Prof Alexandre Thiery

“My research team develops statistical methods for exploring and understanding large and messy datasets of various kinds. It is typically very difficult to extract a meaningful signal when the data is noisy, sparse, high-dimensional or evolving through time.

For example, in one of my ongoing projects, I use some of these newly developed methodologies to quantify and predict solar irradiance in Singapore. This is a very exciting and timely endeavour, given Singapore’s aim to increase solar energy deployment to 8% by 2020. I also leverage very similar algorithms in other unrelated projects, such as the analysis of single cell genomics data.

Together with colleagues from several institutes, I am currently involved in a long-term collaborative effort to develop a better understanding of glaucoma, an eye disease which accounts for up to 40% cases of blindness in Singapore. I am exploring a dataset of unprecedented size, comprising three dimensional scans of human eyes. With advanced statistical methods and signal processing techniques, we are discovering new patterns and structures that give insights into the progression of the disease. Our findings have the potential to help clinicians detect glaucoma at earlier stages of the disease, and better understand the mechanisms underlying the evolution of this irreversible disorder.

Research in computational statistics lies at the intersection between theoretical statistics, mathematics, signal processing, and other areas of science. While it is challenging to stay relevant in this quickly evolving field, it also offers many opportunities to build connections between disparate theories. This is what drives me in the field. “