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Talha Qaiser

I have completed my Ph.D. (April 2019) under the supervision of Prof Nasir Rajpoot at the Tissue Image Analytics Lab, Department of Computer Science, University of Warwick.

My interest involves developing robust applications for computer-assisted grading of cancer by using deep learning and statistical machine learning algorithms.


July 2015 - April 2019, PhD in Computer Science
Department of Computer Science, The University of Warwick, UK
Research: Topology and Attention in Computational Pathology

2007-2011, BS in Computer Engineering
Department of Electrical Engineering, COMSATS Institute of Information Technology, Pakistan
Research: A Computer Vision Based Wheelchair for Handicaps
Secured Campus and Institute Silver Medals

Selected Publications

  • Qaiser, Talha, and Nasir M. Rajpoot. "Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring." IEEE Transactions on Medical Imaging (2019).
  • Qaiser, Talha, Yee-Wah Tsang, Daiki Taniyama, Naoya Sakamoto, Kazuaki Nakane, David Epstein, and Nasir Rajpoot. "Fast and accurate tumor segmentation of histology images using persistent homology and deep convolutional features." Medical Image Analysis (2019).
  • Qaiser, Talha, Abhik Mukherjee, Chaitanya Reddy Pb, Sai D. Munugoti, Vamsi Tallam, Tomi Pitkäaho, Taina Lehtimäki et al. "HER 2 challenge contest: a detailed assessment of automated HER 2 scoring algorithms in whole slide images of breast cancer tissues." Histopathology 72, no. 2 (2018): 227-238.
  • Veta, Mitko, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr,..., Talha Qaiser, ....., et al. "Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge." Medical Image Analysis 54 (2019): 111-121.
  • Bejnordi, Babak Ehteshami, Mitko Veta, Paul Johannes van Diest, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen AWM van der Laak ...., Talha Qaiser, ...., et al. "Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer." Jama 318, no. 22 (2017): 2199-2210.
  • Xue, Mingzhan, Alaa Shafie, Talha Qaiser, Nasir M. Rajpoot, Gregory Kaltsas, Sean James, Kishore Gopalakrishnan et al. "Glyoxalase 1 copy number variation in patients with well differentiated gastro-entero-pancreatic neuroendocrine tumours (GEP-NET)." Oncotarget 8, no. 44 (2017): 76961.
  • Vu, Quoc Dang, Simon Graham, Minh Nguyen Nhat To, Muhammad Shaban, Talha Qaiser, Navid Alemi Koohbanani, Syed Ali Khurram et al. "Methods for segmentation and classification of digital microscopy tissue images." Frontiers in Bioengineering and Biotechnology, 2019.
  • Qaiser, Talha, Yee-Wah Tsang, David Epstein, and Nasir Rajpoot. "Tumor Segmentation in Whole Slide Images Using Persistent Homology and Deep Convolutional Features." In Annual Conference on Medical Image Understanding and Analysis, pp. 320-329. Springer, Cham, 2017.
  • Qaiser, Talha, Korsuk Sirinukunwattana, Kazuaki Nakane, Yee-Wah Tsang, David Epstein, and Nasir Rajpoot. "Persistent Homology for Fast Tumor Segmentation in Whole Slide Histology Images." Procedia Computer Science 90 (2016): 119-124. [link] best_paper_award
  • Qaiser, Talha, K. Sirinukunwattana, and N. Rajpoot. "An Integrated Environment For Tissue Morphometrics And Analytics." Diagnostic Pathology 1, no. 8 (2016). [link]

Academic Awards and Experiences

  • Fully Funded Studentship: For Postgraduate Studies by University Hospitals Coventry and Warwickshire.
  • Won Best Paper Award: At the 20th Medical Image Understanding and Analysis Conference.
  • Silver Medalist: Awarded Campus and Institute Silver Medals in BS Computer Engineering.
  • Azure Research: Co-Investigator on Azure-Warwick Pilot Study on Pathology Image Analytics in the Cloud.
  • Organized the “Her2 Scoring Contest” for breast histology Images at the “Pathology Society of Great Britain and Ireland” in 2016.
  • Invited talks at the ECDP-2019, IATS-2018, MIUA-2017, MIUA-2016, ECDP-2016, BBACGR-2015.
  • Organized the “Intel Workshop-Accelerate Your Code” that brings interactive training for researchers and programmers with an appetite to make their code run faster.
  • Developed an interactive framework for tissue morphometrics that could assist the pathologist to perform analytics and produce more accurate means to assess cancer.
  • Program committee member for IJCAI-ECAI-2018 and MICCAI-COMPAY-2018.


  • Virtual Slide Marker (homepage) (demo)
  • HER2 Scoring Contest for Breast Histology Images
  • Tumour-Collagen Proximity Analysis for Predicting Overall Survival in DLBCL
  • Persistent Homology for Fast Tumor Segmentation in Whole Slide Images
  • Automated Immunohistochemical Scoring of HER2 cases
  • Tumor Segmentation in Breast Metastasis Histology Images


  • Research Assitant at Qatar University (Nov 2014 - May 2015)
  • Computer Vision Developer (Full-time freelancer) at Upwork)


For more details about private BitBucket repositories.

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Talha Qaiser

PhD Student, Tissue Image Analytics Lab, Department of Computer Science, University of Warwick

t dot qaiser at warwick dot ac dot uk

LinkedIn linkedin
GitHub github

Google Scholar googleScholar

ResearchGate RG

Upwork upwork