MA Mentored Research* offers mentored learning and research opportunities for our MA Program in Statistics. Every year our students apply and are selected to partake in exciting projects spearheaded by lead researchers in their respective fields. Researchers at Columbia University, higher education institutions, non-profit organizations, and industry actively seek to engage our top-notch students.  Mentors include faculty, researchers, and industry experts, including some of our beloved alumni.  The projects attract students with diverse topic interests and professional goals. Previous project information can be viewed at MA Mentored Projects. 

*Most students opt to register for STAT GR5398: MA Mentored Research and receive academic credit for their work.  

Ali Turfah

Ali Turfah, MA’21

Biostatistics Ph.D. candidate, University of Michigan - Ann Arbor

“During the summer of 2020 I worked with Dr. Chunhua Weng's lab in the Department of Biomedical Informatics at Columbia University. While the main project I worked on was helping develop deep learning approaches for medical question/answering, the overarching theme of the work was extracting and representing medical evidence from randomized control trials publications. Not only was this an opportunity to get familiar with handling and processing different types of real-world data (unlike the clean purely numeric datasets we see in classes), it also exposed me to the "process of research;" formulating a problem, identifying both the current approaches and their shortcomings, implementing a solution, documenting and explaining that solution to people of varying technical backgrounds, etc. I returned to classes that Fall with a much better understanding of where my interests lie in the more computational side of biomedicine (which was very helpful when writing Statements of Purpose for PhD applications) as well as a concrete set of examples to ground and apply the more theoretical and abstract concepts that I came across in my remaining classes.”

Ruby Xiong

Ruby Xiong, MA’20

Biostatistics Ph.D. candidate, Vanderbilt University 

"I worked with Dr. Yulin Hswen from Harvard Medical School on a project with public health data in summer 2019. I got to witness how scientifically interesting questions are raised and participated in laying out research plans to tackle the problems. I was mainly responsible for data collection, customizing data analysis and manuscript preparation. The whole experience was refreshing, challenging and extremely rewarding. Not only did I learn that research needs extensive self-study on demand and is unlimited to one’s expertise, I also got to experience modifying existing data analysis methods to suit the purpose of application. Throughout the research project, I realized that I enjoyed the satisfaction of building up a complete real-life project using scientific methods, and that I would need more training in rigorous statistical inference to enable myself to validate the statistical methods being used. This experience greatly ascertained my determination of joining a PhD program."

Siddhanth Sabharwal

Siddhanth Sabharwal, MA‘20

Statistics Ph.D. candidate, University of Illinois at Urbana - Champaign

“During 2019 and 2020, I worked with Prof. Dalal on Identifying Ransomware Bad Actors in the Bitcoin Network. Our paper was recently accepted to a conference. I also collaborated with Profs. Lu and Krstovski in the project Corporate Climate and the Career Path of Women and Minorities. These projects gave me the opportunity to work directly with Columbia faculty on interesting research. If one is considering a PhD, mentored research can give you the proper exposure to how research is done in the real-world.”