover, and is built from the ground up for predictable compilation and ease of verification. The compiler is an optimising compiler going through many passes and intermediate languages, but there is scope to add many more to improve the quality and performance of generated code. Example improvements we're looking for include: - Multiple file compilation for Pancake. - Support division. - Support field updates to structs. - Further performance characterisation of the compiler, to identify other important compiler optimisations. These are just examples; the precise contents of this topic needs to be negotiated with the supervisors. This topic can take multiple students working different aspects of improvements.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Report outlining the approach taken, tradeoffs considered and work done; 2. Pull request to the CakeML/Pancake github repository with an implementation and HOL4 formalisation.
Reference Material Links:	https://trustworthy.systems/projects/pancake/ https://github.com/CakeML/cakeml/tree/master/pancake
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Improvements to Viper-based verification of seL4 Microkit
Name of Supervisor:	Rob Sison
Email of Supervisor:	r.sison@unsw.edu.au
Name of Joint/Co-Supervisor:	Zoltan Kocsis, Gernot Heiser
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	seL4 is the world's first operating system (OS) kernel with a proof of implementation correctness, followed by proofs of security enforcement; it is at the same time the benchmark for microkernel performance. The seL4 Microkit is a minimal seL4-based OS framework aimed at embedded and cyberphysical systems. Since verifying the key functionality of the Microkit's original C implementation using an in-house SMT solver-based framework, research at TS has been exploring the use of a new SMT solver-based automated deductive verification workflow based on transpilation to Viper to verify new Pancake language implementations of the Microkit library and Microkit-based OS components in a more scalable manner. This project is to continue bringing the verification of the seL4 Microkit library up to date using this workflow and integrate them into the Microkit's continuous integration testing framework.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security and safety critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Report describing experience verifying the latest Pancake language version of the seL4 Microkit library using the Viper-based workflow; 2. Pull requests against the seL4 Microkit library's implementation and continuous integration testing framework; 3. Verification of some simple Microkit-based example systems added to the CI testing framework if time allows.
Reference Material Links:	- https://sel4.systems/ - https://trustworthy.systems/projects/microkit/ - https://trustworthy.systems/projects/pancake-transpiler/ - https://trustworthy.systems/projects/pancake/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Investigating alternative verification backends for Pancake transpiler
Name of Supervisor:	Miki Tanaka
Email of Supervisor:	miki.tanaka@unsw.edu.au
Name of Joint/Co-Supervisor:	Gernot Heiser
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Pancake is a research programming language for systems programming under development at Chalmers University of Technology, ANU, and UNSW. It comes with a formally verified compiler and is built from the ground up for predictable compilation and ease of verification. We have a transpilation tool ("transpiler") that converts annotated Pancake code into Viper, an intermediate language for an SMT-backend. Using this transpiler, we have verified some properties of device drivers written in Pancake, with annotations stating the necessary conditions. The aim of this project is to investigate the possibility of alternative transpiler backends, such as Why3, for this verification framework. This will involve assessing the advantages and disadvantages over Viper, as well as the feasibility of hybrid verification (of SMT-based and interactive verification).
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Report outlining the approach taken, discoveries and conclusions of the investigation; 2. Pull request to the Trustworthy Systems Group's github repository (if applicable).
Reference Material Links:	https://trustworthy.systems/projects/pancake-transpiler https://www.pm.inf.ethz.ch/research/viper.html
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Linking Pancake annotations to a Hoare Logic
Name of Supervisor:	Miki Tanaka
Email of Supervisor:	miki.tanaka@unsw.edu.au
Name of Joint/Co-Supervisor:	Gernot Heiser
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Programming Languages and Software Engineering
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Pancake is a research programming language for systems programming under development at Chalmers University of Technology, ANU, and UNSW. It comes with a formally verified compiler and is built from the ground up for predictable compilation and ease of verification. We have a transpilation tool ("transpiler") that converts annotated Pancake code into Viper, an intermediate language for an SMT-backend. These annotations encode the pre- and post-conditions that specify the behaviour of the Pancake code in a pseudo-Viper syntax. We then verify that the code correctly implements the specification by sending the transpiled Viper files to the SMT-backend. The aim of this project is to explore the ways to represent these annotations directly in HOL4 interactive theorem prover, most likely as a Hoare logic. This work can leverage the currently on-going work on Viper semantics in HOL4, which is likely to provide a basis for semantics for annotated Pancake.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Report outlining the approach taken, tradeoffs considered and work done; 2. Pull request to the Trustworthy Systems Group's github repository with implementations.
