Recent technological advances in micro and nano-fabrication technology and high-yield electrophysiology techniques allowed us to record the activity of hundreds/thousands of neurons simultaneously. This has spurred renewed interest in applying multi-electrode extracellular electrophysiology approaches in the field of neuroscience. Each electrode samples the activity of one or more neurons in its vicinity.
Honours and Masters project
Displaying 191 - 200 of 232 honours projects.
The evolutionary back and forth between hosts and mobile genetic elements drives the innovation of remarkable molecular strategies to sense or conceal foreign genetic material. The Knott Lab uses bioinformatics, biochemistry, and structural biology to understand how CRISPR-Cas and other novel immune systems specifically sense DNA or RNA. We aim to better understand the function of nucleic acid sensors to harness their activity as tools for molecular diagnostics or as innovative biomedicines.
The rapid growth of electric vehicles (EVs) is transforming the transportation systems worldwide. Both EV fleets and private EVs are emerging as a cleaner and more sustainable component of urban mobility, forming an effective way to solve environmental problems and reduce commute costs in future smart cities. Due to the complex spatiotemporal behaviors of passengers and their travel patterns, the unmanaged electric charging demand from EVs may significantly impact the existing transportation and electrical power infrastructure.
Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic speech recognition, and autonomous driving, etc. However, due to the intrinsic vulnerability and the lack of rigorous verification, DL systems suffer from quality and security issues, such as the Alexa/Siri manipulation and the autonomous car accidents, which are introduced from both the development and deployment stages.
Are you interested in working with hospital data? This project is a collaboration with the Faculty of Medicine, Monash University. In this project, you will be working with medical doctors from Monash Health.
Political polarization is a phenomenon that permeates societies worldwide, manifesting in divergent ideologies, entrenched viewpoints, and societal fragmentation. In the context of Indonesia, a diverse and populous nation with a complex socio-political landscape, understanding political polarization is crucial for fostering social cohesion and effective governance.
In this project, we aim at surveying relevant computational tools/models used for automatic question generation, and then comparing the effectiveness of these tools/models by using existing datasets.
Current studies on diabetes recommender systems and apps mainly focus on the performance and personalisation of AI models and techniques, including machine learning and deep learning models that are trained on user data. These works often use a one-size-fits-all approach for presenting information to users. Yet, research shows that humans process information in different ways, and their attitudes towards an action depend on their attitude-function styles.
The convergence of Artificial Intelligence (AI) with immersive technologies such as Augmented Reality (AR) and Virtual Reality (VR) is rapidly transforming the landscape of healthcare and medical training. While AI enhances decision-making through data-driven insights, AR and VR offer intuitive, spatial, and interactive environments that support diagnostics, education, therapy, and surgical planning. However, the integration of these technologies remains fragmented, with varying degrees of adoption, technical maturity, and clinical impact.
The Javanese language, spoken by a population of over 98 million people, faces notable challenges in digital and technological applications, especially when compared to globally recognized languages. This disparity is highlighted in several studies that discuss the lack of deep learning research benefits due to data scarcity for Javanese. Additionally, other studies have pointed out the inaccessibility of data resources and benchmarks for Javanese, contrasting with languages like English and Mandarin Chinese.