Associate Professor Mahsa Baktashmotlagh
Associate Professor

Mahsa Baktashmotlagh

Email: 
Phone: 
+61 7 336 57597

Background

Mahsa Baktashmotlagh is currently an Associate Professor and an ARC Future Fellow at UQ, developing machine learning techniques applied in: Visual data analysis, Biomedical data (Antibacterial activity prediction), and Cyber Security.

Availability

Associate Professor Mahsa Baktashmotlagh is:
Available for supervision

Qualifications

  • Doctor of Philosophy, The University of Queensland

Search Professor Mahsa Baktashmotlagh’s works on UQ eSpace

80 works between 2011 and 2026
All (80) Journal Article (10) Other Outputs (2) Conference Publication (66) Book Chapter (2)

21 - 40 of 80 works

2023

Conference Publication

How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability

Wang, Zijian, Luo, Yadan, Zheng, Liang, Huang, Zi and Baktashmotlagh, Mahsa (2023). How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00511

How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability

2023

Conference Publication

Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters

Michalkiewicz, Mateusz, Faraki, Masoud, Yu, Xiang, Chandraker, Manmohan and Baktashmotlagh, Mahsa (2023). Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00568

Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters

2023

Conference Publication

KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection

Luo, Yadan, Chen, Zhuoxiao, Fang, Zhen, Zhang, Zheng, Baktashmotlagh, Mahsa and Huang, Zi (2023). KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2021. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.01676

KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection

2023

Conference Publication

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

Chen, Zhuoxiao, Luo, Yadan, Wang, Zheng, Baktashmotlagh, Mahsa and Huang, Zi (2023). Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00344

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

2023

Journal Article

DI-NIDS: domain invariant network intrusion detection system

Layeghy, Siamak, Baktashmotlagh, Mahsa and Portmann, Marius (2023). DI-NIDS: domain invariant network intrusion detection system. Knowledge-Based Systems, 273 110626, 110626. doi: 10.1016/j.knosys.2023.110626

DI-NIDS: domain invariant network intrusion detection system

2023

Conference Publication

Exploring active 3D object detection from a generalization perspective

Luo, Yadan, Chen, Zhuoxiao, Wang, Zijian, Yu, Xin, Huang, Zi and Baktashmotlagh, Mahsa (2023). Exploring active 3D object detection from a generalization perspective. 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, 1 - 5 May 2023. New York, NY, United States: Cornell Tech. doi: 10.48550/arXiv.2301.09249

Exploring active 3D object detection from a generalization perspective

Featured

2023

Journal Article

Source-free progressive graph learning for open-set domain adaptation

Luo, Yadan, Wang, Zijian, Chen, Zhuoxiao, Huang, Zi and Baktashmotlagh, Mahsa (2023). Source-free progressive graph learning for open-set domain adaptation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (9), 1-16. doi: 10.1109/tpami.2023.3270288

Source-free progressive graph learning for open-set domain adaptation

2023

Journal Article

Interpretable signed link prediction with signed infomax hyperbolic graph

Luo, Yadan, Huang, Zi, Chen, Hongxu, Yang, Yang, Yin, Hongzhi and Baktashmotlagh, Mahsa (2023). Interpretable signed link prediction with signed infomax hyperbolic graph. IEEE Transactions on Knowledge and Data Engineering, 35 (4), 3991-4002. doi: 10.1109/TKDE.2021.3139035

Interpretable signed link prediction with signed infomax hyperbolic graph

2023

Conference Publication

Convolutional Persistence as a Remedy to Neural Model Analysis

Khramtsova, Ekaterina, Zuccon, Guido, Wang, Xi and Baktashmotlagh, Mahsa (2023). Convolutional Persistence as a Remedy to Neural Model Analysis. International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 25-27 April 2023. Brookline, MA United States: ML Research Press.

Convolutional Persistence as a Remedy to Neural Model Analysis

2023

Conference Publication

FFM: injecting out-of-domain knowledge via factorized frequency modification

Wang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2023). FFM: injecting out-of-domain knowledge via factorized frequency modification. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00412

FFM: injecting out-of-domain knowledge via factorized frequency modification

2023

Conference Publication

Center-aware adversarial augmentation for single domain generalization

Chen, Tianle, Baktashmotlagh, Mahsa, Wang, Zijian and Salzmann, Mathieu (2023). Center-aware adversarial augmentation for single domain generalization. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 2-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00414

Center-aware adversarial augmentation for single domain generalization

2022

Conference Publication

Contrastive Class-aware Adaptation for Domain Generalization

Chen, Tianle, Baktashmotlagh, Mahsa and Salzmann, Mathieu (2022). Contrastive Class-aware Adaptation for Domain Generalization. 2022 26th International Conference on Pattern Recognition (ICPR), Montreal, QC Canada, 21-25 August 2022. Piscataway, NJ United States: IEEE. doi: 10.1109/icpr56361.2022.9956262

Contrastive Class-aware Adaptation for Domain Generalization

2022

Conference Publication

Rethinking persistent homology for visual recognition

Khramtsova, Ekaterina, Zuccon, Guido, Wang, Xi and Baktashmotlagh, Mahsa (2022). Rethinking persistent homology for visual recognition. Topological, Algebraic and Geometric Learning Workshops, Online, 25-22 July 2022. Brookline, MA United States: ML Research Press.

