Meet Our New PhD Students!
We’ll be featuring mini-profiles of our new PhD students over the next few weeks. We look forward to welcoming them into our community!
Phuc Quang Vu
Hello! I am Phuc, and I am from Vietnam. Back there, I began my undergraduate in Pharmacy, hoping for a stable career, but I stayed through it for its impact on public health. In my junior year, after deciding that being a clinical pharmacist was not how I wanted to spend my life, I rekindled my passion for Math by teaching myself calculus, linear algebra, and Python through online textbooks and courses. Combining this newly rediscovered interest in Math with a background in Pharmacy, I pursued my MPH in Biostatistics at NYU.
At NYU, I worked with Dr. Rebecca Betensky on theoretical derivations and simulations to estimate type I errors of a post hoc approach for multiple hypothesis testing.
This experience sparked my interest in research as I enjoyed learning about the new field by reading articles, working through mathematical problems, and making sense of simulation results. In the end, I learned to be patient with myself and embrace my struggles.
Meanwhile, my self-learning journey did not stop. I read and summarized textbooks in real analysis, statistical learning, causal inference, and longitudinal data analysis. The more I learn, the more fascinated I become with the possible applications of causal inference from the ever-increasing amount of observational data we collect today. Nevertheless, these opportunities come with the challenges of highly correlated and often incomplete data sets. Therefore, I look forward to expanding my toolkits to handle clustered, sparse, and missing data during my PhD program.
Beyond academics, I find people, in general, fascinating. As I lived in multiple cities and met people from all walks of life, I learned to appreciate the lessons hidden in the stories of others and the precious fleeting moments we share in our limited time on earth. When not taking things too philosophically, I enjoyed a good romantic sitcom like How I Met Your Mother or a classic movie like V for Vendetta.
Keyao Zhan
Hello! My name is Keyao Zhan. I was born and raised in Huainan, a small town on the south bank of Huai River in China. I studied mathematics and statistics at the School of Mathematical Sciences in Peking University, and obtained my B.S. in Statistics in June, 2024. Coming to Harvard is my first time studying abroad, and I am very much looking forward to my new life in Boston!
In the first two years of studying at the School of Mathematical Sciences in Peking University, I was constantly learning various mathematical courses in analysis, algebra, and probability. It wasn’t until a course named Mathematical Statistics in my sophomore year that a new field of statistics opened up for me.
It made me realize that abstract mathematical theories could be applied in this way to practical problems and real-world data. I first conducted research in deep learning theory and reinforcement learning with professors in Peking University. While I gained lots of knowledge and experience in modern machine learning, I found playing with theoretical bounds and algorithms is not that attractive to me. Then in my junior year, I did research with Prof. Molei Liu from the Department of Biostatistics in Columbia University. We studied transfer learning with multi-source heterogeneous data and distributional robustness, which is largely inspired by the analysis of EHR data. I was also involved in another project regarding improvement of peer review mechanism using statistical methods with Prof. Weijie Su from the Wharton School of University of Pennsylvania. These experiences ignited my passion for biostatistics, where I can touch and explore lots of real-world data, and directly use statistical methods we propose to address practical problems.
I believe the PhD journey at Harvard will be very exciting and rewarding. I hope to gain more experience in developing statistical methodology that can account for pervasive challenges like high- dimensionality, robustness and data-privacy in a variety of contexts. I am also extremely excited about exploring and studying various subfields in biostatistics!
Outside of my academic pursuits, I love playing the piano and reading science fictions. I also like to play tennis and ping-pong in my free time. I enjoy spending time with my friends, so I hope to make good friends here. I’m super looking forward to meeting everyone!
