Profiles

Hanchen Gan received the M.S. degree in microelectronics from the Institute of Microelectronics, Chinese Academy of Sciences (IMECAS), Beijing, China, in 2024, where he was affiliated with the National Key Laboratory of Integrated Circuit Manufacturing—3D Integration and System Packaging Laboratory. 
From March to October 2024, he worked at Cadence as a Product Validation Engineer. He worked in the CPG Group, validating the Clarity 3D full-wave electromagnetic solver. From November 2024 to August 2025, he was a visiting student with the GBDTC Electromagnetic Informatics Lab at the University of Technology Sydney (UTs).

 

Hanchen’s research interests span antenna design (antenna-in-package (AiP), mmWave phased arrays, base-station antennas, transmissive metasurface antennas) and semiconductor advanced packaging (2.5D/3D packaging，signal and power integrity, die-to-die (D2D) interconnects for chiplets).

Hang Lu is a final-year Ph.D. student in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), working in the Photonics Laboratory under the supervision of Prof. Boon S. Ooi. Hang has published in Light: Science & Applications, npj Nanophotonics, and APL Photonics, with her work featured as a cover article in the IEEE Journal of Selected Topics in Quantum Electronics. She also has experience in designing augmented-reality (AR) display systems and is broadly interested in advanced photonic integration and device–application co-design.

Hang's research focuses on engineering optoelectronic devices and photonic integration circuits for applications in optical communication, illumination, and hardware security. She has hands-on experience in optical design and modeling, nanofabrication, and experimental device prototyping, and has led the development of integrated optoelectronic devices and chips for secure and scalable photonic applications.

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.

• Sep 2021 – Jun 2025

  B.S. in Electronic Science and Technology,

  Beijing University of Posts and Telecommunications (BUPT), Beijing, China

• Sep 2025 – Present

  MS/PhD Student in Electrical Engineering,

  King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

Photonics and Optoelectronics

Hao Liu is a Ph.D. candidate in Computer Science (CS) at King Abdullah University of Science and Technology (KAUST), supervised by Professor Suhaib Fahmy and working in Accelerated Connected Computing Lab (ACCL) research group. He received his Bachelor's degree in Electronic and Information Engineering and his Master's degree in Cyber Science and Technology from Beihang University (BUAA, formerly Beijing University of Aeronautics and Astronautics), Beijing, China, in 2019 and 2021, respectively.

In addition to his research activities, Hao actively contributed to teaching and academic training. He has served as a Teaching Assistant for CS256: Digital Design and Computer Architecture at KAUST, supported the ECE 265P AI Training Program for the Saudi Ministry of Interior.

His research primarily focuses on efficient deep neural network (DNN) inference across the edge–near-edge–cloud continuum, covering CNNs, Vision Transformers, and LLMs. His research interests include model splitting, small–large model collaboration, LLM speculative decoding, model compression, and reconfigurable computing systems. 

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 research scientist internship where he contributing to the development of large-scale foundation models, including autoregressive diffusion and LLM-driven multimodal systems. Haozhe Liu is (co-)first author of over 10 papers in top-tier venues, with more than 1,000 citations. He has participated in large-scale pre-training efforts, scaling models across thousands of GPUs, with research outcomes integrated into commercial products. 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.

Haozhe's research focuses on multimodal generative models, particularly image and video generation, with the long-term goal of developing Physical AI and world models.

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

Hasan Abed Al Kader Hammoud is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), advised by Prof. Bernard Ghanem. During his Ph.D., he also completed research internships at the University of Oxford and Samsung Research UK. Hasan received his B.E. in Electrical and Computer Engineering from the American University of Beirut and his M.S. from KAUST. He is currently a Member of Technical Staff at OpenAI.

Hasan's research focuses on practical machine learning, with an emphasis on continual and online learning, efficient adaptation, self-supervised and multimodal representation learning, large language models, and trustworthy AI.

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.

Hussain Al Abdulaziz is a PhD candidate in Applied Mathematics and Computational Science at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Diogo Gomes. He joined KAUST in August 2021 and received his master's degree in May 2023, with a thesis titled Mass-Preserving Gradient Flows. He began his doctoral studies in June 2023.His research focuses on mean-field games, gradient flows, nonlinear partial differential equations, numerical methods for mean-field games, and mathematical modeling.

Mean-field games, gradient flows, nonlinear partial differential equations, numerical methods for mean-field games, monotonicity methods, and mathematical modeling.

Ibrahim Alsayoud is an M.S./Ph.D. student at King Abdullah University of Science and Technology (KAUST). He obtained the degree of Bachelor of Science in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in 2021.

Photonics and optoelectronics, Fiber-optic sensors

Ilies Benhabbour is a senior Ph.D. student with an international academic and research background spanning France, Germany, and Saudi Arabia. He earned his bachelor's degree from UVSQ and a master's degree from Eurecom. His early work explored adversarial attacks in machine learning and explainable AI at iABG in Germany. He is currently pursuing his Ph.D. under the supervision of Prof. Marc Dacier, focusing on network middlebox interference.

Ilies has designed and deployed a distributed, reprogrammable framework for detecting and verifying network middleboxes, which he uses to study the impact of middleboxes, such as proxies, on HTTP protocols.

