Profiles

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Abdullah Alshehri is a Ph.D. candidate in the Electrical and Computer Engineering (ECE) department at the Integrated Circuit and System (ICS) Research Group at King Abdullah University of Science and Technology (KAUST). 

Alshehri received his Bachelor of Science degree in Electrical and Electronics Engineering from the University of Brighton in the United Kingdom in 2014. In 2016, he earned his master's degree in Electrical Engineering (Electro-physics) from KAUST in Saudi Arabia.

Alshehri's research focuses on designing low-power, high-speed CMOS interface circuits for sensors. He has published over 10 papers and obtained a patent. Throughout his academic and professional journey, Alshehri has gained valuable experience from positions at companies such as STC, Digital Network, ARAMCO, SEMC, Umm Al Qura University, and KAUST.

Abdullah's research interests focus on the design of low-power, high-performance interface circuits for advanced applications. Specific areas of focus include:

1. Low-power, high-speed CMOS interface circuit design:
   • Developing energy-efficient amplifiers, filters, and other analog building blocks
   • Optimizing circuit topologies and techniques to improve power, speed, and linearity
2. High-performance analog comparators:
   • Designing low-offset, low-noise comparator circuits
   • Enhancing comparator speed and resolution for precision applications
3. Energy-efficient digital logic circuits:
   • Implementing compact, low-power digital logic blocks and controllers
   • Exploring circuit techniques to minimize dynamic and static power consumption
4. High-speed, low-power analog-to-digital converters (ADCs):
   • Advancing ADC architectures and circuit designs to improve power consumption and conversion rates
   • Reducing the design complexity of high-performance ADC

• 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.

• Neuromorphic engineering
• spiking neural network

Deep Learning , Near-Field Communication, Array Signal Processing

• Robotics
• Self-Assembly
• Control
• 3D Printing
• Modeling

Arturo is a Ph.D. candidate in Electrical and Computer Engineering at the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division of King Abdullah University of Science and Technology (KAUST). Following his participation in the KAUST's 2017 Photonics Summer Camp, he started his graduate studies at KAUST in August 2018. Prior to his graduate studies he earned B.Sc. in Engineering Physics from Instituto Tecnológico y de Estudios Superiores de Monterrey (Mexico) in 2017, and conducted a research intership in the Nuclear Sciences Institute (ICN) of the Universidad Nacional Autónoma de México in 2016.

Arturo is the co-founder of Pixeltra Inc., a startup company specializing in multidimensional imaging solutions through metasurfaces. He actively serves as a reviewer for Nature Communications, and has authored ten publications in high-impact factor journals during his Ph.D. He received the Academic Excellence award from KAUST in 2022 and 2023, and was awarded 2nd place at the 2019 Falling Walls international pitching competition.

Arturo's research focuses on the design and fabrication of optical metasurfaces, emphasizing practical applications in remote sensing and hyperspectral imaging.

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.

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.

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.