artificial intelligence

Najmeddine Dhieb

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)

AI4GH Seminar Series | Predicting Protein Function and Phenotype Associations

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B2 R5220

The amount of available protein sequences is rapidly increasing, mainly as a consequence of the development and application of high ​throughput sequencing technologies in the life sciences.

Causality-based new drug development: Some successful cases and a new challenge

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B2 L5 R5209

Abstract The success rate of new drug development is extremely low. It is even lower when the new drug has a novel mechanism of action. From my experience, I propose that the success rate can be dramatically increased by predicting the effects of a drug in humans based on the causality-confirmed data. It is dangerous to develop new drugs based on the data in which causality is not confirmed. In biology, there are three different types of relationships in which the causality is confirmed, i.e. the relationships between parent and child, between gene and phenotype and between intervention and

VSIM: Visualization and Simulation of Genomes for Premarital Testing

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B3 L5 R5209

Abstract Interpretation and simulation of the large-scale genomics data are very challenging, and currently, many web tools have been developed to analyze genomic variation which supports automated visualization of a variety of high throughput genomics data. We have developed VSIM an automated and easy to use web application for interpretation and visualization of a variety of genomics data, it identifies the candidate disease variants by referencing to four databases Clinvar, GWAS, DIDA, and PharmGKB, and predicted the pathogenic variants. Moreover, it investigates the attitude towards

AI4GH Seminar Series - VSIM: Visualization and Simulation of Genomes for Premarital Testing

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B2 R5220

Interpretation and simulation of the large-scale genomics data are very challenging, and currently, many web tools have been developed to analyze genomic variation which supports automated visualization of a variety of high throughput genomics data.

KAUST Research Conference Digital Health 2020

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B19 L2 H1

Computational Bioscience Research Center at King Abdullah University of Science and Technology is pleased to announce the KAUST Research Conference on Digital Health 2020.

Artificial Intelligence methods for precision health: Applications to rare disease and cancer research

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B9 L2 H2

Abstract The life sciences have invested significant resources in the development and application of semantic technologies to make research data accessible and interlinked, and to enable the integration and analysis of data. Utilizing the semantics associated with research data in data analysis approaches is often challenging. Now, novel methods are becoming available that combine symbolic methods and statistical methods in Artificial Intelligence. In my talk, I will show how to incorporate biological background knowledge in machine learning models for the identification of gene-disease

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

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

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KAUST

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.

Professor Robert Hoehndorf's PhenomeNET method wins at Ontology matching workshop

1 min read ·
Professor Robert Hoehndorf and Postdoctoral Fellow Miguel Angel Rodriguez Garcia are the winners of the Ontology Alignment Evaluation Initiative Challenge sponsored by Pistoia Alliance.

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.

Sarah Alghamdi defends her master's thesis

1 min read ·
Sarah Alghamdi successfully defended her master's thesis on April 10, 2018. Her project, entitled "Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Ageing and Longevity in Inbred Mouse Strains", was well-received by a panel of professors that included Professor Vladimir Bajic, Associate Professor Xin Gao and Assistant Professor Robert Hoehndorf.

Maxat Kulmanov defends his thesis proposal

1 min read ·
Maxat Kulmanov, a Ph.D. candidate under the supervision of Assistant Professor Robert Hoehndorf, defended his thesis proposal on July 31, 2018.

Azza Althagafi defends her Master's thesis

1 min read ·
Azza Althagafi, a student under the supervision of Assistant Professor Robert Hoehndorf, defended her Master's thesis on November 1, 2018.

KAUST Research Conference: AI in Medicine

1 min read ·

Database to support infectious disease research

1 min read ·
Linking disease pathogens to clinical signs and symptoms through a database could support research into the molecular mechanisms of infectious diseases.

Symbol of change for AI development

1 min read ·
Bridging the knowledge gap in artificial intelligence requires an embedding function that helps step between different types of "thinking."

Robert Hoehndorf promoted to associate professor at KAUST

1 min read ·
KAUST faculty member Robert Hoehndorf was recently promoted from the rank of assistant professor to associate professor. Hoehndorf’s promotion caps a year-long process where the German researcher’s scientific and scholarly output was measured and evaluated by internal and external reviews.

Former KAUST VSRP student wins Best Talk Award at ISMB 2020

1 min read ·
Runar Reve, a former KAUST Visiting Student Research Program (VSRP) student, recently received the International Society for Computational Biology’s (ISCB) Bio-Ontologies COSI – Best Talk Award at the 28th Conference on Intelligent Systems for Molecular Biology (ISMB) 2020.

BORG team win at the KAUST-NVIDIA GPU Hackathon 2022

1 min read ·
Congratulations to Senay Kafkas, Maxat Kulmanov and Fernando Zhapa Camacho of the Bio-Ontology Research Group (BORG) on winning at the KAUST-NVIDIA GPU Hackathon 2022. The 8th edition of the Hackathon on Accelerating Scientific Applications using Graphical Processing Units (GPUs) was held at King Abdullah University of Science and Technology (KAUST), twelve teams of students and researchers enjoyed the opportunity to accelerate their codes in GPU’s under the guidance of expert mentors of NVIDIA, Codee, KAUST Supercomputing Lab (KSL) and KAUST core labs.

MS Thesis Defense | Learning 3D structures for protein function prediction

1 min read ·
Student Nurul Muttakin from the Bio-Ontology Research Group (BORG) under the supervision of Assoc. Prof. Robert Hoehndorf successfully defends his Masters thesis. He presented his research on the topic " Learning 3D structures for protein function prediction".

