For the next few weeks we will be featuring our 1st year doctoral students!
We hope everyone is able to get to know this talented and diverse new group of students.
My name is Rolando J. Acosta Nuñez and I am from San Juan, Puerto Rico. I just graduated from the University of Puerto Rico, in Humacao, with a B.S. in Computational Mathematics and a minor in Actuarial Sciences. I discovered the field of Biostatistics through the SIBS program at the University of Iowa three years ago and since then I have been involved in projects related to clinical trials, electronic medical records and big data; all of which gave me a sense of what my research interests are. Currently, I would like to explore a combination of the fields of epigenetics, GxE interactions, and big data. My goal is to someday amalgamate different data types (e.g. EHR, genomic, environmental, telecommunication , socio-economic, etc.) and create statistical methods in order to analyze them so that we can have a more holistic view of health, at different societal levels.
When I’m not thinking about school or research I spend my time reading books, like How to Create a Mind by Ray Kurzweil, and playing sports, specially baseball and basketball. Because of my Puerto Rican and Dominican roots, I love music, dancing, and Mofongo (if you have not tried it, you definitely should!). I am a fan of social justice, good conversations, politics, and tv series. I look forward to my time at Harvard and I’m eager to work on cutting-edge projects to solve real-life problems.
Hi, my name is Xiao Wu, and I am from Shenzhen, China. I recently received my master degree in Biostatistics from our department, before that, I studied both Law and Mathematics at Peking University during my undergraduate study.
My research interest includes casual inference, Bayesian statistics and statistical learning methods with their application in various fields, especially environmental health studies. Currently, supervised by Professor Francesca Dominici, I am participating in a research aiming to assess adverse health effects of long-term exposure to low levels of ambient pollution, I undertook the task of measurement error correction for exposure response models under casual framework. I extended the regression calibration for adjusting generalized propensity scores to adapt to categorical exposures with misclassification, which enormously enhanced the applicability of our method in environment researches. Beyond this, I intend to develop more innovative statistical methods to handle massive data with complex structures from multiple sources, bridge the causal effects between extrinsic treatments and health conditions, and ultimately benefit the health of people and societies worldwide.
Outside of school, I like traveling and photography. I enjoying exploring scenery and cultures in different areas, and recording them by landscape and documentary photos.
