Profiles

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

Hanan Alahmadi is a Ph.D. candidate in the Statistics program (CEMSE) at King Abdullah University of Science and Technology (KAUST), specializing in spatial methods for health surveillance in Saudi Arabia, with a focus on data integration and cluster detection under the supervision of Professor Paula Moraga. Her research combines satellite and health data to monitor disease and environmental risks and to develop GIS platforms that support data-driven decision-making. She holds a master’s degree in statistics from KAUST, where she was supervised by Professor Håvard Rue. Hanan is also a lecturer at King Saud University and the founder of Sorat Alardh, a space-tech startup that harnesses Earth observation data for environmental and health applications. Her work has been recognized with several honors, including a grant from the Communications, Space & Technology Commission (CST) and her selection as a finalist in the Falling Walls competition.

• Geospatial data analysis and health surveillance
• Spatio-temporal disease data
• Statistics and spatial epidemiology
• Geospatial modeling
• Disease mapping

Hani Al Majed has a Bachelor's degree in Electrical Engineering from the University of Illinois at Urbana-Champaign (2019–2023) and is currently pursuing a Master's in Electrical and Computer Engineering at KAUST (2023–2025) under the supervision of Professor Bernard Ghanem. His career includes internships at IBM, the National Center for Supercomputing Applications (NCSA), Discovery Partners Institute, and KAUST, where he worked on projects related to variational quantum models, 3D body reconstruction, sequence learning for epidemiological forecasting, and applications of physics-informed neural operators.

Hani's current research interests encompass machine learning workflow automation, physics-informed neural operators, AI for Science and chemistry.

Haoyang Li is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST) supervised by Prof. Xin Gao. His research focuses on developing AI-driven methods to integrate multimodal biomedical data, spanning spatial multi-omics, histopathology, and single-cell genomics, with the goal of decoding spatial heterogeneity in diseases and advancing diagnosis, prognosis, and biomarker discovery for personalized therapies. His research has been published in prestigious journals and conferences such as Nature Machine Intelligence, Nature Communications, Science Advances, Bioinformatics, IEEE TMI, and MICCAI. One of his first-authored papers in Nature Communications is recognized as Editor’s Highlight and the 50 best papers in 'Biotechnology and methods'. In addition, Haoyang had two internships at Yale University and Stanford University as visiting student researcher in 2023 and 2024. He has served as a teaching assistant and guest lecturer for the Ministry of Interior in Saudi Arabia, Saudi Aramco, and KAUST. Currently, he serves as an editorial board member and a guest editor for Molecular & Cellular Biomechanics and Biomedical Informatics.

Haoyang has a broad interest in developing AI models to address biological and healthcare problems. Recently, his research has focused on developing AI models for spatial biology, including spatial multi-omics, spatiotemporal omics, and pathological imaging, aimed at translational and clinical research.

Professional Profile

●       03/2023 - 09/2023, Research Intern, Stellantis & IMT Atlantique

●       05/2022-09/2022, R&D Intern, Invisensing

●       06/2021-08/2021, Research Intern, Institut Photovoltaïque d’Île-de-France

Education

● 01/2024 – Present, Ph.D. student in Photonics Lab, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.

● 09/2022 – 12/2023, Second Master’s degree in Optical Networks and Photonics Systems, Université Paris-Saclay & Institut Polytechnique de Paris, Palaiseau, France.

●09/2020 – 12/2023, Engineering degree of Theoretical and Applied Optics, Institut d'Optique Graduate School - Université Paris-Saclay, Palaiseau, France.

●09/2017 – 06/2021, Bachelor of Science and Engineering in Photoelectric Information Science, Huazhong University of Science and Technology, Wuhan, China.

