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Computer Science

Dr Yanda Meng

Dr Yanda Meng

Lecturer
Computer Science

I am a Lecturer (Assistant Professor) at the University of Exeter, Computer Science Department. I am now also an Honorary Lecturer at the Cardiovascular & Metabolic Medicine Department, University of Liverpool.

I did my PhD with Prof Yalin Zheng and Prof Xiaowei Huang at the Eye and Vision Science Department at the University of Liverpool, with a short-term research visit to Prof Jens Rittscher's group at the Biomedical Engineering Institute, University of Oxford. Then, I did a post-doc with Prof Yalin Zheng and Dr Nicholas AV Beare in Liverpool on a Wellcome Trust-funded AI-assisted OCT device for cerebral malaria disease diagnosis and prognosis. I work closely with Dr Alam Uazman on CCM image-based diabetes neuropathy diagnosis and Prof Gregory Lip on cardiovascular diseases early detection.

 

 

I am looking for self-motivated Ph. D. students. If you are interested in working with me, please email me about your background (CV, transcripts, etc..)

Some useful links: (1) EPSRC PhD Studentships; (2) Centre for Doctoral Training in Enviornmental Intelligence; (3) China Scholarship Council and University of Exeter PhD Scholarships

 

 

News:

  • Dec 2024, One paper, ‘Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis’, is accepted by the 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025) project link.
  • Dec 2024, Acceptance of the Royal Society International Exchanges Grant with NSFC as PI (£12,000 external). link
  • Nov 2024, One paper, 'Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers?' is accepted by the 31st International Conference on Computational Linguistics (COLING 2025)
  • Nov 2024, One paper, 'Dynamic Semantic-based Spatial-Temporal Graph Convolution Network for Skeleton-based Human Action Recognition' is accepted by the IEEE Transactions on Image Processing (IEEE-TIP)
  • Nov 2024, One paper, 'Randomness-restricted Diffusion Model for Ocular Surface Structure Segmentation,' is accepted by the IEEE Transactions on Medical Imaging (IEEE TMI).
  • I am recognized as an IEEE TMI Distinguished Reviewer Bronze Level 2023 – 2024.
  • Oct 2024, One paper, 'Clinical Insight-Augmented Multi-View Learning for Alzheimer's Detection in Retinal OCTA Images,' is accepted by the IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2024).
  • Sep 2024, One paper, 'MR2 -Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance', is accepted by the IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI).
  • July 2024, One industry-funded 3-year PhD studentship at the UK tuition fee and UKRI stipend rate is available in my group. The application deadline is 25th Aug 2024. link.
  • July 2024, One paper, ‘Artificial intelligence – based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes - The Silesia Diabetes Heart Study’ is accepted by Cardiovascular Diabetology.
  • July 2024, Acceptance of a UK-rate full PhD studentship as PI (£45,000 external), funded by Liverpool Heart and Chest Hospital NHS Trust Foundation and Liverpool Centre for Cardiovascular Science; the student is expected to start in January 2025.
  • June 2024, One paper, ‘AI-Driven Generalised Polynomial Transformation Models for Unsupervised Fundus Image Registration,’ is accepted by Frontiers in Medicine, section Ophthalmology.
  • June 2024, Two papers were accepted by MICCAI2024, ‘CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting’ and ‘Multi-disease Detection in Retinal Images Guided by Disease Causal Estimation’.
  • May 2024, One paper, ‘Self-Guided Adversarial Network for Domain Adaptive Retinal Layer Segmentation,’ is accepted by IEEE Transactions on Instrumentation & Measurement (IEEE-TIM).
  • May 2024, Acceptance of 2024 SeedCorn Fund of Health Technologies@Exeter as PI (£2,500).
  • May 2024, One paper, ‘The impact of reasoning step length on large language models’, is accepted by ACL 2024 as Findings; congrats to Mingyu and Qinkai as their first-author publications!
  • April 2024, One industry-funded 3.5-year PhD studentship at the UK tuition fee and UKRI stipend rate is available in my group. The deadline to apply is 15th May 2024. link.
  • April 2024, One paper, ‘Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment’, is accepted by Medical Image Analysis.
  • April 2024, Acceptance of an international full PhD studentship as PI (£45,000 external), funded by Liverpool Centre for Cardiovascular Science. The student is expected to start in September 2024.

 

 

 

Publication (See my google scholar for more details):
I have published more than 40 papers in peer-reviewed journals and conferences and authored (first/corresponding) more than 20 publications at prestigious AI, Computer Vision, and Medical Image Analysis journals/conferences,
 
Selected publications (* means equal contribution, † means the corresponding author):
 
  • Yanda Meng et al. Multi-Granularity Learning of Explicit Geometric Constraint and Contrast for Label-Efficient Medical Image Segmentation and Differentiable Clinical Function Assessment. Medical Image Analysis.
  • Yanda Meng et al. Bilateral Adaptive Graph Convolutional Network on CT-based COVID-19 Diagnosis with Uncertainty-Aware Consensus-Assisted Multiple Instance Learning. Medical Image Analysis.
  • Yanda Meng et al. Dual Consistency Enabled Weakly and Semi-Supervised Optic Disc and Cup Segmentation with Dual Adaptive Graph Convolutional Networks. IEEE Transactions on Medical Imaging.
  • Yanda Meng et al. Graph-based Region and Boundary Aggregation for Biomedical Image Segmentation. IEEE Transactions on Medical Imaging.
  • Frank G Preston*, Yanda Meng*, et al. Artificial intelligence utilising corneal confocal microscopy for the diagnosis of peripheral neuropathy in diabetes mellitus and prediabetes. Diabetologia (front cover).
  • *Katarzyna Nabrdalik, *Krzysztof Irlik, *Yanda Meng, et al. Artificial intelligence – based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes - The Silesia Diabetes Heart Study. Cardiovascular Diabetology.
  • Yanda Meng et al. Transportation Object Counting with Graph-Based Adaptive Auxiliary Learning. IEEE Transactions on Intelligent Transportation System.
  • Yanda Meng et al. Artificial Intelligence Based Analysis of Corneal Confocal Microscopy Images for Diagnosing Peripheral Neurapathy: A Binary Classification Model. Journal of Clinical Medicine.
  • Alastair Patefield*, Yanda Meng*, et al. Deep-Learning using preoperative AS-OCT predicts graft detachmeng in DMEK. Translational Vision Science and Technology.
  • Jianyang Xie, Yanda Meng, et al. Dynamic Semantic-based Graph Convolution Network for Skeleton-based Human Action recognition. AAAI 2024.
  • Chengzhi Liu, ... , Yanda Meng, et al. Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis. AAAI 2025.
  • Qinkai Yu, .., Yanda Meng. ‘CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting’ MICCAI 2024
  • Yanda Meng, et al. Spatial Uncertainty-Aware Semi-Supervised Crowd Counting. ICCV 2021.
  • Yanda Meng, et al. Regression of Instance Boundary by Aggregated CNN and GCN. ECCV 2020.
  • Yanda Meng, et al. CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation. MICCAI 2020 (early accept).
  • Yanda Meng, et al. Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency. MICCAI 2022 (early accept).
  • Yanda Meng, et al. BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation. BMVC 2021 (oral).
  • Yanda Meng, et al. Weakly/Semi-supervised Left Ventricle Segmentation in 2D Echocardiography with Uncertain Region-aware Contrastive Learning. PRCV 2023.
  • Yanda Meng, et al. Diagnosis of Diabetic Neuropathy by Artificial Intelligence using Corneal Confocal Microscopy. EAsDEC 2022
 
 
 

 

 
 

 

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