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)

Paving the Way for Next Generation Wireless Data Center Networks

-

B1 L4 R4214

As big data, articial intelligence, cloud services, cellular infrastructure, content delivery; all of which entail interconnected and sophisticated computing and storage resources. Recent studies on traditional data center networks (DCNs) revealed two key challenges: a biased distribution of inter-rack trac, and unidentied ow multi-classes best known as delay sensitive mice ow (MF) and throughput-hungry elephant ow (EF).

Efficient Localization of Human Actions and Moments in Videos

-

B3 L5 R5220

Abstract We are stumbling across a video tsunami flooding our communication channels. The ubiquity of digital cameras and social networks has increased the amount of visual media content generated and shared by people, in particular videos. Cisco reports that 82% of the internet traffic would be in the form of videos by 2022. The computer vision community has embraced this challenge by offering the first building blocks to translate the visual data in segmented video clips into semantic tags. However, users usually require to go beyond tagging at the video level. For example, someone may want

Reproducibility in Computer Science - Part 1

-

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

-

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.

A journey in applied complexity: pioneering record-performing technologies in clean energy harvesting, machine vision, and smart materials - Public Colloquium

-

B9 L2 R2322

Applied Complexity aims to understand the physical origin of these behaviors and transform them into sustainable technologies that tackle global problems of global interest. These range from energy harvesting to clean water production, the design of smart materials, biomedical applications, information security, artificial intelligence, and global warming. In this talk, I will summarize my group's recent research, discussing present results and future challenges of Applied complexity both as a science and engineering.

Machine learning in hardware via trained metasurface encoders: theory, design and applications

-

B2 L5 R5209

In this thesis, we introduce a novel concept of metasurface optical accelerators for machine learning with the corresponding end-to-end optimization framework that is robust to fabrication intolerance and can simultaneously optimize in tens of millions of degrees of freedom. The core of this technology is universal approximators, a single surface of optical nanoresonators mathematically equivalent to a single layer of an artificial neural network (ANN).

Machine-learning-assisted Quality of Transmission Estimation in Optical Networks

Andrea Bianco, Full Professor, Electronics and Telecommunications Department at Politecnico di Torino

-

B9 L4 R4125

Machine Learning (ML) tools have recently been adopted for a wide range of automated operations in optical networking, moving fundamental steps towards the paradigm of zero-touch infrastructures. One example of such tasks is estimating the Quality of transmission of a lightpath prior to its establishment, which is particularly challenging due to the non-linear characteristics of signal propagation in optical fibers and to the often-incomplete knowledge of equipment parameters. This talk provides an overview of the contribution of my research team in the field of ML-based lightpath QoT estimation, including transfer learning approaches for inter-domain model adaptation, active learning for model building with small-sized training dataset, quantification of prediction uncertainty, and adoption of Explainable AI framework to expose the internal decisional mechanisms of trained models.

Data, AI and Cybersecurity: Synergies and Interconnection

-

B9 L2 H2 H2

This Dean's Distinguished Lecture is part of the ECE Graduate Seminar. Modern Artificial Intelligence (AI) technologies, led by deep learning, have gained unprecedented momentum over the past decade.

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.

Student Focus: Adel Bibi

1 min read ·
KAUST Ph.D. student Adel Bibi, who works on bridging the gap between theory and practice in deep learning, believes we're living in a very exciting time.

Testing the blind spots in artificial intelligence

1 min read ·
Understanding the situations when artificial intelligence can fail is critical for application of future autonomous vehicles and medical diagnostics.

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.

KAUST startup tackles COVID using AI and robotics

1 min read ·
The COVID-19 pandemic has activated vital innovation and R&D initiatives to tackle the crippling effects, health ramifications, and overall impact of the coronavirus on global societies and economies. In recent months, the King Abdulaziz City for Science and Technology (KACST), based in Riyadh, Saudi Arabia, launched a COVID-19-themed virtual accelerator aimed at supporting talented innovators, aspiring entrepreneurs, and innovative small companies dedicated to finding solutions to mitigate the spread of the virus through protection, prevention, tracking/detection, and treatment solutions.

Broadening horizons for people with quadriplegia

1 min read ·
An assistive technology uses magnetic skin to support freedom of movement for people with quadriplegia.

Brain-on-a-chip would need little training

1 min read ·
A neural network that mimics the biology of the brain can be loaded onto a microchip for faster and more efficient artificial intelligence.

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.

Divided attention could ease wireless congestion

1 min read ·
Predicting wireless traffic using artificial intelligence could improve the reliability of future wireless communications.

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.

Perovskites used to make efficient artificial retina

1 min read ·
KAUST researchers have built an artificial electronic retina that mimics the behaviour of the eye’s rod retina cells. Their artificial retina can recognise handwritten numbers.

Giving voice to the voiceless through assistive technology

1 min read ·
Artificial skin coupled with sensors and machine learning technology allows people with voice disorders to communicate using soundless mouth movements.

Victor Escorcia

Research Scientist committed to innovating AI agents to empower creativity and increase productivity. Passionate about developing cutting-edge AI applications involving video understanding and creative storytelling. I have a wide range of research and engineering interests from on-device AI to General AI. Reach out!