Reference Material Links:	https://trustworthy.systems/projects/pancake-transpiler https://www.pm.inf.ethz.ch/research/viper.html https://hol-theorem-prover.org
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Look, Ask, Discover: Building a Smart Glasses Platform
Name of Supervisor:	Dr Mengyao Ma
Email of Supervisor:	mengyao.ma@unsw.edu.au
Name of Joint/Co-Supervisor:	Professor Yulei Sui
Email of Joint/Co-Supervisor:	y.sui@unsw.edu.au
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Smart glasses can provide users with immediate information about the objects and environments around them. This project explores how wearable cameras, multimodal AI and online information retrieval can be combined to help users look at an object, ask a question and receive a useful response through a smart-glasses interface. The student will develop a proof-of-concept platform that recognises objects captured by a wearable camera, understands spoken questions, retrieves relevant information from online sources, and presents concise answers through a simple wearable user interface. Example applications may include identifying everyday objects, finding product or location information, providing instructions, and assisting users with visual impairments. The resulting platform will provide a foundation for future smart-glasses applications such as navigation, translation and personalised assistance. Students should have basic Python programming skills and an interest in computer vision, multimodal AI or human–computer interaction. Experience with machine learning, APIs or UI development is desirable.
Research Environment:	The student will work with researchers in artificial intelligence, computer vision and wearable computing. The project will provide access to smart-glasses development hardware, multimodal AI models, web-search services and relevant computing resources. The student will receive regular supervision and gain hands-on experience in platform design, prototype development and experimental evaluation.
Novelty and Contribution:	.
Expected Outcomes:	'- A modular architecture connecting wearable camera input, multimodal AI, web search and user interaction - A proof-of-concept platform for object recognition, spoken questions and online information retrieval - A simple wearable user interface, demonstration scenarios, and an evaluation of accuracy, response time and usability - A software prototype, technical documentation, research report and project poster
Reference Material Links:	'- Google MediaPipe Object Detection: https://developers.google.com/edge/mediapipe/solutions/vision/object_detector - Grounding DINO - Open-Set Object Detection: https://github.com/IDEA-Research/GroundingDINO
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Making Learning Visible in Software Engineering: A Learning Analytics Approach?
Name of Supervisor:	Dr Shaveen Singh
Email of Supervisor:	shaveen.singh@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Software engineering education is inherently process-oriented. Students do not simply produce a final software product; they continuously interpret requirements, design solutions, write and review code, test, debug, collaborate, seek feedback, and revise their approaches. However, much of this learning remains invisible. Traditional assessment typically captures visible outputs - such as the final codebase, report, demonstration, or examination - while providing limited insight into how students reached those outcomes. ? This project applies a learning analytics approach to examine software engineering processes through the lens of self-regulated learning (SRL). It involves designing and evaluating a Learning Analytics Dashboard (LAD) that transforms software development activity into indicators of learning and engagement, supporting student reflection and providing educators with evidence to guide learning support.? Project Phases : ========== 1. Review the literature on self-regulated learning and identify relevant indicators that support monitoring, reflection, and behavioural adjustment. 2. Co-design the LAD with potential users, such as software engineering students, and develop a functional prototype. 3. Evaluate the LAD with a small group of users (e.g., a student focus group), focusing on usability, functionality, and usefulness.
Research Environment:	Software/Tools: - GitLab and GitLab Analytics for software development activity data. - Node.js, TypeScript, and React/TSX for LAD development. - Figma or similar tools for interface prototyping and co-design. Data: - GitLab activity data, such as commits, merge requests, issues, and code reviews. - De-identified or synthetic student software development activity data. - User feedback collected through co-design sessions, usability testing, and focus groups.
Novelty and Contribution:	.
Expected Outcomes:	1. A set of self-regulation indicators relevant to software engineering students. 2. A functional LAD prototype providing self-regulation-oriented insights. 3. A research report (15-20 pages) presenting the LAD’s design and evaluation findings on its usability, usefulness, and potential to support self-regulated learning.
