Mansoor Ali

Ph.D. candidate
School of Engineering and Sciences, Tecnologico de Monterrey, Mexico
Research stay at School of Computer Science, University of Leeds, UK

Email: mansoor.ali@tec.mx, ali.mansoor2024@gmail.com

Short-Bio

I am a 4th year PhD candidate at the School of Engineering and Sciences, Tecnologico de Monterrey, Mexico, having done my research stay at School of Computer Sciences, University of Leeds, UK. My research work is jointly advised by Dr. Gilberto Ochoa Ruiz and Dr. Sharib Ali. Before joining CV-INSIDE and AIMS Lab, I was working at Department of Electronic Engineering, Mehran University of Engineering and Tecnology, Jamshoro, Pakistan as an Assistant Professor.

My research interests lie at the intersection of computer vision and machine learning. Specifically, I work on medical and endoscopic image and video analysis. I have been working on developing deep learning models for image-guided interventions and robust models under distribution shifts. I have experience in working on diverse set of deep learning supervision methods such as fully supervised, semi-supervised and self-supervised methods and on all kinds of tasks including object classification, detection, localization, and scene segmentation, and depth estimation.

News

[06/2025] I was invited to teach Digital image processing course at the Universidad de Panamericana, Campus Aguascalientes as part of an awesome International Summer program.
[05/2025] One paper accepted at Medical Image Understanding and Analysis (MIUA'25) at University of Leeds, UK.
[08/2024] One paper accepted at Mexican International Conference on Artificial Intelligence (MICAI'24) at Puebla, Mexico.
[07/2024] One paper accepted at Cancer Prevention, detection and Prevention (CaPTion) Workshop at MICCAI'24 at MICCAI'24. Marrakech, Morocco.
[06/2024] Wao.... granted MICCAI travel and registration grant by MICCAI society to attend the conference at Marrakech, Morocco.
[07/2024] One paper accepted at Machine Learning for Medical Imaging Workshop (MLMI) at MICCAI'24, Marrakech, Morocco.
[04/2024] One paper accepted at Computer-based Medical Systems Conference at Tecnologico de Monterrey, Campus, Guadalajara.
[08/2023] Started a six-month Visiting Researcher position at AIMS Lab at the University of Leeds, UK.
[08/2023] Received full registration grant for attending International Conference on Computer Vision (ICCV'23) at Paris, France.
[05/2023] One paper accepted at LXAI Computer Vision workshop at CVPR'23 Vancouver, Canada.
[04/2023] Attened and volunteered at International Symposium on Biomedical Imaging (ISBI'23) at Cartagena, Colombia.
[12/2022] Wao!!! Excellent Finish to 2022. My Ph.D project won seed funding from Research Development Fund (RDF).
[12/2022] 1st Ph.D paper gets published in TCIV.
[11/2022] Won first prize among all postgrad programs in a research competetion 'My investigation' @ TEC.
[10/2022] Attended MICAI 20222 in-person at Monetrrey, Mexico.
[10/2022] Participated in Doctoral consortium at LatinX in AI @ ECCV 2022.
[09/2022] Became MICCAI student society member for the first time.
[09/2022] Attended MICCAI-2022 in-person at Singapore, presented paper and two posters.
[08/2022] A paper got acceptance at MICAI 2022.
[08/2022] A paper got acceptance at AE-CAI Workshop @ MICCAI 2022.
[07/2022] Attended Summer School at UCL. Worked on a project Augmented Reality for Surgery under Dr. Mat Carlson and his team.
[06/2022] A paper got acceptance at CaPTion Workshop @ MICCAI 2022.
[06/2022] Successfully defended my Ph.D research proposal.
[08/2021] Started my Ph.D at Tec de Monterrey!

Selected Publications [Google Scholar]

(* Co-first auhtor; † indicates corresponding authorship)

	PolypDINO: Adapting DINOv2 for domain generalized polyp segmentation. Mansoor Ali Teevno†, Raneem Toman, Gilberto Ochoa Ruiz, Sharib Ali. Medical Image Understanding and Analysis (MIUA-2025) Conference at the University of Leeds, UK. [Code][Paper- soon] [Slides]
	Tackling domain generalization for out-of-distribution endoscopic imaging. Mansoor Ali Teevno†, Gilberto Ochoa Ruiz, Sharib Ali. Machine Learning for Medical Imaging (MLMI) Workshop at MICCAI 2024. [Preprint][Paper]
	Domain Generalization for Endoscopic Image Segmentation by Disentangling Style-Content Information and SuperPixel Consistency. Mansoor Ali Teevno†, Rafael Martinez-Garcia-Peña, Gilberto Ochoa Ruiz, Sharib Ali. 2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS), 2024. [Preprint][Paper]
	SUPRA: Superpixel Guided Loss for Improved Multi-Modal Segmentation in Endoscopy. Rafael Martinez-Garcia-Peña, Mansoor Ali Teevno†, Gilberto Ochoa Ruiz, Sharib Ali. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (CVPRW), 2023. [Paper]
	A semi-supervised Teacher-Student framework for surgical tool detection and localization. Mansoor Ali Teevno†, Gilberto Ochoa Ruiz, Sharib Ali. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022. [Paper][Code]
	A comprehensive survey on recent deep learning-based methods applied to surgical data. Mansoor Ali Teevno†, Rafael Martinez-Garcia-Peña, Gilberto Ochoa Ruiz, Sharib Ali. [Preprint]
	Knowledge distillation with a class-aware loss for endoscopic disease detection. Mansoor Ali Teevno†, Gilberto Ochoa Ruiz, Sharib Ali. MICCAI Workshop on Cancer Prevention Through Early Detection (CaPTion), 2022. [Preprint][Paper]
	Object detection and segmentation by composition of fast fuzzy C-mean clustering based maps. Mehmood Nawaz, Rizwan Qureshi, Mansoor Ali Teevno†, Ali Raza Shahid . Journal of Ambient Intelligence and Humanized Computing (AI&HC), 2022. [Paper]

Academic Services

Teaching:

Digital Image Processing - Universidad de Panamericana, Mexico.

Reviewer:

Journal of Biomedical and Health Informatics (JBHI), Computers in Biology and Medicine (CIBM), Clinical Breast Cancer
Medical Image Understanding and Analysis (MIUA-25)
International Symposium on Biomedical Imaging (ISBI'23, 24, 25)
MICCAI Workshop on Cancer Prevention Through Early Detection (CaPTion'23-24)
Mexican International Conference on Artificial Intelligence (MICAI'23-24)