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.

Bilal Maassarani is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). He holds a B.S. in Mechatronics Engineering (2014) and an M.S. in Electrical Engineering (2017) from the University of Waterloo. His bachelor’s program included six co-op internships in roles spanning verification engineering, computational research, ASIC verification, hardware design, and radio modeling at companies including IDT, Natural Resources Canada, Ciena, General Motors, BlackBerry, and Broadcom. After completing his master’s degree, he worked as an FPGA developer at Ericsson.

Bilal joined KAUST initially under the supervision of Prof. Jeff Shamma and is currently advised by Prof. Eric Feron. His research focuses on mechatronic systems, particularly taking engineering problems from concept to functional prototypes. During his master’s studies he developed a dynamic check-weighing machine, and his Ph.D. work centers on the design and control of a novel hybrid-flight-mode unmanned aerial system.

Alongside his academic work, Bilal has contributed to several early-stage start-ups involving smart luggage, agricultural automation, and palm-tree-harvesting tools.

Bilal is interested in finding mechatronic solutions and taking them from problem to a functional proof-of-concept. He developed a dynamic weighing machine during his master's and currently a novel hybrid-flight mode unmanned aerial system as a Ph.D. 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.

Bushra Bin Hemid graduated with first honors in Computer Science from Umm Al-Qura University, and earned her Master's in Information Security from UCL. She has been a Lecturer at University of Jeddah and is currently pursuing an MSc/PhD in Artificial Intelligence at KAUST.

Artificial Intelligence, Machine Learning, intelligent sensing, and infrared imaging technologies. Focus on accessible sensing solutions for healthcare, agriculture, and smart infrastructure.

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.

Cheng-Long Wang is a PhD candidate in Computer Science (CS) at King Abdullah University of Science and Technology (KAUST), advised by Prof. Di Wang. His research focuses on machine unlearning, privacy-preserving machine learning, and trustworthy AI systems. His work explores both theoretical foundations and system-level design for provable and measurable machine unlearning in modern learning frameworks, including graph learning, federated learning, and large-scale deep models.

Cheng-Long Wang's research focuses on machine unlearning, privacy-preserving machine learning, and trustworthy AI systems. His work explores both theoretical foundations and system-level design for provable and measurable machine unlearning in modern learning frameworks, including graph learning, federated learning, and large-scale deep models.

Aldossary research interests include computer vision, machine learning, deep learning, computational neuroscience, and brain–computer interfaces. She is particularly interested in EEG representation and behavior learning, with applications in clinical EEG analysis and brain–computer interfacing.

Damilya Saduakhas is a PhD candidate in Statistics at King Abdullah University of Science and Technology (KAUST) in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) division, working under the supervision of Professor David Bolin. She received her B.S. degree in Mathematics from Nazarbayev University, Kazakhstan, in 2020 and her M.S. degree in Statistics from KAUST in 2022. Her work on log-Gaussian Cox processes on metric graphs received the Best Paper Award at Spatial Statistics 2025 and the Best Poster Award at ISBA World Meeting 2024. During her time at KAUST, she served as president of the ASA Student Chapter and as Academic and Research Counselor on the Graduate Student Council.

Damilya's research focuses on spatial statistical methods based on stochastic partial differential equations, with applications to environmental and urban data. 

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, in-memory computing using beyond CMOS devices, and hardware security primitives.

Bayesian and computational Statistics.

Echo Ziyi Yang is a Ph.D. student at King Abdullah University of Science and Technology (KAUST), conducting research under the supervision of Professor Bernard Ghanem at the Image and Video Understanding Laboratory (IVUL) within the Center of Excellence for Generative AI. She obtained her Master’s and Bachelor’s degrees from Harbin Institute of Technology (HIT), China.

Her research interests focus on Generative AI, autonomous agents, machine learning, and reinforcement learning.

Elham is currently a PhD candidate at the Communications and Computing Systems Laboratory (CCSL). She received M.Sc. degree in Software Systems Engineering from the Department of Computer Science at University College London (UCL), U.K., in 2018. She recieved B.Sc. degree in Computer Science from Imam Abdulrahman University, Alkhobar, KSA, in 2012. 

Elham's research focuses on AI-driven traffic scene understanding at urban intersections, combining advanced sensing technologies with graph representations to downstream intelligent transportation system applications, including real-time traffic monitoring, risk assessment, behavior analysis, flow prediction, and adaptive traffic control. 

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.