About me

Current Work

I am an MS/PhD student at Columbia University in the department of Electrical Engineering, where I am an NSF Graduate Research Fellow. I conduct research in the Neural Acoustic Processing Lab, under the supervision of Dr. Nima Mesgarani. My work is at the intersection of neuroscience, machine learning, and biology. Specifically, I am interested in modeling the representations of language and sound in the auditory cortex with the goal of understanding how different types of sounds are processed through innate bottom-up processing and high-level cognitive information.

Undergraduate Experience

In 2020, I graduated from Johns Hopkins University with a B.S. in Biomedical Engineering, where I took part in a number of research projects (see my Publications and Projects pages for more details). I helped co-develop mvlearn, the first major open-source Python package for multiview machine learning. I worked on a spike inference algorithm based on FRI theory with Dr. Benjamín Béjar. I also conducted research in neuroscience under Dr. Kathleen Cullen analyzing the movements of vestibular schwannoma patients to understand the effects of neurectomy and neural compensation mechanism.

At JHU, I was also heavily involved in biomedical design teams, and I am very proud of the progress my teams made toward building products that can help people in the real world. OtoGlobal Health, a startup that I led for a little over a year, has developed a low-cost hearing screening device for low-resource settings. I also developed a low-cost device to treat postpartum hemorrhage in low-resource settings, (details here).

Outside School

Outside of academics, I love skiing, movies, and reading great fantasy and sci-fi novels. I volunteered as a ski patroller at a local ski resort during high school, where I was trained in emergency medicine.