PhD Dissertation Defense | Ontology design patterns and methods for integrating phenotype ontologies

1 min read ·
CBRC PhD student Sarah Alghamdi successfully defended her dissertation last week. She has been an essential member of the Bio-Ontology Research Group (BORG) since 2015.Her research interests include the applications of artificial intelligence and statistical methods to genomics and healthcare.

PhD Dissertation Defense | Prioritizing Causative Genomic Variants by Integrating Molecular and Functional Annotations from Multiple Biomedical Ontologies

1 min read ·
CBRC PhD Student Azza Althagafi successfully defends her dissertation under the supervision of Associate Professor Robert Hoehndorf. She has been a member of the Bio-Ontology Research Group (BORG) since 2016. Her research interest lies in the crossroads of computer science and biology, leveraging AI techniques to explore the human genome's intricacies and its link to various diseases.

A new approach to rare disease diagnosis

1 min read ·
An innovative AI-based tool leverages varied symptom descriptions, along with evidence from the scientific literature and genomic datasets, to pinpoint disease-associated gene variants.

AI tool predicts function of unknown proteins

1 min read ·
Powered by logic and large language models, DeepGO-SE predicts the biological role of proteins and could be used to aid drug discovery.

Shahad Qathan

M.S. Student, Computer Science
Shahad Qathan is an MS candidate in the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Robert Hoehndorf. Research Interests Artificial Intelligence, more specifically Machine Learning and its applications in healthcare and Bioinformatics Education Profile B.Sc, Computer Science, King Abdulaziz University, Jeddah, Saudi Arabia, 2020

Sarah Alghamdi

Ph.D. Student, Computer Science
Sarah Alghamdi is a Ph.D. candidate in the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Robert Hoehndorf. Research Interests Sarah's research interests include applications of artificial intelligence and using statistical methods to genomics and healthcare. Professional Profile Program Committee for the International Conference of Biomedical Ontology (ICBO 2022) Program Committee for the International Society of Molecular Biology (ISMB 2022) - Bio-Ontology track 2018-2021: Teaching Assistant positions: CS

Sakhaa Alsaedi

Ph.D. Student, Computer Science
​Sakhaa Al-Saedi completed her bachelor's degree in Computer Science in 2016 at Taibah University. She is the founder of the Medvation startup company, inventing educational kits that teach children concepts of robotics and Machine Learning (ML) in fun ways. She worked as a product developer at the Namma Al-Munawara company, Madinah, before starting her master's degree at KAUST in 2017. She is currently working with the Bio-Ontology Research Group (BORG) of Professor Robert Hoehndorf on human genome sequencing to evaluate the impact of Saudi-specific allele frequencies on variant calling

Runar Reve

Visiting Student, Bio-Ontology Research Group
​Runar Reve is from Klepp, Rogaland, in Norway. He is currently in his industry year as a visiting student for his bachelor's degree in Artificial Intelligence and Robotics at Aberystwyth University in Wales and will obtain his degree by the summer of 2021. He is currently working with Professor Robert Hoehndorf Bio-Ontology Research Group (BORG) on genome-wide association study (GWAS) to find variants, or sets of variants, in genomes that can result in genetic disease.​ Research Interests Genome-Wide Association Studies​. Education ​Undergrad in Artificial Intelligence (with integrated year

Robert Hoehndorf

Associate Professor, Computer Science
Robert Hoehndorf is an Associate Professor of Computer Science at KAUST. His research focuses on bioinformatics, knowledge representation and reasoning, Semantic Web technologies, and neuro-symbolic methods.

Maxat Kulmanov

Research Scientist, Bio-Ontology Research Group
Maxat Kulmanov is a Research Scientist in the Bio-Ontology Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Maxat's research interests include bioinformatics, knowledge representation and reasoning, machine learning, neural networks, semantic web, and algorithms. He is interested in knowledge discovery and data integration using artificial intelligence and semantic web technologies in biology and biomedicine. Professional Profile 2020-Present: Postdoctoral Research Fellow, Computational Bioscience Research Center, King Abdullah University of

MD Nurul Muttakin

Ph.D. Student, Computer Science
Nurul Muttakin, is an M.S./Ph.D. candidate in the Bio-Ontology Research Group (BORG) under the supervision of Professor Robert Hoehndorf. Before joining KAUST Nurul completed his B.Sc. in CSE from Bangladesh University of Engineering and Technology, Bangladesh. Research Interest Nurul is Interested in the application of Artificial Intelligence in Bioinformatics tasks like protein function prediction as well as understanding the theory behind it. Education Profile B.Sc. in CSE, Bangladesh University of Engineering and Technology, Bangladesh

Kexin Niu

Ph.D. Student, Bioengineering
Kexin Niu, is an M.S./Ph.D. candidate in the Bio-Ontology Research Group (BORG) under the supervision of Professor Robert Hoehndorf. Before joining KAUST Kexin obtained her bachelor's degree in Bioinformatics from Southern University of Science and Technology, Shenzhen, China. "What I like best about KAUST is the communication of diverse cultures and diverse disciplines, which enables me to have more possibilities." Research Interest Kexin’ s Research interests include but are not limited to bioinformatics and application of machine learning method in biomedical data. Education Profile 2016 -

Azza Althagafi

Ph.D. Student, Computer Science
Azza Althagafi is a Ph.D. candidate in the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Robert Hoehndorf. Professional Profile ​2016 to present Graduate Student, KAUST, Thuwal, Saudi Arabia. 2015 - 2016: Teaching Assistant, Taif University, Taif, Saudi Arabia. 2014 – 2015: Volunteer Teaching Assistant, Umm Al-Qura University, Makkah, Saudi Arabia. 2013 – 2016: Assistant Trainer, Mawhiba, The King Abdulaziz and His Companions' Foundation for Giftedness and Creativity, Makkah, Saudi Arabia. Scientific and