Biomedical Interest
Analysis of sleep data of mood disorder patient
I aim to analyze mood disorder patients' sleep data by using a mathematical tool. Various sleep indexes showed a relation with mood episodes in mood disorder patients. However, which aspect of sleep influences the mood episode is unclear. I use machine learning and mathematical tools to reveal key features that determine the mood episode.
Human circadian phase estimation using mathematical model
Dim Light Melatonin Onset (DLMO) is the golden standard of the human circadian phase. However, it requires high effort and cost as it needs an hourly sample of saliva. I'm using mathematical modeling to reduce this effort and time to do DLMO experiments.
Mathematical Interest
Variance reduction in biochemical reaction networks using control theory
The property of maintaining the specific states against the perturbation is called robust perfect adaptation (RPA) and can be observed in many biological systems. It is well known that an antithetic integral feedback (AIF) controller can achieve this desired property. However, the biggest drawback of this controller is an increased variance, which may distort its performance. I'm recently developing new tools that can reduce the variance and maintain that variance against the perturbation.