Profiles

Aznaur obtained his bachelor's degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology in 2023. He joined KAUST in 2024 to pursue his MS and PhD degrees.

Deep Learning, Computer Vision, Reinforcement Learning.

His research interests include deep learning, large language models, and reinforcement learning.

My undergraduate and graduate education at the University of Waterloo coupled with a variety of internships and a full-time role solidified my interest and background as a multidisciplinary hands-on mechatronics engineer.

I'm interested in finding mechatronic solutions and taking them from problem to a functional proof-of-concept. I developed a dynamic weighing machine during my master's and currently a novel hybrid-flight mode unmanned aerial system as a PhD Candidate.

Bumin K. Yildirim received his B.Sc. degree in Electrical and Electronics Engineering from TED University, Ankara, Türkiye, in 2020, and his M.Sc. degree in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST), Saudi Arabia, in 2023. He is currently pursuing a Ph.D. in the Communications and Computing Systems Laboratory (CCSL) at KAUST.

Bumin's research focuses on exploring generative artificial intelligence-based solutions to address the challenges of future wireless communication networks.

Changhao He received his B.Eng. degree in Information Engineering from Beijing University of Posts and Telecommunications (BUPT) in 2022, where he graduated with distinction as the top student among 344 peers and was the recipient of multiple national awards. He is currently pursuing M.S. and Ph.D. degrees in the Electrical and Computer Engineering (ECE) program at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Ahmed Eltawil.

His research interests include Optimization, UAV-enabled wireless communications, AI and 6G.

Cheng Luo is a Ph.D. student in the Image and Video Understanding Laboratory (IVUL) at King Abdullah University of Science and Technology (KAUST), specializing in generative AI and human-computer interaction. His research focuses on interactive video generation, multimodal understanding, and real-time generation, with applications in the field of mental health. He earned his Master's degree in Computer Science from Shenzhen University, China, in 2023.

His research interests include real-time and interactive video generation, generative models, affective computing, multimodal large language models, human-computer interaction, and psychosis intervention.

https://sites.google.com/view/chlwr

Machine Unlearning

Deng Luo is a Ph.D. Candidate in the Computer Science program under the supervision of Professor Ivan Viola at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. He received his Bachelor's degree in Bioinformatics from Southern University of Science and Technology in 2016. He joined KAUST and received his Master's degree in Bioscience in 2019. He has a multidisciplinary background, including bioinformatics, molecular biology, computer science, and entrepreneurship. 

With research and work experiences in interdisciplinary studies, he is interested in technologies that help people communicate better and that helps knowledge disseminates faster, especially from the perspective of education. He is now working on the Nano-visualization of the mitochondrion as a breakthrough point to the long term goal.

Dhanu Chettri is a Ph.D. candidate at the Advanced Semiconductor Laboratory (ASL) at King Abdullah University of Science and Technology (KAUST), under the mentorship of Prof. Xiaohang Li. His research focuses on ultra-wide bandgap semiconductors, particularly Gallium Oxide (Ga2O3) and Aluminum Nitride (AlN). Before joining KAUST, he served as a Senior Project Fellow at the Council of Scientific and Industrial Research–Central Electronics Engineering Research Institute (CSIR–CEERI).

Chettri’s research primarily involves material growth, device design, fabrication, and circuit implementation of advanced semiconductor devices such as MOSFETs and bidirectional switches. He has made significant contributions to the field, as evidenced by his publications. Notably, he achieved the first demonstration of a normally OFF β-Ga2O3 bidirectional switch, featured in Applied Physics Letters, AIP along with the first demonstration of an AlN MOSFET, published in the Journal of Physics D, IOP.

His research is particularly relevant for developing technologies suited to high-temperature and extreme environment applications, demonstrating the critical role and potential of ultra-wide bandgap semiconductors in modern electronics.

Dhanu's research interests include ultrawide bandgap semiconductor materials, specifically Ga2O3 and AlN. His work focuses on the fabrication and characterization of devices such as MOSFETs and FinFETs.

Divyanshu is a Ph.D. candidate in the Electrical and Computer Engineering department at KAUST. He received his M.Tech degree in VLSI from the Indian Institute of Technology (IIT) Mandi, India. He has worked as a visiting student at the Innovative Technologies Lab and the Integrated Circuits and System Group at KAUST. 

His research interests include Spintronics devices and circuits, VLSI design for beyond CMOS devices, and Hardware security primitives.

Bayesian and computational Statistics.

Elham is currently a PhD student in Electrical and Computer Engineering program (ECE) at KAUST. She holds an MSc in Software Systems Engineering from UCL, London. She has experience in academia working as teaching assistant, then lecturer and department coordinator. She also worked in industry as a system analyst.

Elham's research interest lies under the field of smart mobility by addressing the current challenges faced by traffic control systems. Her current research focuses on design a sustainable AI-based models to mitigate the limitations of the current smart mobility solutions.

Elnur Gasanov is a PhD candidate in the Optimization and Machine Learning Lab at the Center of Excellence for Generative AI (GenAI) at KAUST, where he is advised by Professor Peter Richtárik. His research focuses on distributed machine learning, stochastic optimization, and randomized linear algebra. Elnur holds a Master of Science in Computer Science from KAUST and a Bachelor's degree in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology.

Optimization and machine learning.

Eman Kabbas earned a Bachelor of Science and Education in Mathematics from Imam Abdulrahman Bin Faisal University and a Master’s in Mathematics from the University of North Carolina at Charlotte. Her academic journey, marked by deep curiosity and dedication, led her to become a lecturer at Jubail Industrial College (JIC). Now, as a Ph.D. candidate in Applied Mathematics and Computational Sciences under the mentorship of Professor Håvard Rue, Eman delves into Bayesian and computational statistics, striving to bridge theoretical concepts with practical applications. Eman is dedicated to fostering a new way of teaching statistics and data science through her research experience.

Eman Kabbas's research interests focus on developing and applying spline models in non-parametric regression. She addresses the limitations of splines in prediction tasks with insufficient data by proposing a spline model suitable for both regular and irregular observations, leverages Bayesian techniques to ensure efficient modeling and reliable predictions.

Eman Kabbas earned a Bachelor of Science and Education in Mathematics from Imam Abdulrahman Bin Faisal University and a Master’s in Mathematics from the University of North Carolina at Charlotte. Her academic journey, marked by deep curiosity and dedication, led her to become a lecturer at Jubail Industrial College (JIC). Now, as a Ph.D. candidate in Applied Mathematics and Computational Sciences under the mentorship of Professor Håvard Rue, Eman delves into Bayesian and computational statistics, striving to bridge theoretical concepts with practical applications. Eman is dedicated to fostering a new way of teaching statistics and data science through her research experience.

Eman's research interests include: Bayesian Statistics Computational Statistics Applied Statistics Data Science Her work focuses on advancing the understanding and application of these areas, aiming to contribute significant insights and innovations.