machine learning

Bushra Bin Hemid

M.S. Student

artificial intelligence machine learning information security privacy preserving techniques

MSc/PhD candidate in Artificial Intelligence at KAUST. Expertise in AI and information security. Research focuses on AI for infrared imaging, transforming sensing technologies for healthcare, agriculture, and smart infrastructure

Echo Ziyi Yang

Ph.D. Student

Autonomous Agent machine learning Reinforcement Learning

Ting Li

Postdoctoral Research Fellow, Environmental Science and Engineering

remote sensing machine learning precision agriculture agriculture environmental modeling crop health agricultural productivity sustainable agricultural

Ting Li is a Postdoctoral Research Fellow focusing her research on bridging the gap between complex data and real-world agricultural impact.

Yanda Meng

Assistant Professor, Bioengineering

artificial intelligence medical image analysis machine learning LLM Large Language Models

Yanda Meng designs AI models to improve medical imaging and clinical decision-making.

Anwar Alshaibani

Anwar Alshaibani > Appointments, Roles and Affiliations

AI machine learning deep learning

Visiting student at King Abdullah University of Science and Technology (KAUST).

Racha Zayni

Visiting Researcher, Information Science Lab

machine learning Data Analytics Wireless Communications AI-based Localization Signal processing

Visiting student at King Abdullah University of Science and Technology (KAUST).

Yimeng Chen

Postdoctoral Research Fellow, Computer Science

machine learning nlp deep learning statistics computational probability Python (Programming Language)

Yimeng Chen is a Postdoctoral Researcher in Prof. Jürgen Schmidhuber's research group at King Abdullah University of Science and Technology (KAUST).

Nanbo Li

Postdoctoral Research Fellow, Computer Science

machine learning AI Deep generative models generative ai Computer Vision

Nanbo Li is a Postdoctoral Fellow working in Prof. Jürgen Schmidhuber research group at the King Abdullah University of Science and Technology (KAUST) Center of Excellence for Generative AI.

Omar Ahmed

M.S. Student, Bioengineering

Computer Vision machine learning Computational Neuroscience Electroencephalograms artificial intelligence

Omar Ahmed is an MS student in the Bioengineering department at KAUST. His research explores the mechanisms that enable brain signal generalisability across individuals, addressing how neural activity patterns can be reliably interpreted despite significant inter-subject and temporal variability. A major challenge in neuroscience is that brain activity varies substantially between people and even within the same person over time, which limits the development of universal diagnostic and therapeutic tools. Towards this goal, Omar is developing deep learning models that can identify consistent

KAUST-CEMSE-CS-VISION-CAIR-Dalal-Aldossary

Dalal E. Aldossary

M.S. Student, Computer Science

machine learning Electroencephalograms Computer Vision Computational Neuroscience

Dalal Aldossary is a Master’s student in Computer Science at KAUST. She is part of the VISION-CAIR and the Neuroscience & AI Lab (NAIL), where she works on developing machine learning models that interpret and learn EEG representations and behavior.

Zakaria El Kassimi

Ph.D. Student, Electrical and Computer Engineering

machine learning deep learning Large Language Models

KAUST offers a unique environment where applied mathematics and data science meet real-world impact, with exceptional resources and a supportive community for ambitious research.

Jonathan Klein

Research Scientist, Computer Science

machine learning Computational Photography computational simulations

My fields of research interests include computational simulation, plant simulation and modeling, synthetic training data, machine learning architectures, none-line-of-sight imaging, and computational photography.

Yibin Wang

Ph.D. Student, Electrical and Computer Engineering

machine learning Free Space Optics FPGA

Keep Moving forward

Andrea Vanessa Rocha

Research Specialist, Statistics

Statistical Modeling computational statistics machine learning stochastic processes

Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab

wireless communication Signal processing optimization machine learning

Visiting Student, King Abdullah University of Science and Technology

Mohamed Ads

Visiting Student (former), King Abdullah University of Science and Technology

IoT Telecommunications Smart Wireless Massive Systems LED Wireless Communication Systems artificial intelligence machine learning Cyber Security

