Research Students

Noppamas Yolai, also known as Pop, is actively involved in a research project that employs finite element modeling to investigate the impact of different types and shapes of microneedles on the activation of antigen-presenting cells (APCs), which play a vital role in initiating an adaptive immune response. Along with analyzing the impact of APC activation, she also evaluates the mechanical strength of polymer microneedles, aiming to enhance their ability to withstand the compressive forces exerted during skin insertion. Noppamas is motivated to develop innovative microneedle technology that can provide efficient and safe drug and vaccine delivery methods. Her research is expected to make significant contributions to the field of microneedle technology and improve healthcare outcomes.

Pikkanet Suttirat is currently focused on utilizing machine learning with wearable device sensors to develop a system that can provide early warning alerts for respiratory infection events, even before the onset of symptoms. He is proficient in both supervised and unsupervised approaches to machine learning for classification. He has experience with traditional classification algorithms such as Logistic Regression, K-Nearest Neighbor, and Random Forest. Additionally, he is also working on using machine learning techniques to identify risk factors associated with leptospirosis outbreaks in Thailand.  

Tanakorn's current research focuses on investigating the transmission of infectious diseases across complex networks and analyzing the impact of RT-PCR, RT-LAMP, and ATK-based testing on disease dynamics. He is also developing a disease transmission model that combines data on reported infections and viral load in wastewater to forcase the disease transmission dynamics and inform policy decisions.

Chalermchai Tongbai is dedicated to the development and design of microneedles. His primary focus is on engineering microneedles that can effectively and safely penetrate the skin while delivering drugs or vaccines with high efficiency. His work is motivated by the numerous benefits of microneedle technology, such as reduced discomfort and increased patient compliance, when compared to traditional injection methods. Chalermchai's research aims to contribute to the continued advancement of microneedle technology to improve healthcare outcomes for patients.

Natcha's research is dedicated to developing epidemic models for simulating the transmission of infectious diseases, aiming to deepen our understanding of transmission dynamics and assess intervention effectiveness. Her research revolves around developing evolutionary epidemic models tailored to simulate the spread of COVID-19 in Thailand, with the hope of shedding light on the disease's transmission mechanisms and identifying effective intervention strategies. 

Thanchanok Lincharoen's research interests lie in the transmission dynamics of infectious diseases, with a specific focus on understanding how face masks affect airborne transmission. For her Master's thesis, she investigates the effectiveness of face masks, physical distancing, and improving air ventilation in reducing SARS-CoV-2 transmission in indoor settings.

Sumet Khumphairan is a Ph.D. student at Heidelberg University. His research focuses on developing dynamical models in infectious disease ecology using a combination of mathematics and machine learning.