I am a PhD candidate in EECS, advised by Dr. Pete Szolovits in the Clinical Decision Making Group (MEDG). My current research focus is Natural Language Processing for healthcare applications, within the broader umbrella of Machine Learning for Healthcare. I have interests in multiple fields: 1) Semi-Supervised or Self-Supervised Learning, 2) Joint image-text modeling, 3) Information Extraction (pure NLP), towards grounding in the language domain.
My masters thesis focused on the task of relation extraction (an important component of Natural Language Understanding) and made commentary about issues of reproducibility. I experimentally demonstrated the drastic effects pre-processing and model architecture choice can have on downstream task performance. Showcasing results on multi-domain datasets reveals this problem is not limited to one field, but can have the most grave consequences for healthcare due to the cascading impact of errors in the domain.
I am a recipient of the Frederick (1953) and Barbara Cronin Fellowship at MIT and presented with the honor of being a Graduate Woman of Excellence. I completed my bachelors in Computer Science at Florida International University, and worked on projects related to Classical AI (Knowledge Representation) and named entity recognition (character recognition from folktales). I had the honor of being banner marshal for the Class of 2017 for the College of Engineering and Computing and named as the Outstanding Undergraduate in Computer Science in recognition of academic achievement and service to the department.
In my free time, I enjoy practicing and teaching yoga, photography, drawing and cooking (which is my new hobby!).