Hi, my name is Sambit! 👋
I’m a Ph.D. candidate in the Department of Biomedical Engineering and Institute of Computational Medicine at Johns Hopkins. My research interests lie on the intersection of statistics, machine learning, and medicine.
At Hopkins, I’ve had the pleasure working with Joshua T. Vogelstein in the NeuroData lab. I work on developing methods for high-dimensional hypothesis testing, causal inference, and extensions of random forest. These methods are neatly wrapped in the hyppo and scikit-tree Python packages. I have also applied these methods to real data sets, including those from Bert Vogelstein and the Neurobehavioral Core at NIEHS (as a data science intern over the summer of 2023).
I completed my master’s degree (MSE) in Biomedical Engineering at Johns Hopkins in 2020. I was also an undergard at NC State in Biomedical Engineering and Biology while on the Goodnight Scholarship. There, I worked with Leslie Sombers, using electrochemistry to understand neural systems.
As a way to “pay it forward”, I run the Ramchandara Panda Scholarship Competition, which provides scholarships to local students in my family’s village in India and helps preserve local traditions for future generations.
In my free time, I like to read books and go on hikes!
Sambit Panda is a Ph.D. candidate in the Department of Biomedical Engineering at Johns Hopkins University, where he is advised by Dr. Joshua T. Vogelstein. His research focuses on the following topics: causal inference, hypothesis testing, neuroscience, and random forest extensions. He received a MSE in Biomedical Engineering from Johns Hopkins in 2020, and he received a BS in Biomedical Engineering and Biology from North Carolina State University in 2018. He received the Goodnight Scholarship in 2018 and the National Institutes of Health T32-a Grant in 2020. He has also reviewed papers for SoftwareX and SciPy (2020, 2021) and chaired for SciPy (2020, 2021, 2023).