35+ post-docs and students
Note - the Programme and Posters is subject to change
Neural Radiance Field Based Computerised Tomography Reconstruction (Aaron Smith, University of Canterbury)
Enhancing Aerial Imagery Analysis: Leveraging Explainability and Segmentation (Anany Dwivedi, University of Waikato)
Generative Pre-trained Workflow Transformer: Transforming User Story to Workflow (Ardi Oeij, Lincoln University)
Active Few-shot Learning for Rare Bioacoustic Feature Detection (Ben McEwen, University of Canterbury)
Predicting Wildfires in Canadian Forests from Satellite Images using Deep Learning (Blesson Mammen, Unitec Institute of Technology)
Symmetric Self-Paced Learning for Domain Generalization (Di Zhao, University of Auckland)
Forecasting Sea Surface Temperatures and Anomalies Using Graph Neural Networks (Ding Ning, University of Canterbury)
Multi Modal CNN Transformer for Embryo Morphokinetic State Classification on Single Images and Time Inputs (Hooman Misaghi, University of Auckland)
ESG disclosure and investors’ attention: Evidence from Mutual fund prospectuses (Huayu Shi, University of Auckland)
Anomaly Detection for Maritime Trajectories (Jack Julian, University of Auckland)
Towards Robust Strategies for Satellite Streak Identification in Wide-Field Astronomical Survey Images (Jack Patterson, University of Canterbury)
End-to-end Knowledge Graph Construction System Powered by Large Language Models (Jason Pang, Lincoln University)
If outliers exist contaminated else not contaminated (Jesse Wood, Victoria University of Wellington)
Adaptive Isolation Forest (Jia(Justin) Liu, University of Waikato)
A framework for the segmentation of the cerebral cortex laminar structure (Jiaxuan Wang, University of Auckland)
Personality-based Hybrid Machine Learning Model for Mentor-Mentee Matching using Collaborative and Content Filtering Methods (Jitty Varghese, Auckland University of Technology)
Enhancing Fake News Classification in Urdu: A Multilingual Large Language Model Approach with Domain Adaptation for Low Resource Languages (Muhammad Zain Ali, University of Waikato)
Combining physics and artificial intelligence: a hybrid model for actionable climate projections (Neelesh Rampal, NIWA)
ASML: A Scalable and Efficient AutoML Solution for Data Streams (Nilesh Verma, University of Waikato)
Learning from Task Metadata in Multi-Task Learning (Olivier Graffeuille, University of Auckland)
Machine Learning for Cold-Formed Steel Design (Parsa Yazdi, University of Waikato)
Investigating Deep Hybrid Models for Out Of Distribution Detection (Paul Schlumbom, University of Waikato )
Deep Learning-Based Prediction of Ischaemic Heart Disease and Atrial Fibrillation Using Electrocardiogram Data (Pengqian Han, University of Auckland)
Unveiling the Rational Foundations of Acupuncture Point Selection and Combinations for healing some diseases through Complex Network Analysis (Pranesh Shrestha, Unitec Institute of Technology)
Increasing the Effective Sequence Length of Large Multimodal Model for Document Understanding and Processing (Qiming Bao, University of Auckland)
Optimising Returns on Earth Observation Missions Using Deep Learning-Based Architectures for Cloud Detection in Remote Sensing Images (Ronnie Paguia, Auckland University of Technology)
Enhancing self-driving: Speed bump and pothole detection and quantization (Ruigeng Wang, University of Auckland)
Leveraging Machine Learning and Deep Learning for Climate Change Mitigation: A Multifaceted Approach (Simna Rassak, ESR)
Deep reinforcement learning based planning method in state space for lunar rovers (Siyao Lu, University of Auckland)
Efficient Deep Learning-based Representation of Minimal Surfaces (Sobhan Latifi, University of Otago)
Trajectory Flow Map Enhanced Transformer for Next POI Recommendation (Song Yang, University of Auckland)
Quantile-Boost: An Ensemble Algorithm for Downscaling Extreme Precipitation (Thomas Bailie , University of Auckland)
Anomalous Precipitation Detection using Deep Autoencoders (Tobias Milz, University of Canterbury)
Adaptive Prediction Interval for Data Stream Regression (Yibin Sun, University of Waikato)
Zero-Knowledge Proof-based Verifiable Federated Learning on Blockchain (Zhibo Xing, University of Auckland)
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models (Zihao LUO, University of Auckland)
For more information on talks see the programme information. For abstracts click here.