Profiles

Professor Salama received his B.S. (Hons.) degree from Cairo University, Egypt, in 1997. He obtained his M.S. and Ph.D. degrees in electrical engineering from Stanford University, U.S., in 2000 and 2005, respectively.

The principal investigator of the KAUST Sensors Lab, Salama joined the University in 2009. From 2009 to 2011, he served as the founding program chair for Electrical Engineering at KAUST. Before joining KAUST, he worked as an assistant professor at Rensselaer Polytechnic Institute, U.S., from 2005 to 2009.

Dr. Salama—a senior member of the Institute of Electrical and Electronics Engineers (IEEE)—has authored 360 articles and holds 50 patents on low-power mixed-signal circuits for intelligent, fully integrated sensors and nonlinear electronics, particularly memristor devices.

His work on complementary metal-oxide semiconductor (CMOS) sensors for molecular detection has been funded by the National Institutes of Health (NIH) and the Defense Advanced Research Projects Agency (DARPA). He is also the co-founder of Ultrawave Labs, a biomedical imaging company.

Salama received the Stanford-Berkeley Innovators Challenge Award in Biological Science.

Professor Salama’s research interests cover various interdisciplinary aspects of electronic circuit design and semiconductor fabrication. He is actively engaged in developing devices, circuits, systems and algorithms to enable inexpensive analytical platforms for a variety of industrial, environmental and biomedical applications.

Salama’s most recent research has focused on developing neuromorphic circuits for brain emulation.

• Developing Biosensors to detect biomarkers for cancer and other ailments.
• Studying electrochemical characteristics of various materials, polymers and films.
• Designing wearable, point-of-care, biotech medical devices.
• Utilizing machine learning to aid in sensing and data interpretation.

Li Zhang received the B.S. degree in microelectronic science and engineering from University of Electronic Science and Technology of China, China, 2018 and the M.S. degree in electrical engineering from King Abdullah University of Science and Technology, Saudi Arabia, 2019.

Li Zhang is interested in quantized neural networks, neural network accelerator and software/hardware co-design.

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.

• Developing Biosensors to detect biomarkers for cancer and other ailments.
• Studying electrochemical characteristics of various materials, polymers and films.
• Designing wearable, point-of-care, biotech medical devices.
• Utilizing machine learning to aid in sensing and data interpretation.

Sebastian Celis Sierra is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), where he develops advanced integral-equation solvers for the accurate simulation of electromagnetic metasurfaces. He holds an M.S. in Electrical Engineering (2018–2020) from KAUST and dual B.Eng. degrees in Electrical/Power Engineering and Electronics Engineering (2014–2018) from Universidad de los Andes, Bogotá.

Sebastian's research focuses on formulating and implementing surface and volume integral-equation methods in both the time and frequency domains to capture complex electromagnetic behavior in arbitrarily shaped metasurfaces. By coupling these formulations with generalized sheet transition conditions (GSTCs), he aims to achieve both numerical efficiency and physical fidelity. His work advances the theoretical foundations and practical computational tools necessary for the next generation of communication systems.