Ahmed H. Shahin

Ahmed H. Shahin

PhD Student at University College London

University College London (UCL)

I am Ahmed, a PhD student in the Department of Computer Science at UCL. Under the joint supervision of David Barber at the UCL AI Centre and Daniel Alexander at the UCL Centre for Medical Image Computing (CMIC), my research focuses on the development of machine learning techniques for the diagnosis and prognosis of the Interstitial Lung Diseases from medical images and clinical data. My work is part of the Open Source Imaging Consortium (OSIC), an initiative aimed at promoting swift progress in the fight against respiratory diseases.

In March 2023, I completed a research internship with the Cardiovascular Imaging team at Siemens Healthineers in Princeton, USA, where I designed machine learning approaches to assist clinicians in the diagnosis and treatment of cardiovascular diseases.

Prior to joining UCL, I served as a senior machine learning engineer at Intixel, a Cairo-based start-up for AI in radiology. I also undertook a six-month research internship at Inception Institute of AI in Abu Dhabi. My research contributions have been published as first-author papers in prestigious conferences such as MICCAI, MIDL, RSNA, and ISBI. In addition, I have served as a reviewer for MICCAI, the International Journal of Computer Vision (IJCV), IEEE Access, and NILES'19, and am currently a program committee member for the Medical Imaging Meets NeurIPS and FAIR-MICCAI workshops.

Download my CV (last updated 2/3/2022).

Interests
  • Machine Learning
  • Medical Image Analysis
  • Computer Vision
Education

  • PhD in Computer Science, 2020 - Present

    University College London, UK

  • MSc in Informatics, 2019

    Nile University, Egypt

  • BSc in Biomedical Engineering, 2017

    Mansoura University, Egypt

Recent News

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  • I am serving as a program committee member for the Medical Imaging Meets NeurIPS workshop. Call for abstracts

  • I am starting a research internship at Siemens Healthineers, Princeton, USA.

  • Our abstract on Machine Learning for Identifying IPF Imaging Biomarkers has been accepted for presentation at the annual meeting of the Radiological Society of North America (RSNA'22).

Recent Publications

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Ahmed H. Shahin, Joseph Jacob, Daniel C. Alexander, David Barber (2022). Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data. In Medical Imaging with Deep Learning (MIDL).

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Ghadir Ali, Ahmed H. Shahin, Mohamed Elhadidi, Mustafa Elattar (2020). Convolutional Neural Network with Attention Modules for Pneumonia Detection. In 2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT).

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Ahmed H. Shahin, Prateek Munjal, Ling Shao, Shadab Khan (2020). FAIRS: Soft Focus Generator and Attention for Robust Object Segmentation from Extreme Points. Arxiv.

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Ahmed H. Shahin, Shadab Khan, Javier Villafruela, Jianbing Shen, Ling Shao (2019). Extreme Points Derived Confidence Map as a Cue for Class-Agnostic Interactive Segmentation Using Deep Neural Network. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).

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Ahmed H. Shahin, Karim Amer, Mustafa A. Elattar (2019). Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation. In International Symposium on Biomedical Imaging (ISBI).

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Experience

 
 
 
 
 
Machine Learning Consultant
Data Science Systems
Oct 2020 – Feb 2021 London, UK
Supported a private project related to exploring AI methods for lung image analysis.
 
 
 
 
 
PhD Student
University College London
Mar 2020 – Present London, UK
  • Topic: Machine Learning for High-Resolution Lung Image Analysis
  • Supervisors: David Barber and Daniel Alexander
  • Worked as a Graduate Teaching Assistant in COMP0016 Systems Engineering course (2020/2021, 2021/2022) to supervise students with their computer vision and machine learning projects.
  • Worked as a Graduate Teaching Assistant in COMP0090 Introduction to Deep Learning course (Autumn 2021).
 
 
 
 
 
Senior Machine Learning Engineer
Intixel
Nov 2019 – Feb 2020 Cairo, Egypt
Worked on developing deep learning algorithms for chest abnormalities detection and localization from X-Ray scans.
 
 
 
 
 
Research Intern
Inception Institute of Artificial Intelligence
Mar 2019 – Aug 2019 Abu Dhabi, UAE
  • Supervisor: Shadab Khan
  • Worked on weakly supervised methods for class-agnostic medical image segmentation to alleviate the annotated data scarcity problem.
 
 
 
 
 
Teaching Assistant
Mansoura University
Feb 2018 – Jun 2018 Mansoura, Egypt
Taught COM123 Electronic Measurements course for undergraduates.
 
 
 
 
 
Research Assistant
Nile University
Oct 2017 – Feb 2019 Giza, Egypt
  • Supervisor: Mustafa A. Elattar
  • Worked on the applications of deep neural networks in medical image analysis, particularly skin lesion segmentation and diagnosis.
  • Taught CSCI304 Design and Analysis of Algorithms course for undergraduates.

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