Visiting Student, King Abdullah University of Science and Technology

Hayssam Dahrouj

Research Scientist (former), King Abdullah University of Science and Technology

6g wireless systems cloud- and fog-radio access networks cross-layer optimization Cooperative networks machine learning Optical communications

Senior Research Scientist at KAUST (King Abdullah University of Science and Technology)

Karen Sanchez

Postdoctoral Research Fellow

Computer Vision machine learning AI for healthcare deep learning Medical imaging

Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Hani A. Al Majed

M.S. Student

machine learning Computer Vision AI4Science

Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science

Computer Vision machine learning Deep generative models

Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Saleh AlJazzar

Visiting Scholar (former), King Abdullah University of Science and Technology

Signal processing Wireless Communications machine learning

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Muhammad Esmat

Visiting Scholar (former), King Abdullah University of Science and Technology

machine learning neural network

Visiting student at, King Abdullah University of Science and Technology (KAUST).

Yasser Jaber

Visiting Researcher (former), King Abdullah University of Science and Technology

machine learning software artificial intelligence

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).

Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

embedded systems IoT energy efficiency machine learning artificial intelligence intrusion detection computer networks

Ahsan Mehmood

Intern (former), Information Science Lab

IoT Biomedical Signal Processing healthcare Digital signal processing machine learning

Visiting student at King Abdullah University of Science and Technology (KAUST).

Abdulkarem Badiea Alshaibani

M.S. Student, Information Science Lab

Localization machine learning GNSS localization Riemannian Optimization

MS Student at the Information Science Lab at the King Abdullah University of Science and Technology (KAUST).

CBRC Dual Seminar - Analysis of COVID-19 Severity - DeepSVP computational method

Sakhaa Al-Saedi, PhD Student; Azza Althagafi, PhD Student

Apr 12, 13:00 - 14:00

KAUST

machine learning Computer science artificial intelligence

Sakhaa Al-Saedi: We conduct a systematic genetic analysis of risk variants related to increasing the severity of COVID-19. It leads to a better understanding of its genetic basis and identifies the host genes to be targeted to tackle the COVID-19 pandemic and reduce its death toll. Azza Althagafi: We developed DeepSVP, a computational method to prioritize structural variants involved in genetic diseases by combining genomic and gene functions information. DeepSVP significantly improves the success rate of finding causative variants in several benchmarks and can identify novel pathogenic structural variants in consanguineous families.

CEMSE Big Data Open Day shows off fascinating discoveries

1 min read · Thu, Dec 8 2016

big data machine learning knowledge discovery supercomputing

The fifth-anniversary event marked CEMSE's biggest successes and featured 20 KAUST discoveries, with more than 1,000 visitors from the community attending the event."Big data has many applications: to understand medicine better; to manage food supplies, and to connect objects. Data is at the center of everything," said Dean Mootaz Elnozahy of the University's Computer, Electrical, Mathematical Science and Engineering (CEMSE) Division at the CEMSE Big Data Open Day held on December 4, 2016.

Professors discuss big data and human health in latest Sci-Café

1 min read · Mon, Mar 13 2017

machine learning big data artificial intelligence comparative genomics biomedical data human health

Professors Takashi Gojobori, Xin Gao and Robert Hoehndorf spoke about big data and human health at the Sci-Café event held on February 27. Their talk, which was moderated by James Calvin, Vice President for Academic Affairs, aimed to answer the question, "Can Big Data Solve My Health Problems?" This event was open to all members of the KAUST community.

Sheng Wang

Research Scientist, Structural and Functional Bioinformatics

bioinformatics machine learning Computational biology protein structure prediction

Sheng Wang worked as a Research Scientist at Prof. Xin Gao's Structural and Functional Bioinformatics Group at King Abdullah University of Science and Technology (KAUST). Sheng got his Ph.D. in Bioinformatics from the Institute of Theoretical Physics at the Chinese Academy of Sciences in 2010. He was then a postdoc fellow at Toyota Technological Institute in Chicago during 2010 and 2014. During 2014 and 2017, he was a research professional at the Department of Human Genetics at the University of Chicago. Since March 2017, he joined the SFB group as a research scientist. Currently, Sheng is a

Sakhaa Alsaedi

Ph.D. Student, Computer Science

artificial intelligence machine learning