Profiles

Olga Krestinskaya (Graduate Student Member, IEEE) is a Ph.D. candidate at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Her research focuses on software–hardware co-design for in-memory computing (IMC) architectures and AI hardware, with a particular interest in hardware-aware neural architecture search (NAS) algorithms, memristor-based systems, neuromorphic computing, and mixed-signal IMC implementations. She has authored several high-impact works on analog memristive neural networks, mixed-signal circuit-level implementations of in-memory computing architectures, quantized neural networks, and brain-inspired algorithms, with a focus on developing energy-efficient and scalable IMC hardware for AI applications.

Olga is the recipient of the 2019 IEEE CASS Predoctoral Award, the 2025 Web of Talents STEM Award (1st place), and multiple KAUST Dean’s Awards. Her work was recognized with the Best Poster Award at the 2nd Nature Conference on Neuromorphic Computing (2024), and she was shortlisted for the prestigious Rising Stars Women in Engineering Workshop (Asian Deans’ Forum 2024).

Olga`s research area is neuromorphic and brain-inspired algorithms, circuits, and architectures. In particular, she is interested in memristor-based architectures for neural networks and neuro-inspired systems. Currently, Olga is focusing on analog circuit-level implementations of reconfigurable memristive neural network architecture and optimization of hyperparameters.

I am a PhD student of computer science in Bio-Ontology Research Group under the supervision of Professor Robert Hoehndorf interested in mathematical and programming applications to natural sciences. In 2023 I graduated from Moscow State University, Faculty of Mechanics and Mathematics, Department of Mathematical Logic and Theory of Algorithms. In 2021 I acquired a second degree in the field of algorithmic bioinformatics. From 2020 to 2023 I worked as a research assistant in Ivannikov Institute for System Programming of the Russian Academy of Sciences; my research there was related to ECG signal classification with deep learning techniques and ECG delineation.

My current research interests are related to the development of ontology embedding methods and knowledge-enhanced learning with application to natural sciences.

 AI, IoT, Wireless Communications.

Control systems and power systems engineering. Modeling, simulation, analysis and design of solutions applied to power system stability and control. Optimal and data-driven approaches to the integration of renewable energy resources.

Education and Early Career

Paolo Redondo obtained his Bachelor's and Master's (M.Sc.) of Statistics from the University of the Philippines Diliman. He joined the PhD program in Statistics at KAUST in 2021.

• Extreme statistics.
• Time series.

Qilong Pan is a Ph.D. candidate in Statistics at KAUST, under the supervision of Prof. Ying Sun. Prior to his Ph.D., he earned a master's degree in Statistics at KAUST, and a bachelor's degree in Statistics from Wuhan University of Technology.

Qilong Pan's work bridges statistical modeling, optimization, and high-performance computing (HPC) to tackle complex challenges in geospatial analytics and machine learning. 

security, distributed systems

Rajat Kumar is a Ph.D. student at the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. He received the Bachelor of Technology degree in Electronics and Communication Engineering from the National Institute of Technology (NIT) Hamirpur, India, in 2019 and the Master of Technology degree in Electrical Engineering with a specialization in Very Large Scale Integration (VLSI) from the Indian Institute of Technology (IIT) Mandi, India, in 2021.

His research interests encompass energy harvesting, nanoelectronics, beyond-CMOS devices, and VLSI design.

Roman received the B.S. and M.S. degrees from the Faculty of Physics, Saint Petersburg State University, Saint Petersburg, Russia, in 2012 and 2014, respectively. Since 2018, he has been pursuing a Ph.D. degree at the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. His research mainly focuses on gas discharge plasma at atmospheric pressure and its application. Roman's academic advisor is Professor Deanna Lacoste.

Samy Mounir recently graduated from UCLouvain in Belgium with a B.Sc. in Engineering, specializing in Software and Mathematical Engineering. His diverse experiences include AI internships at KAUST and Belixys, as well as optimization and data analysis projects using real-world data. His research focuses on leveraging cutting‐edge AI techniques to solve practical problems.

Samy’s research centers on applied AI solutions with a focus on computer vision and smart city applications. He is currently working on plant monitoring using UAVs and computer vision techniques.