Reference Material Links:	1. Bistolfi, I., de Mooij, S., Sparou, C., Molenaar, I., & van der Graaf, J. (2026, July). Co-designing a Dashboard Promoting SRL for Secondary Education. In International Conference on Human-Computer Interaction (pp. 37-58). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-032-30781-1_3 2. Aguilar, S. J., Karabenick, S. A., Teasley, S. D., & Baek, C. (2021). Associations between learning analytics dashboard exposure and motivation and self-regulated learning. Computers & Education, 162, 104085. DOI: 10.1016/j.compedu.2020.104085 3. Matcha, W., Uzir, N. A. A., Gaševi?, D., & Pardo, A. (2019). A systematic review of empirical studies on learning analytics dashboards: A self-regulated learning perspective. IEEE transactions on learning technologies, 13(2), 226-245. DOI: 10.1109/TLT.2019.2916802
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	New device classes for sDDF
Name of Supervisor:	Gernot Heiser
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Peter Chubb
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	The seL4 Device Driver Framework (sDDF) provides the basis for high-performance I/O in LionsOS, currently under development in TS. It presents a highly modular design with a (compared to Linux) much simplified driver model. The sDDF presently specifies driver interfaces for a number of device classes, this project is to contribute another class. Of specific interest are: - HID devices - video capture (camera)
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. specification of sDDF driver interfaces; 2. implementation – depending on the device class and the complexities of the interface, this could be a native driver written from scratch, a native driver ported from a different OS, or a a driver embedded in its normal OS running as a guest in a virtual machine on top of seL4 (a “driver OS”); 3. performance evaluation (keeping in mind that a driver OS will have limited ability to test the performance limits of the design).
Reference Material Links:	https://trustworthy.systems https://sel4.systems https://stage.trustworthy.systems/projects/drivers/ https://stage.trustworthy.systems/projects/LionsOS/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Proving even more functional properties for seL4's system calls
Name of Supervisor:	Rob Sison
Email of Supervisor:	r.sison@unsw.edu.au
Name of Joint/Co-Supervisor:	Gernot Heiser
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	seL4 is the world's first operating system (OS) kernel with a proof of implementation correctness, followed by proofs of security enforcement; it is at the same time the benchmark for microkernel performance. The seL4 Microkit is a minimal seL4-based OS framework aimed at embedded and cyberphysical systems. The verification of the seL4 Microkit library relies on the kernel correctly implementing certain functional properties of seL4's system calls, phrased as postconditions on the system call's outputs it must meet if its caller satisfies preconditions on its inputs. Work at TS is now underway on proving such properties are satisfied by the seL4 kernel's abstract specification in the Isabelle/HOL interactive theorem prover. This project is to increase the coverage of functional properties proved about seL4's system calls, continuing to focus on cases most relevant to their use by the seL4 Microkit. Stretch goals can include proving further such properties as guided by the informal specifications given in the seL4 Reference Manual.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security and safety critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. Verification of a Microkit-relevant functional property for at least one seL4 system call; 2. Report describing experience and any new proof infrastructure developed to verify seL4 system call functional properties using Isabelle/HOL.
Reference Material Links:	- https://sel4.systems/ - https://trustworthy.systems/projects/microkit/verification/ - https://trustworthy.systems/projects/kugap/ - https://isabelle.in.tum.de/ - https://sel4.systems/Info/Docs/seL4-manual-latest.pdf
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Robots to the Rescue
Name of Supervisor:	Prof Maurice Pagnucco
Email of Supervisor:	.
Name of Joint/Co-Supervisor:	A/Prof Yang Song
Email of Joint/Co-Supervisor:	yang.song1@unsw.edu.au
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Robot’s have the potential to revolutionise how we undertake dangerous and mundane tasks. Search and rescue is one such dangerous task. In this project we develop an urban search and rescue robot using the 4-legged Unitree Go2 robot. We will develop advanced mapping and search techniques able to operate in simulated rescue scenarios. The eventual goal is to compete in the annual RoboCup Rescue competition. In this project you will learn how to use the data from the many sophisticated sensors on the Go2 to navigate rescue environments and identify objects including people that require assistance.
Research Environment:	Robotics Lab in the School of Computer Science and Engineering, working with current Vertically Integrated Project and Honours thesis students on the same topic.
Novelty and Contribution:	.
Expected Outcomes:	Development & Implementation: Implement sophisticated navigation and computer vision algorithms using the Robot Operating System (ROS). RoboCup Experience: Development of a competitor for the international RoboCup Rescue competition.
Reference Material Links:	https://yuheng-andy-jian.github.io/UNSW-Robocup-Rescue/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Secure Point-of-Sale Reference System
Name of Supervisor:	Gernot Heiser
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Lesley Rossouw
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	The TS group has a simple point-of-sale system implemented on top of LionsOS. This project is to revisit its architecture from the security point-of-view, including minimising the trusted computing base (TCB) and investigate feasibility of verifying the TCB. Options to investigate include implementing the business/accounting logic in a verification-friendly language (Pancake or CakeML) and using scalable verification approaches under investigation in TS.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	• Report describing the evaluation, proposed design/implementation and take-aways; • any design, implementation and verification artefacts resulting from the above.
