Profiles

He completed his undergraduate studies in Computer Science and Engineering at Sejong University in South Korea. He then pursued a master’s degree in Computer Science at KAUST under the supervision of Prof. Mohamed Elhoseiny, focusing on machine learning and generative models. Building on this foundation, he continued into the PhD program at KAUST, where his research now spans affective vision–language modeling, generative AI, and Neuroscience + AI.

His research focuses on affective vision–language modeling, generative AI, and the integration of Neuroscience with machine learning. He works on multimodal emotion understanding, interpretable generative models, and EEG-based neural signal modeling, aiming to build human-centered AI systems that connect perception, affect, and computational intelligence.

Michal A. Mankowski completed his Ph.D. in Computer Science at KAUST in 2020 and was a postdoctoral research fellow in the TREES research group. He is currently an assistant professor in the Department of Surgery at NYU Grossman School of Medicine, where his research focuses on data-driven approaches to organ transplantation and healthcare systems.

Michal's research focuses on the intersection of theoretical computer science and applied data science, specifically addressing optimization challenges within complex systems.

Michał Forystek received his B.Sc. degree in Information and Communication Technology from AGH University of Science and Technology in Kraków, Poland, in 2023.

He has a 2 years of experience as a Java Developer working for IG Group in Kraków.

Currently he is a Computer Science Master's student at the Secure Next Generation Resilient Systems Lab (SENTRY) under the supervision of Professor Charalambos Konstantinou.

Michał's research involves using Load Altering Attacks to exploit the Load Frequency Control in Power Systems and developing the appropriate countermeasures.

KAUST alumna Dr. Rabab Alomairy earned both her M.S. and Ph.D. in computer science from the King Abdullah University of Science and Technology (KAUST) under the supervision of Professor David E. Keyes and Senior Research Scientist Hatem Ltaief. She is currently a postdoctoral fellow at MIT’s JuliaLab and a recipient of the KAUST Ibn Rushd Fellowship.

Her research spans high-performance computing (HPC), task-based numerical libraries, GPU programming and AI-accelerated scientific applications, with emphasis on performance optimization for multicore and many-core architectures. Dr. Alomairy has collaborated with leading institutions, including Oak Ridge National Laboratory, the Innovative Computing Laboratory at the University of Tennessee and MINES ParisTech, contributing to the DOE-funded SLATE project during her internship at UTK.

In recognition of her impactful work, Dr. Alomairy was named a Rising Star in Computational and Data Sciences by the U.S. Department of Energy in 2022. She also led the first Julia tutorial for productive HPC at the Supercomputing Conference. Her work has scaled across the world’s top supercomputers and earned international honors, including a finalist recognition for the ACM Gordon Bell Prize (2020), the Gauss Award and the IEEE Computer Society Technical Community on High Performance Computing (TCHPC) Early Career Researchers Award for Excellence in High Performance Computing (2025).

Dr. Alomairy continues to advance sustainable computation and foster collaboration across disciplines, translating advances in HPC and AI into real-world impact.

• Task-based numerical libraries and applications
• Performance optimizations
• Artificial intelligence at large scale
• Dense linear algebra

Sakhaa Alsaedi is a Ph.D. graduate in Computer Science at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Xin Gao and Prof. Takashi Gojobori. She received her bachelor’s degree in Computer Science from Taibah University in 2018 and her master’s degree in Computer Science from KAUST in 2020. 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.

Sakhaa's research focuses on developing principled computational frameworks for causal reasoning in medical digital twin systems by integrating multimodal biomedical data. More broadly, her work includes multi-omics data integration, causal biomedical knowledge graph construction, causal reasoning framework development, and genetic risk factor analysis. She aims to develop computational approaches that advance the understanding of complex biological systems and genetic risk factors, ultimately supporting precision medicine and broader data-driven discoveries in biomedicine.