Kumail Alhamoud

Kumail Alhamoud

MS Student - Computer Science



I am currently an MS student in Computer Science at KAUST’s Image and Video Understanding Lab (IVUL), advised by Prof. Bernard Ghanem, where I am passionate about applying robust machine learning algorithms to tackle real-world challenges. For my future PhD studies, I am eager to leverage these machine learning tools to make a positive impact in the fields of medical imaging, medicinal chemistry, and healthcare.

My undergraduate research at Cornell University, where I worked with Prof. Fengqi You at the Process-Energy-Environmental Systems Engineering (PEESE) lab, gave me a solid foundation in large-scale system optimization, particularly in the area of hybrid quantum-classical approaches to industrial scheduling. Currently, in my MS studies, I am engaged in machine learning research, including continual learning from image and video data, robustness and domain generalization, and molecular conformation generation.

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  • Computer Vision
  • Reliable Deep Learning
  • Continual Learning
  • Domain Generalization
  • AI for Healthcare and Biomedicine
  • MS in Computer Science, 2021-Present


  • BS in Electrical and Computer Engineering, 2021

    Cornell University


KAUST, Image and Video Understanding Lab (IVUL)
Graduate Researcher
Sep 2021 – Present Thuwal, Saudi Arabia

Projects include:

  • Video Continual Learning
  • Generalization and Transferability of Molecular Graph Representations
  • Domain Generalization and Adversarial Robustness
Cornell University, Fengqi You Research Group
Undergraduate Research Assistant
Jan 2020 – Jan 2021 Ithaca, NY, USA

Projects include:

  • Quantum Computing for Industrial Scheduling Optimization
  • Deep Generative Modeling for Automatic Molecular Design and Drug Discovery
Boston University, Damp Lab
Undergraduate Research Assistant
Jun 2019 – Aug 2019 Boston, MA, USA
Helped develop a software tool, using BLAST and Python, that uses DNA Sequence Alignment for Sequence Pathogenicity Screening.

Awards and Fellowships

Best Poster Award at SCML 2022
Awarded by the KAUST Research Conference on Scientific Computing and Machine Learning for work on “Chemistry-informed Graph Representation Learning for Molecular Conformation Generation and Beyond.”
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Saudi Leadership Society Fellow
Chosen by the Misk Foundation as an inaugural member of the prestigious Saudi Leadership Society.
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Cornell University
Summa Cum Laude (Highest Distinction)
Graduated with the highest distinction (Summa Cum Laude) from the Electrical and Computer Engineering department at Cornell University.
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Cornell University
Outstanding Teaching Assistant Award
Awarded for my performance as a TA in INFO/CS 4300: Language and Information.
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Rhodes Trust
Rhodes Scholarship Finalist
Added to the historical list of finalists at one of the most prestigious international scholarships.
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KAUST Gifted Student Program Scholarship
A highly selective, full-tuition-and-expenses scholarship, awarded to few outstanding Saudi students.