Meet our Co-Lab Honours Grants recipients

Meet our Co-Lab Honours Grants recipients
Meet our Co-Lab Honours Grants recipients

The Australian National University (ANU) Australian Signals Directorate (ASD) partnership recently welcomed a new cohort of Honours students who will work on research with the potential to solve national security challenges.

The 17 ANU-ASD Co-Lab Honours Grant 2023 recipients were celebrated on 4 April by ANU Vice Chancellor Professor Brian Schmidt AC and ASD First Assistant Director Stephen McGlynn.

The award is available for Australian undergraduate students undertaking ANU Honours research projects adjacent to ASD research interests, from linguistics and and cryptography to mathematics and cyber security.

The Co-Lab Grant also offers career-focused support for students while they develop their projects. The cohort will be provided with training and mentoring, including career development opportunities and access to networking events that will help build important connections to bolster their early careers. By the end of the year, the students prepare to showcase and present their research.

The 2023 cohort will focus on a wide range of cross-disciplinary research topics, with eight students who are pursuing Honours in areas of expertise supervised by the ANU College of Engineering, Computing and Cybernetics (CECC).

We recently had the opportunity to meet the group and learn about the CECC Honours projects at a welcome event hosted by the ANU-ASD Co-Lab.

We’re excited to see how these projects develop, and to learn about our student’s Co-Lab Honours experience as the year goes on.

Angus Atkinson

Improving garbage collection within computers

“I’m looking at garbage collection,” says Angus. “It’s a technique that programming languages use to keep track of what memory is or isn’t being used by a program, and automatically frees it when it’s not in use so it can be used by other programs.”

Angus hopes to speed up what is currently a memory intensive task.

“The problem with garbage collection is that it’s very memory intensive. It involves going through the entire memory space of a program to search what things point to other things and work out what’s in use.

“I’m looking at how we can speed garbage collection up by using something called software cache prefetching. The aim is to tell a computer what things to store in the cache. That way the things we need are in fast memory, speeding things up.”

Nicholas Dale

Risks posed by microarchitecture vulnerability in Arm64 CPUs

“I’m looking at the vulnerabilities present in CPUs at a hardware level,” says Nicholas. “Things that are generally very difficult to patch out because they’re issues in the silicon. Basically, identifying design flaws.

“The focus I’m looking at now is on arm 64 CPUs. For example, Apple silicon ones. It’s a new and emerging area in CPU development, with new architecture that has a lot of aspects that aren’t present in other CPUs.

Nicholas has posed several research questions to explore throughout his Honours project, including reviewing: “What are the vulnerabilities? Can they be exploited? And what is the impact of these risks?”

Cormac Kikkert

Moving CEGAR-Tableaux to solve new, more complex logics

Cormac’s research is looking to further develop a tableaux-like method that’s already proven successful at solving model logics over the standard benchmarks.

“CEGAR-Tableaux is a new type of algorithm that can solve the modal logic K really fast, which I created a few years ago. K is the simplest modal logic and has the most competition. So, the fact that CEGAR-Tableaux is the fastest solver on K makes the prospect of extending it to harder logics promising.

“The hope is that I can extend it to solve non-classical logics really fast,” says Cormac.

“This could be used for computer verification, because you can formulate computer code as formulae and see whether it’s possible to run into a big error. This makes it very useful for correctness.”

“It would be great if it can be used with other harder logics, to solve other more complex problems.”

Stefan Rebel

Engineering remote, long-life early bushfire detection systems

“As part of the ANU Bushfire Initiative, my project is to develop a wireless sensor network that’s going to be deployed out in the bush to detect the early ignition of bushfires,” says Stefan.

Stefan’s research will be focused on engineering systems that are long-life and sustainable in regional and remote areas of Australia.

“These bushfire sensors will need to be deployed in remote regions where they won’t have access to power,” said Stefan.

“Firstly, I’ll be doing a circuit board design for the sensor limits. I’ll then complete power consumption analysis for these boards. Based on the information, I’ll aim to make a solar power supply to ensure they can survive for a long time out in the bush.”

Jonas Schwerin

Continued research on Smart Tracker technology

“This year, I’ll be reverse engineering a specific smart tracking brand and figuring out if it’s safe to use,” says Jonas.

“This will be a continuation of another project at ANU where smart tags and AirTags have been reverse engineered. We’ll be working on reverse engineering ours and eventually making a detection model that minimises safety concerns.”

Jonas’ work will help towards better understanding the impact of this increasingly popular technology.

“Many people are starting to use them a lot more, with a lot of different companies coming into play. We want to figure out if all these trackers are safe to use and determine if the Bluetooth technology is being used correctly.”

Ashley Tang

Exploring ways to mend the reproducibility crisis

“My Honours project is looking at the reproducibility crisis,” says Ashley. “Basically, code and results not being sufficiently reproducible in scientific computing.”

“I’m looking at how different Q&A forums – such as Stack Overflow, datascience and The AI Exchange – can help to promote and identify gaps in our understanding of reproducibility.”

Ashley’s project will examine the technology along with user attitudes and behaviours, to make recommendations for enhancements.

“I’m using natural language processing analysis like topic modelling to uncover the kind of challenges, discussions and opportunities for how we can improve it.”

“I’ll use an online survey with developers to uncover their perceptions of reproducibility and the code in those forums as well.”

You are on Aboriginal land.

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

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