Jiaqi Lv

About me

Personal Info

UK Research and Innovation (UKRI) - Engineering and Physical Sciences Research Council (EPSRC) Doctoral Scholarship.

Under the supervision of Dr Shan Raza.

I graduated with an First-Class Masters of Engineering (MEng) degree in Computer Science from the University of Warwick in 2023.

Email: jiaqi.lv@warwick.ac.uk

Office: CS3.02, Department of Computer Science

Research Interests

I'm very interested in the development and application of deep learning models for the analysis of the tumour micro-environment.
Automatic discovery and validation of biomarkers from pathology data for cancer treatment selection and patient stratification.

Research Projects

Some of my projects:

Automatic segmentation of blood vessels from H&E-stained whole-slide images using deep learning.
Automated Assessment of Tumour-Infiltrating Lymphocytes from H&E-stained histopathology Whole-Slide Images.
Automatic segmentation of tissue structures from H&E-stained whole-slide images using deep learning.

International Biomedical Grand Challenges:

MONKEY Grand Challenge:Link opens in a new window Lymphocytes and Monocytes Detection from PAS-Stained Whole-Slide Images. Led the TIAKong team to achieve 1st place in overall detection and 2nd place in subtype classification.
PUMA Grand Challenge:Link opens in a new window Tissue segmentation and Cell Detection from H&E Images of Advanced Melanoma. Led the TIAKong team to achieve 1st place in Track 1 and joint 1st place in Track 2.
2025 MIDOG Grand Challenge: Mitosis Detection from H&E Images. Co-Led the TIAKong team to achieve 1st place in mitosis detection and 2nd place in atypical mitotic figures classification.
Chimera Grand Challenge: Contributed to TIA-Pegasus team to achieve 1st place in track 1 prostate cancer biochemical recurrence prediction.

Other Interests

I am also interesting in varies software and web applications development.
I'm also very passionated about the application of AI models to solve real-world problems.
I have been contributing to the TIAToolBox, an OpenSource computational pathology toolbox with more than 300k downloads.

Publications

J. Lv, S. S. Antonowicz and S. E. A. Raza, "Deep Learning Based Segmentation of Blood Vessels from H&E Stained Oesophageal Adenocarcinoma Whole-Slide Images", 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), Houston, TX, USA, 2025, pp. 1-5, doi: 10.1109/ISBI60581.2025.10980962.
Lv, J., Zhu, Y., Tenorio, C.G.C., Chohan, B.S., Eastwood, M., Raza, S.E.A. (2026). "Leveraging Pathology Foundation Models for Panoptic Segmentation of Melanoma in H&E Images", Medical Image Understanding and Analysis. MIUA 2025. Lecture Notes in Computer Science, vol 15916. Springer, Cham. https://doi.org/10.1007/978-3-031-98688-8_5
Esha Sadia Nasir, Jiaqi Lv, Mostafa Jahanifar, Shan E Ahmed Raza, "MitoDetect++: A Domain-Robust Pipeline for Mitosis Detection and Atypical Subtyping", https://arxiv.org/abs/2509.02586
Noorul Wahab, Ethar Alzaid, Jiaqi Lv, Fayyaz Minhas, Adam Shephard, Shan E Ahmed Raza, "ModalSurv: Investigating opportunities and limitations of multimodal deep survival learning in prostate and bladder cancer", https://arxiv.org/abs/2509.05037
Jiaqi Lv, Esha Sadia Nasir, Kesi Xu, Mostafa Jahanifar, Brinder Singh Chohan, Behnaz Elhaminia, Shan E Ahmed Raza, "KongNet: A Multi-headed Deep Learning Model for Detection and Classification of Nuclei in Histopathology Images", Medical Image Analysis, Volume 114, https://doi.org/10.1016/j.media.2026.104233.
Mark Schuiveling, Hong Liu, Daniel Eek, et al., "Associations between spatial distribution of immune cell subsets and clinical outcomes in patients with advanced melanoma treated with immune checkpoint inhibitors: results from the PUMA challenge", https://www.medrxiv.org/content/10.64898/2026.03.09.26347935v1
Behnaz Elhaminia, Catherine King, Jiaqi Lv, Lorraine Harper, Paul Moss, Owen Cain, Dimitrios Chanouzas, Shan E Ahmed Raza, "A deep learning framework for glomeruli segmentation with boundary attention", https://arxiv.org/abs/2604.14263.
M Aubreville, J Ammeling, S Banerjee, et al., "Mitosis Detection in the Wild: Multi-Tumor and Context-Aware Generalization in the MIDOG 2025 Challenge", https://arxiv.org/abs/2606.07368.
Esha Sadia Nasir, Jiaqi Lv, Mostafa Jahanifar, Shan E Ahmed Raza, 'Efficient Classification of Atypical vs. Normal Mitotic Figures Using LoRA-Fine-Tuned Foundation Models", MICCAI 2025. Lecture Notes in Computer Science, vol 16519. Springer, Cham. https://doi.org/10.1007/978-3-032-25180-0_6.

Teaching Assistant

2022-2023:

CS118 Programming for Computer Scientists
CS126 Design of Information Structures

2023-2024:

CS262 Logic and Verification
CS435/CS915 Advanced Computer Security
CS424/CS904 Computational Biology

2024-2025:

CS435/CS915 Advanced Computer Security
CS324 Computer Graphics
CS424/CS904: Computational Biology

2025-2026:

CS435/CS915 Advanced Computer Security
CS424/CS904 Computational Biology