Rethinking persistent homology for visual recognition

2022

Conference Publication

Modular construction planning using graph neural network heuristic search

Hawkins, Philip, Maire, Frederic, Denman, Simon and Baktashmotlagh, Mahsa (2022). Modular construction planning using graph neural network heuristic search. 34th Australasian Joint Conference on Artificial Intelligence (AI), Electr Network, 2-4 February 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-97546-3_19

Modular construction planning using graph neural network heuristic search

2022

Conference Publication

Learning to generate the unknowns as a remedy to the open-set domain shift

Baktashmotlagh, Mahsa, Chen, Tianle and Salzmann, Mathieu (2022). Learning to generate the unknowns as a remedy to the open-set domain shift. 22nd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-8 January 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV51458.2022.00379

Learning to generate the unknowns as a remedy to the open-set domain shift

2022

Conference Publication

Master of all: simultaneous generalization of urban-scene segmentation to all adverse weather conditions

Reddy, Nikhil, Singhal, Abhinav, Kumar, Abhishek, Baktashmotlagh, Mahsa and Arora, Chetan (2022). Master of all: simultaneous generalization of urban-scene segmentation to all adverse weather conditions. Computer Vision – ECCV 2022, Tel Aviv, Israel, 23-27 October 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-19842-7_4

Master of all: simultaneous generalization of urban-scene segmentation to all adverse weather conditions

2021

Conference Publication

Conditional Extreme Value Theory for Open Set Video Domain Adaptation

Chen, Zhuoxiao, Luo, Yadan and Baktashmotlagh, Mahsa (2021). Conditional Extreme Value Theory for Open Set Video Domain Adaptation. MMAsia '21: ACM Multimedia Asia, Gold Coast, QLD Australia, 1 - 3 December 2021. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3469877.3490600

Conditional Extreme Value Theory for Open Set Video Domain Adaptation

2021

Conference Publication

Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings

Moskvyak, Olga, Maire, Frederic, Dayoub, Feras, Armstrong, Asia O. and Baktashmotlagh, Mahsa (2021). Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. 2021 Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, QLD Australia, 29 November 2021 - 1 December 2021. Piscataway, NJ United States: IEEE. doi: 10.1109/dicta52665.2021.9647359

Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings

2021

Conference Publication

Semi-supervised keypoint localization

Moskvyak, Olga, Maire, Frederic, Dayoub, Feras and Baktashmotlagh, Mahsa (2021). Semi-supervised keypoint localization. 9th International Conference on Learning Representations (ICLR) 2021, Virtual, 3-7 May 2021. Appleton, WI United States: International Conference on Learning Representations. doi: 10.48550/arXiv.2101.07988

Semi-supervised keypoint localization

2021

Conference Publication

Learning to diversify for single domain generalization

Wang, Zijian, Luo, Yadan, Qiu, Ruihong, Huang, Zi and Baktashmotlagh, Mahsa (2021). Learning to diversify for single domain generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCV48922.2021.00087

Learning to diversify for single domain generalization

Current funding

  • 2024 - 2028
    Rethinking Topological Persistence
    ARC Future Fellowships
    Open grant
  • 2023 - 2027
    Analytics for the Australian Grains Industry (AAGI)
    Grains Research & Development Corporation
    Open grant
  • 2021 - 2027
    Reducing Simulation-to-Reality Gap as Remedy to Learning Under Uncertainty
    Facebook RFP Statistics for Improving Insights Models and Decisions
    Open grant

Past funding

  • 2019 - 2022
    Collaborative Lab of Health Informatics with Neusoft
    Neusoft Research of Intelligent Healthcare Technology, Co Ltd
    Open grant

Availability

Associate Professor Mahsa Baktashmotlagh is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose a supervisor.

Available projects

  • Enhancing Efficiency of Foundational Models

    Explore techniques such as model sparsity, knowledge distillation, and task-specific adaptation to reduce computational overhead without sacrificing performance.

Supervision history

Current supervision

Completed supervision

Enquiries

For media enquiries about Associate Professor Mahsa Baktashmotlagh's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au