Profiles

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.

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.

Elsiddig Awadelkarim Elsiddig is a Ph.D. candidate at Applied Mathematics and Computer Science  Research Group under the supervision of Professor Raul Tempone at King Abdullah University of Science and Technology (KAUST). 

Monte Carlo algorithms in Bayesian Statistics, Stochastic Control, 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.

Fahad Aljehani is a Ph.D. candidate in Electrical and Computer Engineering. His academic journey began at Dayton University in the USA, where he earned a Bachelor's degree in Electrical Engineering from 2012 to 2016. He then joined King Abdullah University of Science and Technology (KAUST) and completed his Master's degree in Electrical Engineering from 2017 to 2019. Currently, he is pursuing his Ph.D. at KAUST, focusing on the design of advanced control algorithms and estimation techniques to optimize process control systems.

Fahad's research focuses on designing advanced control algorithms and estimation techniques to optimize process control systems, specifically in aquaculture and wastewater treatment. He utilizes a multidisciplinary approach that combines classical control theory with cutting-edge artificial intelligence and machine learning methodologies to develop adaptive, efficient, and scalable models that enhance system performance, improve sustainability, and reduce operational costs. 
Area of interests: 

• Optimal control for a class of nonlinear systems
• Estimation and observer design methods in nonlinear systems 
• Reinforcement learning and dynamics programming
• Computer vision
• Machine learning

Gokul is an electrical engineering student who is currently doing research in core areas like power electronics, power systems and control systems. His research mainly focuses on grid design, modeling, control and development of modular power converters which helps in creating new solutions for sustainable energy generation, transmission, distribution and consumption.

He is experienced in Hardware-In-the-Loop (HIL) and Rapid Control Prototyping (RCP) systems like RTDS, Opal-RT, Speedgoat, Typhoon and dSPACE. He has great experience in MATLAB Simulink, NI Multisim, OrCAD Pspice and other ECAD tools which include Altium, Eagle and KiCAD.

The project he was involved in with KAUST as a visiting student was the development of a bi-directional multi-node Smart DC Grid for Autonomous Power Interchange Systems (APIS) which includes Energy Storage Systems (ESS). The system is designed in MATLAB Simulink and tested in real-time machines like Speedgoat and Opal-RT which links the software framework called Hyphae by Sony CSL, LF Energy. 

He was involved in other research projects like control design of the 6-ph PMSM motor, Level - 3 Autonomous Vehicle, High Voltage Low Power Converter,  Robust Steering Controller Design, Modelling of the University's Distribution Network etc...

Gokul's research focuses on power electronics, power systems, and control systems, with an emphasis on grid architecture, advanced modeling, control strategies and the development of modular power converters to optimize sustainable energy generation, transmission, distribution, and consumption. He has substantial expertise in Hardware-In-the-Loop (HIL) and Rapid Control Prototyping (RCP) platforms such as RTDS, Opal-RT, Speedgoat, Typhoon, and dSPACE. Skilled in MATLAB Simulink, NI Multisim, OrCAD Pspice, and ECAD tools including Altium, Eagle, and KiCAD.

• King Abdullah University of Science and Technology (KAUST) December 2021 - Present

PhD in Applied Mathematics and Computational Sciences Thuwal, Saudi Arabia, Advisor: Peter Richtarik 

• King Abdullah University of Science and Technology (KAUST) August 2020 - December 2021

MS in Applied Mathematics and Computational Sciences Thuwal, Saudi Arabia
Advisor: Peter Richtarik 

• Moscow Institute of Physics and Technology (MIPT) September 2014 - July 2019

BS in Applied Mathematics and Physics Dolgoprudny, Russia, Advisor: Boris Polyak 
Thesis: Averaged Heavy Ball Method

Stochastic Optimization, Distributed Optimization, Federated Learning, Machine Learning