Imran is a Ph.D. student in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST) supervised by Prof. Shehab Ahmed Elsayed. He has published his works in such journals as IEEE Transactions on Sustainable Energy, IEEE Access and IEEE Open Journal of Power Electronics, as well as such conferences as IEEE International Symposium on Circuits and Systems (ISCAS) and IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) with a focus on developing novel methodologies and integration of AI, optimization, and advanced control methods to enhance the performance, reliability, and sustainability of power and renewable energy systems. He also received best paper awards in conferences. He completed his M.S. in Electrical and Computer Engineering at KAUST and his bachelors in Electrical and Computer Engineering at Aligarh Muslim University (AMU), India.

Israel's has experience in several advanced areas, including Voice Search Processing, Manifold Learning, Image Processing, Dimensionality Reduction, Optimization, and the mathematical foundations of deep learning. His primary objective is to develop professional, end-to-end technology solutions that integrate signal processing (both hardware and software), machine learning, MLOps, and robust back-end systems.

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.

Jiahao Wei is a M.S./Ph.D. student at the Photonics Laboratory at King Abdullah University of Science and Technology (KAUST). He obtained his Bachelor of Optoelectronic Information Science and Engineering from Southern University of Science and Technology (SUSTech) in 2024. During his undergraduate studies, he primarily researched quantum dot light-emitting diodes (QLEDs). From Sept. to Dec. 2024, he conducted academic visiting at Hong Kong University of Science and Technology (Guangzhou).

Photonics, Optoelectronics

Jian Shi is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), where he conducts research under the supervision of Prof. Peter Wonka. Before joining KAUST, Shi earned an M.Sc. in Cloud Computing with Distinction (First-Class Honours) from University of Leicester and a bachelor's degree in Information Management and Information Systems from Zhengzhou University of Aeronautics. His professional experience includes research positions at NEC Laboratories China, The Chinese University of Hong Kong, and GE Power, where he worked on a broad range of machine learning and computer vision applications.

Shi has established a strong publication record in leading journals and conferences in artificial intelligence and computer vision. His work has appeared in premier venues including ACM SIGGRAPH, ICML, CVPR, ICCV, ECCV, IEEE TPAMI, and ICRA. His recent research contributions include advances in stereo video generation, depth estimation, anomaly detection, human keypoint estimation from LiDAR data, and the integration of geometric reasoning into generative AI systems.

In addition to his academic research, Shi is a co-founder and core maintainer of Kornia, one of the world's most widely used open-source differentiable computer vision libraries built on PyTorch. He has also served as a mentor and organization administrator for Google Summer of Code, helping foster open-source innovation in computer vision and machine learning.

Among his notable achievements, Shi received the KAUST Dean's List Award in 2025 in recognition of his academic excellence and research accomplishments. He is also an inventor on multiple patent filings and has delivered invited talks on emerging topics such as agentic computer vision and open-source AI infrastructure. Through both his scholarly contributions and open-source leadership, Shi continues to advance the development of next-generation vision systems that enable machines to perceive, understand, and synthesize the three-dimensional world.

Shi's recent work explores the intersection of geometry and generative AI. His research investigates stereo video synthesis, disparity learning, diffusion models, multi-view reconstruction, and high-fidelity 3D scene understanding. By incorporating geometric constraints into learning-based systems, he seeks to improve robustness, realism, and spatial consistency in next-generation AI vision models.

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.

Jinane Bazzi received her Bachelor's degree in Computer and Communications Engineering from the American University of Beirut (AUB) in 2021 with High Distinction. She earned her Master's degree in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST) in 2023. During her graduate studies, she was a visiting researcher at the University of California, Irvine (UCI), and a research intern at IBM Research, Switzerland. She is currently pursuing a Ph.D. in Electrical and Computer Engineering at KAUST.

Jinane's research lies at the intersection of hardware architecture and deep learning, with a focus on compute-in-memory (CIM) techniques for efficient AI acceleration.

Jinjie Mai is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), advised by Prof. Bernard Ghanem. Jinjie received his bachelor’s degree in Engineering from School of Data and Computer Science, Sun Yat-sen University, China in 2020. He was a visiting student at KAUST after graduation and then joined KAUST in 2022. His publications have appeared in CVPR, ICCV, ECCV, and SIGGRAPH Asia.

His work investigates how geometric, spatial, and temporal structure can be recovered from imperfect visual observations, with interests including 3D reconstruction, camera pose estimation, visual correspondence learning, spatial reasoning, visual memory from long-form video, and 4D scene understanding. He also develops controllable video generation and editing systems that maintain spatial consistency and temporal coherence while responding to user instructions, reference content, and real-world events. By bridging visual perception and visual generation, his research aims to create intelligent systems that can both understand dynamic environments and interact with them in a coherent, context-aware, and user-driven manner.

Joao Vitor Cordeiro de Brito is a PhD student in the Statistics Program at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor David Bolin.

Prior to KAUST, he obtained his degree in Applied Mathematics from the Federal University of Rio de Janeiro (UFRJ), Brazil. During his bachelors, João did undergraduate research on ergodic aspects of problems from number theory, and was awarded with honors/prizes in national and international contests in mathematics.

His research interests lie primarily at the intersection of spatio-temporal statistics, mathematical physics, and Bayesian computational methods, with a particular focus on data defined on networks, which are modeled as metric graphs.