Overview
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
Works
Search Professor Mahsa Baktashmotlagh’s works on UQ eSpace
2024
Book Chapter
Source-Free Domain-Invariant Performance Prediction
Khramtsova, Ekaterina, Baktashmotlagh, Mahsa, Zuccon, Guido, Wang, Xi and Salzmann, Mathieu (2024). Source-Free Domain-Invariant Performance Prediction. Lecture Notes in Computer Science. (pp. 99-116) Cham: Springer Nature Switzerland. doi: 10.1007/978-3-031-72989-8_6
2024
Conference Publication
Embark on DenseQuest: a system for selecting the best dense retriever for a custom collection
Khramtsova, Ekaterina, Leelanupab, Teerapong, Zhuang, Shengyao, Baktashmotlagh, Mahsa and Zuccon, Guido (2024). Embark on DenseQuest: a system for selecting the best dense retriever for a custom collection. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657674
2024
Conference Publication
Leveraging LLMs for unsupervised dense retriever ranking
Khramtsova, Ekaterina, Zhuang, Shengyao, Baktashmotlagh, Mahsa and Zuccon, Guido (2024). Leveraging LLMs for unsupervised dense retriever ranking. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657798
2024
Conference Publication
Domain-aware knowledge distillation for continual model generalization
Reddy, Nikhil, Baktashmotlagh, Mahsa and Arora, Chetan (2024). Domain-aware knowledge distillation for continual model generalization. 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-8 January 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/wacv57701.2024.00075
2023
Conference Publication
Selecting which dense retriever to use for zero-shot search
Khramtsova, Ekaterina, Zhuang, Shengyao, Baktashmotlagh, Mahsa, Wang, Xi and Zuccon, Guido (2023). Selecting which dense retriever to use for zero-shot search. SIGIR-AP 2023 - Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, Beijing, China, 26-28 November 2023. New York, United States: Association for Computing Machinery. doi: 10.1145/3624918.3625330
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
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
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
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
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
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
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
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
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.
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
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
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
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.
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
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
Supervision
Availability
- Associate Professor Mahsa Baktashmotlagh is:
- Available for supervision
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Supervision history
Current supervision
-
Doctor Philosophy
Exploring Facets of Model Generalizability on Out-of-Distribution Data
Principal Advisor
Other advisors: Professor Guido Zuccon
-
Doctor Philosophy
Enhancing Robustness and Generalizability in Computational Models
Principal Advisor
Other advisors: Dr Xin Yu
-
Doctor Philosophy
Revisiting Assumptions and Evaluation Metrics in Domain Generalization
Principal Advisor
-
Doctor Philosophy
Generalizing Implicit Representations for Robotics Manipulation of Articulated Objects
Principal Advisor
Other advisors: Dr Peyman Moghadam
-
Doctor Philosophy
Enhancing Safety and Reliability of machine learning models using lifelong multi-modal learning
Principal Advisor
Other advisors: Professor Helen Huang, Dr Yadan Luo
-
Doctor Philosophy
Parametric Deep Neural Networks for Computer Vision Problems
Principal Advisor
-
Doctor Philosophy
Parametric Deep Neural Networks for Computer Vision Problems
Principal Advisor
-
Doctor Philosophy
Parametric Deep Neural Networks for Computer Vision Problems
Principal Advisor
-
Doctor Philosophy
Enhancing Plant Phenotyping Accuracy through Analysing Video Data
Principal Advisor
Other advisors: Professor Bhagirath Chauhan, Dr Yadan Luo
-
Doctor Philosophy
Unsupervised Domain Adaptation on 3D Object Detection and Segmentation
Associate Advisor
Other advisors: Professor Helen Huang, Dr Yadan Luo
-
-
Doctor Philosophy
Towards Analysis of Contextual Melanoma Indicators and Identification of Total-Body Ugly Duckling Lesions with Deep Neural Networks
Associate Advisor
Other advisors: Dr Brigid Betz-Stablein, Dr Shakes Chandra
-
Doctor Philosophy
The role of duality in machine learning and computer vision.
Associate Advisor
Other advisors: Professor Brian Lovell
-
Doctor Philosophy
Automatic Retinal Health Monitoring through Multi-modal Medical Imaging
Associate Advisor
Other advisors: Dr Xin Yu
-
Completed supervision
-
2024
Doctor Philosophy
Exploring Facets of Model Generalizability on Out-of-Distribution Data
Principal Advisor
Other advisors: Professor Guido Zuccon
-
2023
Doctor Philosophy
Monocular 3D Reconstruction: Shape Representation, Scalability and Generalization.
Principal Advisor
Other advisors: Dr Yadan Luo
-
2022
Doctor Philosophy
On Encoding Causality for Natural Language Understanding
Principal Advisor
Other advisors: Professor Xue Li
-
2024
Doctor Philosophy
Towards Analysis of Contextual Melanoma Indicators and Identification of Total-Body Ugly Duckling Lesions with Deep Neural Networks
Associate Advisor
Other advisors: Dr Brigid Betz-Stablein, Dr Shakes Chandra
-
2023
Doctor Philosophy
On improving vision model transferability to address domain shift in an open world
Associate Advisor
Other advisors: Professor Helen Huang
-
2021
Doctor Philosophy
Visual Learning from Imperfect Data via Inductive Bias Modelling
Associate Advisor
Other advisors: Professor Helen Huang
Media
Enquiries
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