Reference Material Links:	Please check with project lead.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	VMM environment for developing Microkit applications on Linux
Name of Supervisor:	Gernot Heiser
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Peter Chubb
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	The seL4 Microkit provides a simple programming model for seL4-based systems, aimed at supporting embedded systems. Developing directly on an embedded platform restricts the available tools, and it would be preferable use a full Linux environment for development. There exists a rudimentary library for emulating Microkit interfaces on Linux, using UIO to map sDDF shared memory into the space, and to map between notification events and Linux IRQs. There also exists the ability to pass a block device through to a Linux VMM. This leaves the following tasks: 1. maturation of the library including (synchronous) protected procedure calls; 2. inclusion of simple ways to map device registers and IRQs into UIO; 3. actual use cases of drivers developed using this framework.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1. A framework that allows using a standard editor, make, GCC, and GDB inside a Linux VMM to build and debug components that can then be deployed natively. 2. Report describing the system.
Reference Material Links:	https://trustworthy.systems https://sel4.systems https://trustworthy.systems/projects/microkit/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Zephyr-compatible API for LionsOS
Name of Supervisor:	Gernot Heiser
Email of Supervisor:	gernot@unsw.edu.au
Name of Joint/Co-Supervisor:	Courtney Darville
Email of Joint/Co-Supervisor:	.
School:	School of Computer Science and Engineering
For CSE and EET Projects:	School Project
Faculty Research Area (Theme):	Embedded Systems and Communications
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Zephyr is a small real-time operating system for connected, resource-constrained and embedded devices. It's popularity make it a de-facto standard for embedded systems, with many embedded-systems engineers familiar with its API. Support for the Zephyr API in LionsOS would therefore ease porting embedded applications into native components.
Research Environment:	The Trustworthy Systems (TS) Group is the pioneer in formal (mathematical) correctness and security proofs of computer systems software. Its formally verified seL4 microkernel, now backed by the seL4 Foundation, is deployed in real-world systems ranging from defence systems via medical devices, autonomous cars to critical infrastructure. The group's vision is to make verified software the standard for security- and safety-critical systems. Core to this a focus on performance as well as making software verification more scalable and less expensive.
Novelty and Contribution:	.
Expected Outcomes:	1 Design, implementation and evaluation of a Zephyr-compatible API on top of Lions (with liberal re-use of Zephyr code (as permitted under its permissive license). 2. Report describing the above.
Reference Material Links:	https://trustworthy.systems https://sel4.systems https://stage.trustworthy.systems/projects/LionsOS/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Projects offered by other Engineering Schools that may be of interest are:

Graduate School of Biomedical Engineering

Project Title:	Combination Therapy with Antimicrobial Peptides to Combat Multidrug-Resistant Bacteria
Name of Supervisor:	Edgar Wong
Email of Supervisor:	edgar.wong@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Chemical Engineering
Faculty Research Area (Theme):	Health & Medical Technologies
Applicable to other Engineering schools/disciplines:	Biomedical Engineering Computer Science & Engineering Mechanical & Manufacturing Engineering Photovoltaic and Renewable Energy Engineering
Terms:	Summer
Abstract:	Antimicrobial resistance (AMR) is now considered a critical global healthcare challenge and urgently requires new therapeutic strategies to overcome this issue. Antimicrobial peptides (AMPs) and mimics thereof have been shown to effectively synergise and revive the 'lost' activity of antibiotics against multidrug-resistant bacteria. This approach is promising in combating AMR and we aim to build upon our initial work and develop further. The project will look at testing more combinations and against wider panel of bacteria including priority pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii.
Research Environment:	Very biofocussed project and hence the scholar will be mainly working in a PC2 microbiology lab to perform antimicrobial assays. Scholar needs to have good attention to detail.
Novelty and Contribution:	.
Expected Outcomes:	Tested various combinations of AMPs and antibiotics against different bacteria strains. The results are expected to lead to high impact publication and also further in vivo testing in animal models with collaborators, which would form the basis of preclinical work for future translation. The scholar will learn/enhance technical skills at working in a biolab and also develop deep knowledge in the AMR field.
Reference Material Links:	https://www.edgarwonglab.com/ https://pubs.acs.org/doi/full/10.1021/acsinfecdis.2c00087 https://pubs.acs.org/doi/full/10.1021/acs.biomac.4c01137 General reading on antimicrobial peptides (AMPs) and combination therapy
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No