Dr. Yang Zhao

Dr. Yang Zhao

she/her

Lecturer (Assistant Professor), La Trobe University

Yang Zhao

About Me

I am a Continuing Lecturer (Assistant Professor) in the Department of Computer Science and Information Technology at La Trobe University. Before joining La Trobe, I was a Machine Learning Research Fellow at the Australian Institute for Machine Learning, The University of Adelaide.

My research lies broadly in computer vision and deep learning, with a particular focus on developing vision-language models, multimodal learning methods, and foundation model techniques that can be applied to real-world challenges across disciplines. My current interests include AI for sustainable agriculture, AI for health, and interdisciplinary applications of AI in areas such as cultural heritage.

I am always open to interdisciplinary collaboration and currently supervise Honours, Master’s, and Doctoral students.

Recent News

  • [Aug 2026] I’m honoured to share that I’ve been selected as a finalist for the Data Science / AI Pioneer Award at the 2026 Women of Colour in STEM Awards.
  • [Jan 2026] One paper “VaseVQA-3D: Benchmarking 3D VLMs on Ancient Greek Pottery” has been accepted to ICLR 2026.
  • [Jan 2026] One paper “VaseVQA: Multimodal Agent and Benchmark for Ancient Greek Pottery” has been accepted to EACL 2026.
  • [July 2025] One paper “PresentAgent: Multimodal Agent for Presentation Video Generation” has been accepted to EMNLP 2025.
  • [July 2025] One paper “PedDet: Adaptive Spectral Optimization for Multimodal Pedestrian Detection” has been accepted to ECAI 2025 (spotlight).
  • [July 2025] One paper “Contrastive Lie Algebra Learning for Ultra-Fine-Grained Visual Categorization” has been accepted to MM 2025.
  • [June 2025] One paper “Advancing federated domain generalization in ophthalmology: Vision enhancement and consistency assurance for multicenter fundus image segmentation” has been accepted to Pattern Recognition.
  • [June 2025] One paper “CIT: Rethinking class-incremental semantic segmentation with a Class Independent Transformation” has been accepted to Pattern Recognition.
  • [March 2025] One paper “MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule” has been accepted to ICME 2025.
Older news
  • [Dec. 2024] Received SCEMS Early Career Researcher Award 2024 at La Trobe University.
  • [Nov. 2024] Received Australian Pattern Recognition Society (APRS) Early Career Researcher Award 2024 at DICTA 2024.
  • [Nov. 2024] Invited talk “Landmark Detection and Medical Applications” at DICTA 2024.
  • [Oct. 2024] One paper “MedDet: Generative Adversarial Distillation for Efficient Cervical Disc Herniation Detection” has been accepted to BIBM 2024 (Oral).
  • [July 2024] One paper titled “Motion Avatar: Generate Human and Animal Avatars with Arbitrary Motion” has been accepted to BMVC 2024.
  • [April 2024] One paper titled “Artificial Intelligence to Automate Assessment of Ocular and Periocular Measurements” has been accepted to European Journal of Ophthalmology.
  • [Feb. 2024] One paper titled “A Landmark-based Approach for Instability Prediction in Distal Radius Fractures” has been accepted to IEEE ISBI 2024.
  • [Jan. 2024] One paper titled “Facial and Mandibular Landmark Tracking with Habitual Head Posture Estimation using Linear and Fiducial Markers” has been accepted to Healthcare Technology Letters.
  • [Jan. 2024] One paper titled “Self-Supervised Lie Algebra Representation Learning via Optimal Canonical Metric” has been accepted to IEEE TNNLS.
  • [Jan. 2024] One paper titled “Occluded Person Retrieval with Hierarchical Feature Optimization” has been accepted to IEEE FG 2024 (Oral) (best reviewed papers).
  • [Aug. 2023] I joined CSIT, La Trobe University as a continuing Lecturer (Assistant Professor).
  • [Feb. 2023] One paper titled “Normal periocular anthropometric measurements in an Australian population” has been accepted to International Ophthalmology.
  • [Nov. 2022] One paper “Learning Deep Asymmetric Tolerant Part Representation” accepted in IEEE TAI.
  • [Oct. 2022] One paper “Mix-ViT: Mixing Attentive Vision Transformer for Ultra-Fine-Grained Visual Categorization” accepted in Pattern Recognition.
  • [Aug. 2022] One paper “Gait-Assisted Video Person Retrieval” accepted in IEEE TCSVT.
  • [Apr. 2022] One paper “SPARE: Self-Supervised Part Erasing for Ultra-Fine-Grained Visual Categorization” accepted in Pattern Recognition.
  • [Apr. 2022] One paper “RB-Net: Training Highly Accurate and Efficient Binary Neural Networks with Reshaped Point-wise Convolution and Balanced Activation” accepted in IEEE TCSVT.
  • [Feb. 2022] I joined AIML, The University of Adelaide as a Machine Learning Orthopaedic Research Fellow.
  • [Sept. 2021] One paper “EAR-NET: Error Attention Refining Network For Retinal Vessel Segmentation” accepted in DICTA 2021.
  • [Aug. 2021] One paper “Learning Discriminative Region Representation for Person Retrieval” accepted in Pattern Recognition.
  • [Jul. 2021] One paper “Benchmark Platform for Ultra-Fine-Grained Visual Categorization Beyond Human Performance” accepted in ICCV 2021.
  • [May 2021] One paper “MaskCOV: A Random Mask Covariance Network for Ultra-Fine-Grained Visual Categorization” accepted in Pattern Recognition.
  • [Mar. 2021] One paper “Learning Deep Part-Aware Embedding for Person Retrieval” accepted in Pattern Recognition.
  • [Feb. 2020] One paper “Deep high-resolution representation learning for visual recognition” accepted in IEEE TPAMI.
  • [Nov. 2019] One paper “MobileFAN: transferring deep hidden representation for face alignment” accepted in Pattern Recognition.
  • [Nov. 2019] One paper “Patchy Image Structure Classification Using Multi-Orientation Region Transform” accepted in AAAI 2020.
  • [Apr. 2019] One paper “High-resolution representations for labeling pixels and regions” published in arXiv.
  • [Mar. 2018] I went to The University of Adelaide.
  • [Feb. 2018] I enrolled in Griffith University.

Contact

  • Email: y.zhao2@latrobe.edu.au
  • Address: La Trobe University, PS2 319, Department of Computer Science and Information Technology, Melbourne, VIC, 3086, Australia