I’m a machine learning researcher and software engineer with expertise in neuroscience, immunology, and bioinformatics. I’m currently a Ph.D. Candidate in Computer Science at Northeastern University, where I’m co-advised by Deniz Erdogmus, Robin Walters, and Jan-Willem van de Meent. My research focuses on techniques for reducing the amount of calibration data required to train BCI models, and reducing the performance gap between training and test subjects. Some highlights of my work include:

  • Regularization techniques for learning subject-invariant representations
  • Contrastive learning and data augmentation strategies to extrapolate to unseen gesture combinations
  • Error-augmented model feedback to train human subjects

I’ve been funded by a long-term research contract with Meta Reality Labs, in which we developed techniques to use electromyography (EMG) for gesture recognition and human-computer interfaces. Previously, I completed two internships at Mitsubishi Electric Research Laboratories (MERL) under the supervision of Dr. Ye Wang and Dr. Toshiaki Koike-Akino, where I designed regularization techniques for subject transfer learning. I’ve also been a member of CAMBI, a cross-university collaboration focused on applying brain-computer interface (BCI) research for assistive communication.

Before starting my Ph.D., I worked for several years as a software engineer focused on the analysis of high-throughput genetic sequencing data. I received my MMSc in Immunology from Harvard Medical School in 2016, and my Bachelor’s in Neuroscience from Amherst College in 2013.

Selected Publications