Silvio Giancola

Silvio Giancola is a Research Scientist at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL), part of the Center of Excellence for Generative AI (GenAI).

Safa Khemiri

Safa Khemiri is an MS/PhD candidate at the Communication Theory Lab (CTL), King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini. Education and Early Career In 2018 and after being ranked among the top 2% at the Tunisian national contest for entrance to engineering schools, Safa Khemiri joined the best engineering school in Tunisia, "Ecole Polytechnique de Tunisie (EPT)" where she received multidisciplinary training. In her final year, she specialized in signals and systems. Before joining KAUST for her Master’s degree, Safa had

Nojood Almayouf

Nojood Almayouf is a Graduate Research Assistant in the Distributed Systems and Autonomy (DSA) Lab within the Robotics, Intelligent Systems and Control (RISC) Research Initiative. Education M.S. in Electrical Engineering, KAUST, Saudi Arabia (Aug 2017 - Dec 2019). Visiting graduate student, Stanford University, United States (Jun 2017 - Aug 2017). B.S. (with first honor) in Electrical and Computer Engineering, Effat University, Saudi Arabia (Jan 2013 - Jun 2017). Professional Profile Graduate Teaching Assistant for ECE 271A/ME 221A: Linear Control Systems Course, KAUST (Aug 2022 - Dec 2022)

Maria Sara Nour SADOUN

Visiting Student (former), Information Science Lab
Research internship in King Abdullah University of Science and Technology within EMANG as a Visiting Student on the topic of Epileptic Seizure Detection using Electroencephalography (EEG).

Khalil Allouch

Khalil Allouch is a MS/PhD student at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini. Education Khalil Allouch has studied mathematics and physics at the University of Tunis and has been among the top 1% in the Tunisian national contest of mathematics and physics in 2019. In 2022, he received his Engineering Diploma with first-class honors in multidisciplinary engineering from Ecole Polytechnique de Tunisie. Early Career Before joining the MS/Ph.D. program at KAUST, he had research experience with KAUST as a visiting

Hakim Ghazzai

Hakim is a researcher focusing on designing multi-disciplinary innovative solutions for diverse smart city applications and services.

Frankly Toro

Frankly Toro is a Ms/Ph.D. student under the supervision of Prof. Bernard Ghanem at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career He is a graduate of National University of Colombia where he received a B.S. degree in Mechatronics. Education Profile B.S., Mechatronics , National University of Colombia, 2020

Ferdaous Tarhouni

Ferdaous Tarhouni is an MS/PhD student at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini. Education and Early Career Ferdaous has studied mathematics and physics at the Preparatory Institute for Engineering Studies of Tunis and has been ranked among the top 2% in the national engineering school exam in 2020. This enabled her to enter the Ecole Polytechnique de Tunisie (EPT), one of the most prestigious engineering schools in Tunisia where she received multidisciplinary training. In her final year, she specialized in

Fares Fourati

Fares Fourati is a Ph.D. student at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini. Education Fares Fourati has studied mathematics and physics at the University of Sfax and has been among the top 1% in the Tunisian national contest of mathematics and physics in 2017. In 2020, he received his diplôme d’ingénieur with first-class honors in multidisciplinary engineering from Ecole Polytechnique de Tunisie. In 2022, he received his Master of Science in electrical and computer engineering from KAUST. Early Career Before

Fat-hy Omar Rajab

Master's Thesis Abstract The multi-agent robotic system has been proved to be more superior in undertaking functionalities, arduous or even impossible when performed by single agents. The increased efficiency in multi-agent systems is achieved by the execution of the task in a cooperative manner. But to achieve cooperation in multi-agent systems, a good localization system is an important prerequisite. Currently, most of the multi-agent systems rely on the use of the GPS to provide global positioning information which suffers great deterioration in performance in indoor applications, and also

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.

Amer AlGhadhban

Amer AlGhadhban is a Ph.D. student under the supervision of Professor Basem Shihada at Networking Research Lab in King Abdullah University of Science and Technology (KAUST). Amer obtained both of his degrees B.S. and M.Sc. in Computer Engineering from King Fahd University of Petroleum and Minerals (KFUPM). He was a Cisco Academy instructor and during that he earned multiple professional certificates: Cisco Certified Network Associate (CCNA), Cisco wireless, SANS-GIAC Certified Firewall Analyst (GCFW-Gold), Certified Ethical Hacker (CEH), Security Certified Network Engineer (SCNP), and SANS

Alejandro Pardo

Alejandro Pardo is a Ph.D. candidate in the Electrical and Computer Engineering (ECE) program under the supervision of Professor Bernard Ghanem at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. Education and Early Career Alejandro has an Engineer’s degree in Artificial Intelligence in both Electronics and Biomedical Engineering from the University of Los Andes in Colombia in 2017. He continued his studies at the University of Los Andes and received his Master’s Degree in Biomedical Engineering in 2018. He visited KAUST as a

Abdurauf Abdurakhmanov

Abdulmajeed Aljaloud

Visiting Student, Computer Science
Visiting Student Research Program ,Research Intern at King Abdullah University of Science and Technology (KAUST)