artificial intelligence

Yasmeen Alsaedy

M.S. Student, Computer Science
She is an AI researcher specializing in generative AI and deep learning. With a strong academic foundation and hands-on experience in machine learning, data science and artificial intelligence, she is passionate about advancing AI applications in real-world scenarios. She has contributed to cutting-edge projects, published research, and collaborated on innovative solutions that bridge the gap between AI theory and practice. Her expertise includes designing and implementing advanced data models, AI-driven visual/text computing, and deep learning architectures.

Yasser Jaber

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

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)

Reproducibility in Computer Science - Part 1

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B9 L3 R3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Reproducibility in Computer Science - Part 2

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B9 L3 R3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Reproducibility in Computer Science - Part 3

-

B9 L3 R3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Computer vision: Teaching computers how to see the world

1 min read ·
Ghanem works in the Visual Computing Center (VCC) and is interested in computer vision, image processing, and machine learning.

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

1 min read ·
​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.

The awesome scope of big data

1 min read ·
Sifting through huge amounts of data may bring a better understanding of whale shark social structures, protein targets for drug therapies and disease-causing genes.

KAUST Associate Professor Xiangliang Zhang talks about artificial intelligence

1 min read ·
Xiangliang Zhang, associate professor of computer science in the University's Computer, Electrical and Mathematical Science and Engineering division, recently gave an invited Early Career Spotlight Talk at the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-18) 2018. During the event—which was held in Stockholm, Sweden, from July 13 to 19—Zhang and 21 international peers presented on all areas of artificial intelligence (AI).

Tweaking tools to track tweets over time

1 min read ·
Computer model learns to identify Twitter users’ evolving interests by analyzing their Tweets.

AI reveals nature of RNA-protein interactions

1 min read ·
A deep learning tool could help in structure-based drug discovery.

ActivityNet is featured in the 2019 Artificial Intelligence Index

1 min read ·
ActivityNet is featured in the AI Index as the benchmark for the algorithms that can recognize human actions and activities from videos.

Approximating a kernel of truth

1 min read ·
Machine learning tasks using very large data sets can be sped up significantly by estimating the kernel function that best describes the data.

CEMSE Division startups in focus: Peregrine Genomics

1 min read ·
The future has already arrived when it comes to the most exciting and promising field of modern medicine—precision medicine.

Flattening the sentimental curve

1 min read ·
-By Meres J. Weche, KAUST News As municipal, regional and national governments have mandated longer and more restrictive isolation time periods to slow down the spread of the COVID-19 pandemic and "flatten the curve," KAUST Associate Professor of Computer Science Xiangliang Zhang works on flattening the "emotional curve." Zhang's research focuses on developing reliable algorithms to analyze complex data sets through machine learning and artificial intelligence. Her research group specifically uses computer models to analyze social media posts on Twitter to study people's interests. When the

Tracking the Curve: Analyzing the Emotional Response to COVID-19

1 min read ·
Hashtags like #covid19 and #coronavirus help us stay up to date on the developments of the new coronavirus pandemic. But beyond breaking news, tweets also offer a glimpse into the emotional side of the COVID-19 crisis.

AI that's built to save lives

1 min read ·
Associate Professor Xin Gao and his group have developed an artificial-intelligence (AI) based solution to help increase COVID-19 testing accuracy. Identifying cases of early stage infection has been particularly challenging for frontline clinicians. Gao's AI-based model, which aims to increase accuracy, has been put to immediate use at King Faisal Specialist Hospital (KFSH) in Riyadh.

How AI helps improve COVID-19 testing

1 min read ·
Following a call by President Tony Chan for KAUST PIs to contribute through their research capabilities to alleviate the COVID-19 pandemic, efforts coordinated by Donal Bradley, KAUST vice president for research, and Pierre Magistretti, KAUST dean of the Biological and Environmental Science and Engineering division, mobilized a group of faculty to form the Rapid Research Response Team (R3T).

Meet KAUST prospective student: Pratik Nag

1 min read ·
Pratik Nag will join KAUST this fall as a Ph.D. candidate and member of the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Pratik holds a master's degree in statistical quality control and operation research, and a bachelor's degree in statistics, from the Indian Statistical Institute and the University of Calcutta, India.

Deep learning in the emergency department

1 min read ·
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.

KAUST research group win inaugural MCIT Digital Innovation Award

1 min read ·
A team of KAUST researchers have won first place in the Digital Research track at the inaugural Digital Innovation Awards held on Sunday, April 25, 2021. Launched by the Ministry of Communications and Information Technology (MCIT), the awards aim to “enhance the culture of innovation and entrepreneurship in digital research and development” in Saudi Arabia.

KAUST-KFUPM collaboration wins top honors at STC AIoT Hackathon

1 min read ·
A team composed of KAUST and King Fahd University of Petroleum and Minerals (KFUPM) students was one of three winning teams of this year’s Saudi Telecom Company (STC) AIoT (AI & IoT) Hackathon. The KAUST entry, AgriDoctor, a proposed autonomous, sustainable, intelligent agriculture system, was a standout pick for the competition judges from a pool of 110 project submissions and 350 participants.

Ángel López Oriona

Postdoctoral Research Fellow, Statistics
Dr. López Oriona received his bachelor’s degree in Mathematics and his master’s degree in Statistics both from the University of Santiago de Compostela (Spain), his master’s degree in Big Data Analytics from the European University of Madrid (Spain), and his PhD in Statistics from the University of A Coruña (Spain). He was a Visiting Researcher at the Sapienza University of Rome (Italy), the University of Sydney (Australia), the Helmut Schmidt University of Hamburg (Germany), and Lancaster University (United Kingdom). Since September 2023, he is a Postdoctoral Fellow in the Environmental

Pratik Nag

Ph.D. Student, Statistics
Pratik Nag is a Ph.D. candidate at the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Pratik obtained a master's degree in statistical quality control and operation research from the Indian Statistical Institute, India. Research Interests Pratik's research interests focus on machine learning, artificial intelligence and statistical techniques to solve problems related to spatio-temporal processes. Education Profile Master's degree in Statistical Quality Control and operation research, Indian Statistical Institute, India

Jesper Tegner

Professor, Bioscience
Jasper Tegner is an M.D./Ph.D., innovator and professor with over 350 publications, dedicated to exploring the interconnected mechanisms underlying life, intelligence and the mind. His research aims to advance fundamental progress in artificial intelligence by moving beyond engineering to understand the intrinsic modes of operation within cells, between cells and within the brain.

Bernard Ghanem

Professor Ghanem's research focuses on computer vision and machine learning, emphasizing large-scale video understanding, vision for automated navigation and theoretical foundations.