August 20, 2025: A total of 117 students from Shibaura Institute of Technology (Japan), Kasetsart University (Main Campus, Thailand) and Kasetsart University (Sriracha Campus, Thailand) participated in the Global Project-Based Learning (gPBL) Program hosted by the School of Engineering and Technology (SET) under the theme “AI Power for Sustainable Engineering”. The visiting students were accompanied by faculty and academic supervisors from their respective institutions.
Opening Ceremony and Welcome Remarks
The program commenced with inspiring welcome remarks from Dr. Geoff Chao, Head of the Civil and Infrastructure Engineering (CIE) Department, who emphasized the wonderful collaboration between universities, highlighting how this partnership creates an invaluable intercultural learning platform for students from different countries. “gPBL is our shared classroom across borders: by putting AI in students’ hands, we accelerate safer, smarter, and more sustainable engineering,” said Dr. Chao.
The opening ceremony was further enriched by a meaningful gift exchange between the participating universities, symbolizing the spirit of international academic cooperation and friendship.
The gPBL program aimed to explore the transformative applications of Artificial Intelligence in Civil Engineering. Participants collaborated to develop a shared understanding of how AI is revolutionizing traditional engineering practices, from blueprint design to algorithmic solutions, fostering international cooperation in engineering education and cutting-edge technology integration.
During the program, students engaged in different collaborative learning activities. The keynote lecture “From Blueprints to Algorithms: How AI is Transforming Civil Engineering” by Dr. Chutiporn Anutariya, Faculty, ICT, provided comprehensive insights into AI’s revolutionary impact on civil engineering, covering applications from generative design and predictive maintenance to safety monitoring and digital twin technology. The presentation highlighted how AI enhances design efficiency, improves construction site safety, reduces costs through predictive analytics, and promotes sustainable infrastructure development. These interactions provided valuable opportunities for cross-cultural exchange and academic enrichment through international collaboration in engineering education. Between sessions, the master of ceremonies kept the energy high with fun Q&As, mini and prizes.
Laboratory Visit Activities
The main program activities focused on technical learning through laboratory experiences and interactive sessions. Students participated in comprehensive laboratory visits to four specialized facilities, each offering unique insights into different aspects of engineering research and practice:
Computer Science (CS) Hands-on Activity
Students participated in an engaging Decision Tree Masterclass, a 30-40 minute interactive session that provided hands-on experience with decision tree algorithms. Through a practical activity using images, participants learned how decision trees split data based on features such as size, habitat, and physical traits to arrive at accurate classifications. This practical approach simplified complex AI concepts while making the learning process both fun and relatable. By the end of the session, participants gained clear insights into how decision trees function in real-world problem-solving and data classification scenarios. The interactive format helped students understand the fundamental principles behind one of the most important machine learning algorithms used in engineering applications.
Geotechnical and Earth Resources Lab (GTE)
Students were given a comprehensive tour of the GTE laboratory facilities and participated in an innovative hands-on activity combining traditional soil testing with AI technology. They received a soil sample, which they mixed with water to create a soil-water mixture for moisture content analysis. Using AI image recognition technology, students determined the moisture content of their samples through visual analysis algorithms. The AI-generated results were then verified using traditional sensor measurements, demonstrating the integration of artificial intelligence with conventional geotechnical testing methods. This activity showcased how modern AI applications are revolutionizing soil analysis and quality control in geotechnical engineering practice.
Structural Engineering Lab (STE)
Students engaged in a comprehensive hands-on experiment exploring fundamental concepts of structural dynamics, including natural frequency, time period, and structural stiffness in vibrating systems. Using a specially designed experimental model consisting of a concrete base, vertical rod, and adjustable masses, participants conducted forced and free vibration tests to understand how structures respond to dynamic loads. Students measured vibration characteristics using both traditional stopwatch methods and modern mobile applications to record acceleration data and analyze structural behavior. The experiment included varying mass configurations and excitation points to observe changes in amplitude, frequency, and damping characteristics. Through this practical experience, students gained valuable insights into earthquake engineering principles and how engineers design buildings to withstand seismic forces safely. This exercise was a demonstration of structural health monitoring research going on at AIT.
Water Engineering and Management Lab (WEM)
Students visited the WEM laboratory facilities with a special focus on the physical modeling laboratory, where they observed large-scale hydraulic models and experimental setups. The instructor provided detailed explanations of how physical modeling works in water engineering, demonstrating scaled-down versions of real-world hydraulic systems such as dams, spillways, and water treatment facilities. Students learned about the principles of similitude and how engineers use physical models to predict the behavior of full-scale water infrastructure projects. The visit highlighted the benefits of physical modeling in validating computational fluid dynamics simulations and optimizing design parameters before construction. Although no hands-on activities were conducted, students gained an appreciation for the role of experimental validation in water resources engineering and flood management systems.
Student Feedback
Students described the program as engaging and eye-opening. Many appreciated how AI concepts became clear through hands-on lab work and concise explanations, noting that the sessions were well-paced, practical, and relevant to real engineering challenges. They also highlighted the welcoming atmosphere at AIT and said they left more confident about applying AI in their studies and future careers.
Nuttanawat Pakkadthong (Thailand – Kasetsart University)
“Although I have had experience in lab works at Kasetsart University, I am very fascinated by AIT’s approach to incorporate the use of AI to simplify the work. This integration made it easier to understand everything that I have learned in my university and presented it in a more accessible way. I particularly enjoyed the WEM lab, especially the physical model laboratory where I got to know more about how a dam works. The information on physical modeling provided me with a deeper understanding of hydraulic engineering principles that complement my theoretical knowledge.”
Kanawat Chantapiriyapoon (Thailand – Kasetsart University)
“I got to know about what AI actually is and how we use it in our day-to-day life, even without us actually recognizing it. I learned about the transformation of AI through time and its evolution in engineering applications. To me as a Civil Engineer, it’s particularly fascinating as nowadays there are many technologies emerging in our field. Understanding these technologies is important to improve and simplify our work processes and enable us to be better engineers. The program opened my eyes to the potential of AI in solving complex engineering problems.”
Himawari Ohnuk (Japan – Shibaura Institute of Technology)
“Today was a good experience for me to visit AIT and explore all the different laboratories. In SIT, we perform laboratory work in the final years of our study only, so experiencing the laboratory work here at an earlier stage was very beneficial for me. I also enjoyed the welcoming environment here at AIT and am thankful for the gPBL program for providing me with the platform to collaborate with people from different nationalities and learn more about cultural diversity. This international exposure has broadened my perspective on engineering education and cross-cultural collaboration in academic settings.”
Closing Ceremony
The day concluded with a short quiz round and final remarks from Dr. Geoff Chao, who thanked faculty facilitators and student participants for building an environment where curiosity, rigor, and collaboration reinforce one another. As teams dispersed, many carried a shared takeaway: when students from different systems tackle the same problem, they not only learn faster—they learn to design for sustainability. The gPBL program turned the theme “AI Power for Sustainable Engineering” into live practice, strengthening ties among institutions committed to preparing engineers for a more intelligent, resilient, and sustainable built environment.
