Intelligent cyber-Physical Systems Lab
Research Field
Dr. Hojjat Baghban is an Assistant Professor in the Department of Artificial Intelligence at Chang Gung University, Taiwan, where he leads the Intelligent Cyber-Physical Systems Research Lab. He is the Principal Investigator of the National Science and Technology Council (NSTC)-funded project titled "Reliable Service Chain Orchestration in a Multi-Domain Edge Intelligence Ecosystem (Grant Number: 113-2222-E-182-001). He received his Ph.D. from National Yang Ming Chiao Tung University (formerly National Chiao Tung University), Taiwan. He has 19 years of experience in Computer Science Lecturing and Senior Researcher, and research project leader. His research collaborations involved multiple research groups in Taiwan, UK, EU, Brazil, and West Asia in edge-cloud computing and Intelligent network orchestration, focusing on the development of Next-Generation Networks. His recent research contributions include Artificial Intelligence solutions for optimizing Service Function Chains (SFCs) in 5G and distributed computing environments, such as the edge-cloud continuum. He has contributed to the design and development of edge capacity usage optimization and has proposed an Edge-AI-specific approach using Deep Reinforcement Learning. Additionally, Prof. Baghban has been investigating Generative Artificial Intelligence solutions in Edge Computing. His team has also worked on Edge Intelligence-enabled medical image classification to enhance data privacy in healthcare centers. Currently, Prof. Baghban is serves on the editorial board of the peer-reviewed International Journal of Networked and Distributed Computing. Dr. Baghban actively collaborates with several international technical communities and conferences. He is an organizing committee member of DataCom 2024 and FCP-2022 and was a member of the editorial team for DataCom 2022. Additionally, he is an Executive Committee Member of the IEEE Technical Committee on Cloud Computing (TCCLD) and serves as the Membership Director of IEEE TCCLD.
The Intelligent Cyber-Physical Systems Research Lab at Chang Gung University focuses on pioneering research at the intersection of Edge Artificial Intelligence (Edge-AI), Intelligent Network Service Orchestration and Optimization, and Generative AI in Edge Computing. Our lab explores cutting-edge AI-driven solutions to enhance the efficiency, adaptability, and intelligence of distributed computing environments, particularly within next-generation edge-cloud ecosystems. We aim to develop innovative service orchestration techniques that optimize resource allocation, network performance, and scalability. Additionally, our research delves into Generative AI methodologies, leveraging their potential to enhance decision-making, automation, and security in Edge-AI-powered systems. Through collaborations with academia, industry, and global research communities, we strive to advance the frontiers of intelligent cyber-physical systems, enabling smarter, more efficient, and autonomous digital infrastructures.
- Edge Artificial Intelligence (Edge-AI),
- Intelligent Network Service Orchestration.
- Foundation Models (FMs), including Large Language Models (LLMs)
- Multi-agent Systems and Dynamic Optimizations.
- Artificial Intelligence of Things
Dr. Baghban has been recognized for his outstanding contributions in research, academia, and technical leadership. He was honored with an Appreciation Award for his invited lecture talk at the Office of Industry-Academia Co-Creation, National Yang Ming Chiao Tung University, Taiwan. My research was further acknowledged with the Best Paper Award at the IEEE International Symposium on Cloud and Service Computing, in December 2016. As a Principal Investigator, I earned the Merit of the National Science and Technology Council (NSTC) funding. I have been an invited keynote speaker, delivering talks at prestigious international conferences, including the IEEE WOMOM 2024 (The 25th IEEE International Symposium on a World of Wireless, Mobile, and Multimedia Networks, Australia, June 2024) and the 2nd Mandalika International Multi-Conference on Science and Engineering (MIMSE), Indonesia, November 2023. My leadership extends to serving as an Executive Committee Member of the IEEE Technical Committee on Cloud Computing (TCCLD) and contributing as an Editorial Team Member for DataCom-2022 and FCP-2022. Additionally, he is a Guest Editor for the Special Issue "Mobile Cloud Computing in Wireless Networks and IoT" in the Sensors Journal under the Intelligent Sensors section. I am also serving as the editorial board of the peer-reviewed International Journal of Networked and Distributed Computing, further demonstrating his commitment to advancing research in networked and distributed computing systems.
- Ph.D. in Electrical Engineering and Computer Science, National Yang Ming Chiao Tung University (Former name National Chiao Tung University).
2 Vacancies
Job Description
The Intelligent Cyber-Physical Systems Research Group at Chang Gung University, Taiwan, is inviting international Master’s and Ph.D. students to apply for an internship opportunity focused on Deep Reinforcement Learning (DRL) for Edge Computing. We seek highly motivated researchers with expertise in Reinforcement Learning (RL) and Deep Learning, who are eager to contribute to cutting-edge research in intelligent resource management, optimization, and automation in edge computing environments.
(Note: Senior Undergraduate student who has experience in the mentioned filed are welcome)
Preferred Intern Education Level
- International Master’s or Ph.D. students in the related fields.
- Senior Undergraduate student who has experience in the mentioned filed are welcome
Skill sets or Qualities
- Proficiency in Python programming and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow). (for both position)
- Strong background in Large Language Models (LLMs) (for the 1st internship position).
- Strong background in Reinforcement Learning (RL), Deep Reinforcement Learning (DRL), (For the 2nd internship Position)