• Fiber Optic Sensing
• Optoeletronics
• Photonics

He received his M.S. degree in Computer Science from Shenzhen University in 2022, where he was honored with the China National Scholarship and Outstanding Graduate Award. In 2022, he interned at Jarvis Lab, Tencent, and was a visiting student at Norwegian Biometrics Laboratory (NBL), Norwegian University of Science and Technology (NTNU). In 2024, he joined Meta AI as a research scientist internship. He has first-authored more than ten papers in top-tier journals and conferences. His work was recognized as the best paper in the NeurIPS 2023 workshop. He is the reviewer for CVPR, ICCV, ECCV, ICML, AAAI, and MICCAI. His recent research interests primarily focus on generative models, particularly their efficiency and security aspects. His long-term goal lies in making the learnable systems reliable, responsible, and explainable..

Deep Generative Models, XAI, Efficient AI and Responsible AI.

Haozheng HE is currently a MS/Ph.D. student at the Sensors Lab, in the CEMSE, King Abdullah University of Science and Technology (KAUST). He received the Bachelor of Engineering degree in Integrated Circuits and Systems from the University of Electronic Science and Technology of China, Chengdu, China, in 2023.

His research lies in Computer Architecture, Embedded Systems, Artificial Intelligence and FPGA

Heng Wang is a Ph.D. Candidate in Electrical and Computer Engineering of King Abdullah University of Science and Technology (KAUST), where he specializes in nanofabrication, lithography, and nanodevice processing. He earned his bachelor's degree in Microelectronic Science and Engineering from the University of Electronic Science and Technology of China (UESTC). During his academic career, he developed strong hands-on experience in cleanroom processes and supported collaborative research in advanced electronics and quantum devices.

My research focuses on the development of graphene-based geometric diodes for  terahertz (THz) rectennas, aiming to enable efficient high-frequency energy harvesting and detection. I specialize in nanofabrication techniques such as electron beam lithography  to realize ultra-small, high-performance devices. My work also integrates cleanroom process optimization and AI to advance next-generation nano devices.

Hikmatullo Ismatov earned a Bachelor's degree in Applied Mathematics and Computer Science from Lomonosov Moscow State University (2017-2021). He joined KAUST as an MS/PhD student in 2023. Before starting his graduate studies, Hikmatullo completed an internship at KAUST in the same year.

Hikmatullo Ismatov's research centers on nonlinear PDEs, particularly the Infinity-Laplace equation. This class of equations has significant applications in understanding various optimization problems and phenomena, such as tug-of-war games and image processing. His work aims to contribute to the theory and applications of nonlinear PDEs, particularly through rigorous mathematical analysis and computational approaches.

Hongxian Yi is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). Hongxian obtained his thesis-based M.S. in Computer Science from KAUST in Dec 2020 and his B.S. in Computer Science and Technology from Shandong University in 2018. He has also studied at Beijing Institute of Technology and Chung-Ang University as an exchange student. Before coming to KAUST, he worked as a Solution Architect Intern at Amazon Web Services, Inc.

His research focuses on computer vision, robotics, and autonomous driving systems, with particular emphasis on 3D perception and efficient computing for embedded platforms.

Started his academic path at Specialized Educational Scientific Center of NSU, Russia in 2015, then finished B.S. in Automation of Physical and Technical Research at Novosibirsk State University from 2017–2021, and now doing research in King Abdullah University of Science and Technology, Saudi Arabia while MS and PhD.

Besides his academic work he is an author of "Vectozavr" Youtube channel where he presented his research and some fun projects.

In 2021 he created an online school - vectozavr.ru of physics and math for game developers.

Jichen Lu is currently a Ph.D. student at Network Lab. He earned a Bachelor's degree in Computer Science from the Southern University of Science and Technology (SUSTech). He joined King Abdullah University of Science and Technology (KAUST) in 2021 and completed his Master's degree in 2023. His current research interests include optimization in computer networks, machine learning methods for networks, and AI applications on edge computing.

Jichen's research involves designing optimization algorithms for computer networks and distributed devices, considering multiple KPIs like energy consumption, latency, throughput, etc. He is also focusing on machine learning algorithms for networks and artificial intelligence applications on edge devices.