Research Center on Artificial Intelligence and Sustainability
Research Field
Pao-Ann Hsiung, Ph.D., received his Ph.D. in Electrical Engineering from the National Taiwan University, Taipei, Taiwan, ROC, in 1996. Since August 2007, he has been a full professor at the National Chung Cheng University (CCU), Taiwan. Currently, he is the Chief Information Officer, CCU, the Director of the Research Center on AI and Sustainability, CCU and the Director of the Taiwan-India Joint Research Center on Artificial Intelligence at IIT Ropar and CCU. Previously, he was the department chair, Dean of International Affairs, and the Director-General of Intelligence Technologies Department, Chiayi City Government. He has published 300 papers in international journals and conferences. He was the recipient of the 2010 CCU Outstanding Research Award, 2001 ACM Taipei Chapter Kuo-Ting Li Young Researcher, and 2004 CCU Young Scholar Research Award. He helped Chiayi to achieve 2018 TOP7 Smart City in the Intelligence Community Forum world competition. He has also helped obtain financial budget of NT$300 million dollars. Dr. Hsiung is a fellow of the IET, a senior member of the IEEE and the ACM, and a life member of the IICM. Dr. Hsiung’s main research interests include smart system design, deep learning, AIoT, smart city technology such as smart traffic and smart grid, embedded real-time system design.
The Research Center on Artificial Intelligence and Sustainability is located at room 509, Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan. It was established in March 2022. The research center is currently being led by Professor Pao-Ann Hsiung. We are committed to the research on the design of smart systems, including applications to smart traffic, smart grid, environment protection, and biomedical diagnosis. Currently, we have three research projects undergoing inclouding Design of Integrated Command and Control Center for Sustainable Smart Cities, Taiwan-India Joint Research Center on Artificial Intelligence and Smart Observer : Distant-Water Fishermen Labor Rights and Safety Management. We have achieved several research results disseminated in more than 300 publications.
1. Multimodal Federated Learning for Sustainable Smart Cities (using FedMultimodal framework)
2. Digital Twin Design with Scenario Planning for City Disaster Management (with AI-based Management)
3. Situational Awareness for Urban Environment and Traffic (using CityGML)
4. City-based Carbon Emission Estimation (need to develop an APP or website, along with web parser and Python programming)
5. Open Source Contribution: Automatic Deployment of AI models based on Kubernetes, Kubeflow and Kserve (on GitHub)
6. Image-based Multiple Person Tracking Across Multiple Cameras (Tracking of Distant Water Fishermen)
7. AI and Image/Video-based Quality Monitoring of Water Bodies (such as lakes, rivers, etc.)
8. Classification of Movement Disorders in Parkinson's Disease (based on UPDRS)
Current Research Projects:
- Design of Integrated Command and Control Center for Sustainable Smart Cities
- Taiwan-India Joint Research Center on Artificial Intelligence
- Smart Observer : Distant-Water Fishermen Labor Rights and Safety Management
We have achieved several research results disseminated in more than 300 publications.
Ph.D., Electrical Engineering, National Taiwan University, Taiwan
B.S., Department of Mathematics, National Taiwan University, Taiwan
5 Vacancies
Job Description
The Internship Plan is as follows, subject to change based on individual qualifications:
1st month: Collection of real and online datasets
2nd month: Model design, training, and validation
3rd month: Application and paper writing
Preferred Intern Education Level
- Currently enrolled or graduated Master Students
- Currently enrolled PhD Students
Skill sets or Qualities
- Python Programming
- Deep Learning
- C/C++ Programming (optional)
1 Vacancy
Job Description
EE students are preferred for this internship.
Preferred Intern Education Level
PhD candidates preferred.
Skill sets or Qualities
CMOS circuit design experience