Two-Day Face-to-Face Partial Discharge- Fundamentals, Testing and Industry Experience CPD Course

30 January 2025 8:30am31 January 2025 5:45am
This CPD course will feature presentations by Prof. Dr.- Ing. Stefan Tenbohlen from the Institute of Power Transmission and High Voltage Technology at the University of Stuttgart in Germany. This course will deliver the theoretical background information necessary to develop a good understanding of the phenomena of partial discharge (PD) in high-voltage equipment, as well as current measurement techniques for partial discharge. Along with this, the course will look at the experience of industry using partial discharge for diagnostic and testing work. Using the high-voltage laboratory at the University of Queensland, there will be demonstrations of some key measurement techniques for partial discharge.

Mitigating Distribution Shifts in Using Pre-trained Vision-Language Models

2 December 2024 11:00am
In this talk, I will first introduce our recent work to fine-tune a pre-trained VLM with downstream tasks, and further improve the generalisation ability of a pre-trained VLM. Then, I will introduce another work on how to detect label set shift when using pre-trained VLMs in zero-shot classification.

Scalable and Lightweight Content-based Recommender Systems

28 November 2024 11:00am
Content-based recommender systems (CRSs) play a crucial role in assisting users to navigate the vast information available on the Internet.

Two-Day Face-to-Face Bushings for Power Transformers- Design, Maintenance and Testing CPD Course

28 November 2024 8:30am29 November 2024 5:45pm
This two-day face-to-face course will bring industry professionals together for dialogue and sharing of knowledge to better understand the operation of bushings for power transformers, as well as the design, maintenance and testing thereof.

Towards Graph Machine Learning in the Wild

27 November 2024 1:00pm
In this talk, we will introduce recent advances that develop theoretically principled and practical useful methods for learning on graphs in the challenging open-world hypothesis, where the model needs to generalize to out-of-distribution testing data in the wild.
2024 Innovation showcase

Innovation Showcase 2024

20 November 2024 5:00pm7:00pm
Don't miss the 2024 Innovation Showcase, a unique opportunity for EECS students to showcase their end of year projects to industry partners and the UQ community.

Evaluation and Reasoning in Real-world Scenarios

20 November 2024 1:00pm
This talk will cover evaluating and training LMs to reason in real-world scenarios.

Long-Range Meets Scalability: Unveiling a Linear-Time Graph Neural Network for Recommendation at Scale

13 November 2024 1:00pm
In this talk, I will introduce Linear-Time Graph Neural Network (LTGNN), a breakthrough approach designed to bridge the scalability gap between GNNs and simpler methods without sacrificing GNNs’ unique ability to capture distant dependencies.

Renewable Energy Integration: CPD Course

13 November 2024 8:30am14 November 2024 5:00pm
This two-day face-to-face course will bring industry professionals together for dialogue and knowledge sharing to better understand the renewable energy technologies and their integration regarding renewable generator modelling, control techniques, frequency and voltage regulation aligning with grid codes.

Introduction to the Fundamentals of Power Systems: CPD Course

11 November 2024 8:30am12 November 2024 5:00pm
This two-day face-to-face course will bring industry professionals together for dialogue and sharing of knowledge to better understand the fundamentals of power systems along with its modelling and operational aspects.

Contextual Document Embeddings

6 November 2024 11:00am
In this work, we argue that dense document embeddings, while effective, are implicitly out-of-context for targeted use cases of retrieval, and that a contextualized document embedding should take into account both the document and neighboring documents in context - analogous to contextualized word embeddings.

Graph Neural Networks in Epidemic Modeling: An In-Depth Review and Toolkit

30 October 2024 1:00pm
This talk offers a comprehensive review of GNN applications in epidemic modeling, presenting a hierarchical taxonomy for both epidemiological tasks and modeling techniques.

See All You Want: Detecting Everything with Vision Foundation Models

23 October 2024 3:00pm
We introduce Dispersing Prompt Expansion DiPEx, a self-supervised prompt learning strategy that overcomes the limitations of manually crafted text queries in VLMs, which often miss objects due to semantic overlap diminishing detection confidence.

Advanced Strategies to Alleviate Challenges of Data Scarcity in Deep Learning for Medical Image Analysis

23 October 2024 11:00am
This PhD study aims to tackle the common challenges by designing novel training strategies for deep learning models trained on imperfect datasets.

Inference-Time Strategies for Ranking and RAG with LLMs

23 October 2024 9:30am
While Large Language Models (LLMs) exhibit strong zero-shot capabilities, carefully designed inference-time strategies are crucial for unlocking their full potential. This talk delves into two tasks where this is particularly evident: text ranking and retrieval-augmented generation (RAG).

Decentralized POI Recommender Systems

21 October 2024 10:00am
This thesis proposes several key works as solutions in decentralized POI recommender systems.

Graph Foundation Model in the Era of LLMs

16 October 2024 1:00pm
The central focus of our research: developing large language models and foundational models specifically tailored for graph data.

Language Inclusivity with Foundation Models

10 October 2024 3:00pm
In this talk, I will outline the progress in LLM research, and the opportunities they afford to multilingual settings.

Recreating the Physical Natural World from Images

9 October 2024 1:00pm
In this talk, I will discuss an alternative approach through inverse rendering, which enables machine learning models to extract explicit physical representations from raw, unstructured image data, such as Internet photos and videos.

Human-Computer Conversational Vision-and-Language Navigation

8 October 2024 11:00am
This presentation embarks on a comprehensive exploration of the VLN trajectory, tracing its inception to seminal benchmarks such as Room-to-Room (R2R).

Automatic Retinal Health Monitoring through Multi-modal Medical Imaging

2 October 2024 3:30pm
This project aims to develop a multi-modal, multitask diagnostic algorithm that leverages several novel deep learning innovations.

Entrepreneurship: What does it Mean to EMCRs?

27 September 2024 1:00pm
The EECS EMCR Advocacy Committee invites you to a panel session themed around entrepreneurship development.

Mitigating Domain Shifts in Real-world Image Recognition

19 September 2024 12:00pm
This thesis focuses on practical scenarios of domain adaptation.

Towards Graph Foundation Model

11 September 2024 1:00pm
In this talk, we will introduce: (1) The long-term technical goal will the GFMs serve (2) The knowledge gap in the graph domain the GFMs can fill (3) The critical problem GFMs can solve.

Integrating Text and Audio Signals for Efficient and Effective Podcast Search

2 September 2024 9:00am
Searching the gigantic corpus of online podcasts involves multiple challenges ranging from content and style diversity to expensive audio processing to variable length. In this thesis, we aim to address these challenges and devise novel approaches to improve state-of-the-art performance.

Self-Supervised Learning for Irregular Time Series

16 July 2024 11:00am
Our primary research question is how we can effectively utilize limited labelled data for irregular time series modelling?

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