Gozde Gunesli

I am a Research Fellow in the Tissue Image Analytics (TIA) Center at the University of Warwick. I completed my Ph.D. in Computer Science at the University of Warwick in 2025, supervised by Prof. Nasir Rajpoot and Dr. Shan Raza. My research focuses on developing machine learning, deep learning, and computer vision methods for Computational Pathology, with the goal of advancing cancer diagnosis and prognosis.

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Education

• PhD in Computer Science, University of Warwick, UK (2021–2025)

  Dissertation: "Machine Learning Methods for Problems in Computational Pathology"

• MSc in Computer Science, Bilkent University (2017-2019)
• BSc in Computer Engineering, Bilkent University (2013-2017)

Honours and Awards

• Early Career Fellowship Award, Institute of Advanced Study (IAS), University of Warwick (2025–26) - a funded and competitive fellowship supporting independent, interdisciplinary research.
• Fully funded studentship for PhD (GlaxoSmithKline)
• Fully funded studentship for MSc (BilkentUniversity)
• Comprehensive Scholarship for BSc (BilkentUniversity)

Publications

• Gunesli, G. N., Dawood, M., Young, L. S., Minhas, F., Raza, S. E. A., & Rajpoot, N. M. (2025). Star-Motifs: Revealing Single-Cell Spatiotypes from Routine Histology Using Star-Convex Neighborhoods. bioRxiv, 2025-11.
• Wang, R., Gunesli, G. N., Skingen, V. E., Valen, K. A. F., Lyng, H., Young, L. S., & Rajpoot, N. (2025). Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histology images. npj Precision Oncology, 9(1), 11.
• Al-Rubaian, A., Gunesli, G. N., Althakfi, W. A., Azam, A., Snead, D., Rajpoot, N. M., & Raza, S. E. A. (2025). CellOMaps: A compact representation for robust classification of lung adenocarcinoma growth patterns. Computers in Biology and Medicine, 192, 110127.
• Al-Rubaian, A., Gunesli, G. N., Althakfi, W. A., Azam, A., Rajpoot, N., & Raza, S. E. A. (2024, May). Cell Maps Representation for Lung Adenocarcinoma Growth Patterns Classification in Whole Slide Images. In 2024 IEEE ISBI (pp. 1–5). IEEE.
• Gunesli, G. N., Bilal, M., Raza, S. E. A., & Rajpoot, N. M. (2023). A Federated Learning Approach to Tumor Detection in Colon Histology Images. Journal of Medical Systems, 47(1), 99.
• Gunesli, G. N., Jewsbury, R., Raza, S. E. A., & Rajpoot, N. M. (2022). Morph-Net: End-to-End Prediction of Nuclear Morphological Features from Histology Images. In International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis (pp. 136-144). Cham: Springer Nature Switzerland.
• Gunesli, G. N., Sokmensuer, C., & Gunduz-Demir, C. (2020). AttentionBoost: Learning what to attend for gland segmentation in histopathological images by boosting fully convolutional networks. IEEE Transactions on Medical Imaging, 39(12), 4262-4273.
• Koyuncu, C. F., Gunesli, G. N., Cetin-Atalay, R., & Gunduz-Demir, C. (2020). DeepDistance: a multi-task deep regression model for cell detection in inverted microscopy images. Medical Image Analysis, 63, 101720.
• Gunesli, G. N. (2019). Boosting fully convolutional networks for gland instance segmentation in histopathological images (MSc Dissertation, Bilkent University, Turkey).

Teaching Experience

• Senior Graduate Teaching Assistant, University of Warwick (2021 - 2025)

  • CS349 Data Mining (23/24)

  • CS430/CS910 Foundations of Data Analytics (21/22)

  • CS126 Design of Information Structures (20/21, 21/22, 22/23)

  • CS324 Computer Graphics (22/23, 23/24)

• Teaching Assistant, Bilkent University (2017-2019) 
  • CS201 Fundamental Structures of Computer Science I (2017-2019) 
  • CS102 Algorithms and Programming II (Fall 2019):
  • GE301 Science Technology and Society (Spring 2019)​

• Undergraduate Teaching Assistant, Bilkent University (2013-2016) 
  • CS224 Computer Organization (Fall 2014 – Spring 2016 )
  • CS101 Algorithms and Programming I​ ​(Spring 2014)