Profiles

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

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.

Jinane received her Bachelor's Degree in Computer and Communications Engineering from the American University of Beirut (AUB) in 2021, with High Distinction.

From June 2020 to June 2021, she was a visiting student at the Communication and Computing Systems Laboratory (CCSL) at KAUST, in collaboration with the University of California-Irvine (UCI).

Her research interests focus on in-memory computing for deep learning hardware acceleration to enhance the efficiency and performance of neural network computations.

José Maria earned his Bachelor of Engineering in Electronic Engineering, with a minor in Telecommunications, from Universidad Peruana de Ciencias Aplicadas (UPC) in Lima, Peru, in 2018. During his undergraduate studies, he was awarded a partially funded scholarship in 2013. In 2018, he received funding for a research project through the VII Annual Research Incentive Competition at UPC, which led to the publication of a paper and a presentation at the XXII Symposium on Image, Signal Processing, and Artificial Vision (STSIVA) in 2019.

José Maria began his career with internships at IBM Peru, first as a Computer Specialist and later as a Software Developer. His interest in the Internet of Things (IoT) grew, leading him to become a speaker at various universities, where he taught IoT and Machine Learning. He focused on using single-board computers to connect multiple devices and leverage environmental data. José Maria has worked on several research projects at UPC, including a notable Digital Image Processing project aimed at developing a reliable method for diagnosing health issues in coffee plants using machine learning in Python, providing early diagnosis tools for cultivators.

José Maria is proficient in Python, Java, and machine learning technologies. His research interests lie in leveraging machine learning to enhance communication methods, with a focus on coding and modulation, Smart Grid technologies, and satellite networks. He is passionate about the Internet of Things (IoT) and has shared his knowledge as a speaker at various universities, teaching IoT and Machine Learning. His sessions emphasize the use of single-board computers for data-driven device connectivity, showcasing practical applications of these technologies.

Karim is a graduate from Bauman Moscow State Technical University. He received a specialist degree in a field of electrical engineering (2014 – 2020), with a focus on radars and wireless communications. He worked at part-time job as embedded systems and DSP engineer for 2.5 years. After that he had internship in summer of 2019 at Huawei Russian Research Institute (RRI) and after graduating from university, he worked at Huawei RRI for 1 year. During his job he improved receiver’s sensitivity applying some convex and non-convex optimization approaches and provide some dimensionality reduction approaches for system identification.

Nowadays Karim works in topics related to Joint Sensing And Communication (JSAC), quantum computing and communications over unlicensed spectrum.

Adaptive algorithms in wireless communications, Radar signal processing and machine learning. Quantum computing.