Tag: SDG 4: PENDIDIKAN BERMUTU

Yogyakarta, June 26, 2025 — The AI Track of the Summer School continued today with a session designed to deepen participants’ understanding of the fundamental concepts underpinning machine learning algorithms, specifically Support Vector Machines (SVM). The learning focused on the mathematical intuition and visualization of how the algorithm works to form an optimal decision boundary. ... 

Yogyakarta, June 25, 2025 — The “Modelling 101” session, part of the MIDSEA Summer School series, was successfully held in the Arjuna Room at Alana Hotel Yogyakarta. The event saw participation from 13 individuals representing various countries, including Indonesia, the Philippines, Japan, and Thailand. Attendees came from diverse backgrounds, ranging from lecturers and researchers to WHO representatives and students with an interest in infectious disease modeling. ... 

Unlike previous sessions, the final meeting of the MIDSEA Summer School 2025 Simulation Track on Saturday, June 28, 2025, in the Bima Room at the MICC Building, The Alana Yogyakarta Hotel and Convention Center, was dedicated to project work with no new material presented. Professor Alexander Richard Cook, the track’s speaker from the Saw Swee Hock School of Public Health, National University of Singapore (NUS), divided the 14 participants into three groups, assigning a different problem to each. The main focus of this session was group discussions guided by Professor Cook. ... 

Yogyakarta, June 28, 2025 — Entering the fifth day of Track Inference in the MIDSEA Summer School, participants were treated to in-depth material on model selection presented by Dr. Akira Endo, Assistant Professor from the Saw Swee Hock School of Public Health. This session was one of the highlights of the day, as it directly discussed the foundations of statistical and epidemiological modeling. ... 

Entering the fourth day of Track Inference in the MidSEA Summer School 2025, the participants’ enthusiasm grew stronger, especially when entering one of the key sessions: Bayesian Parameter Estimation for Transmission Models. This session provided in-depth learning on how modern statistical approaches can be applied to understand and predict the spread of infectious diseases. ... 

The “Modeling 101” session, part of the MIDSEA Summer School series of activities, was successfully held at the Arjuna Room, Alana Hotel Yogyakarta. The session featured three main speakers: Dr. Hannah Clapham from the Saw Swee Hock School of Public Health, Prof. Jomar Fajardo Rabajante from the University of the Philippines Los Baños, and Dr. Wirichada Pan-Ngum from the Mahidol-Oxford Tropical Medicine Research Unit (MORU). The three speakers presented complementary materials on the fundamentals of modeling in the context of infectious disease epidemiology and its application in public health policy. ... 

On the fourth day of the Track AI MIDSEA Summer School 2025 series of activities, participants explored the application of Reinforcement Learning (RL) in the context of infectious disease intervention. The first session began with an introduction to the basic concepts of RL, where participants learned about the main structure of RL agents, including the state, action, reward, and policy components. This explanation was presented visually using interactive simulations to facilitate understanding. ... 

Following the discussion of static network models on Wednesday, June 25, 2025, the fourth meeting of the Simulation Track MIDSEA Summer School 2025 at the Bima Room, MICC Building, The Alana Yogyakarta Hotel and Convention Center focused on dynamic network models for the spread of infectious diseases. The track began with a discussion of the program code for the static network model problem provided the previous day by Prof. Alexander Richard Cook, Deputy Dean for Global Health at the Saw Swee Hock School of Public Health, National University of Singapore (NUS). Following that, as an introduction to the fourth meeting’s material, Prof. Cook explained that the fundamental difference between this model and the static network model is the change in the vertices or edges of the network graph. ...