張馨文 Hsin-wen Chang

開發統計方法分析各類生物醫學數據

In the past five years, I have developed statistical methodology for analyzing various types of biomedical data, including functional data such as wearable device data, clinical trial data with time-to-event outcomes, and data from COVID-19 studies.

My research works are substantial because the methods I have developed are not only motivated by real data of current interest, but also involve solving challenging theoretical problems.

The results are accepted/published in three top journals in statistics within the last five years. In addition, I increase the impact of my research by developing statistical software packages and writing relevant guides/case studies, leading to publication in reputed statistical computing journal and software network.

More specifically, my 2019 Annals of Statistics paper proposes new theory that can push the field of nonparametric likelihood methods and order-restricted inference forward.

Furthermore, the methods in the paper have the potential of practically influencing the analysis of non-inferiority clinical trials, which are increasingly popular for identifying safer and/or more cost-effective medical treatments.

My 2022 Journal of the Royal Statistical Society: Series B paper is expected to have high impact at the intersection of nonparametric likelihood methods and functional data analysis.

It can also have great practical impact on how researchers handle many situations involving functional data with discontinuities in the mean and/or covariance functions.

My 2023 The American Statistician paper can significantly impact the field of nonparametric inference in the presence of unknown sampling bias.

The proposed method can be valuable for observational studies that involve unknown biased sampling mechanisms, such as in the COVID-19 studies investigated in the paper.

得獎感言

I am very grateful for receiving the award. Looking back at the best works of mine in the past few years, I recall doing them while imagining each of them to be my last research work.

Because it was the last, I tried to devote all my love for research into them. I had those thoughts because I was not very confident, and I imagined my academic career would end once I got kicked out of my institute.

This award and my recent promotion did inject me with some confidence and peace of mind. I hope I can learn how to do great research with this new mindset, though, or whether I should discard this mindset in case it negatively affects my future research.

Because I sometimes forgot these issues, I wrote them here so that the future me could be reminded of them and do better. I thank the National College of Science & Technology again for the recognition.