About

I am an Assistant Professor at the Mendoza College of Business at the University of Notre Dame. I recently defended my Ph.D. dissertation at the University of Massachusetts Amherst in the College of Information and Computer Science. At UMass I was a member of the Bio-NLP group, working with Dr. Hong Yu. My research interests are in Machine Learning and Natural Language Processing. I am particularly interested in model evaluation and quantifying uncertainty, as well as applications in biomedical informatics.

Prior to UMass, I worked as a software developer at Eze Software in Chicago and as an IT Audit Associate for KPMG. I received my Master's Degree in Computer Science at DePaul University, where I worked on projects in Computer Science Education and Recommender Systems.

Updates

  1. February 2020: Our abstract Bots versus Humans in Online Social Networks: A Study of Reddit Communities was accepted to Sunbelt 2020.
  2. November 2019: I successfully defended my Ph.D. dissertation, "Learning Latent Characteristics of Data and Models using Item Response Theory."
  3. September 2019: Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity accepted to appear at ASRU 2019
  4. August 2019: Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds accepted to appear at EMNLP 2019
  5. March 2019: Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds accepted as an extended abstract at the NAACL Shortcomings in Vision and Language workshop
  6. March 2019: Comparing Human and DNN-Ensemble Response Patterns for Item Response Theory Model Fitting accepted as an extended abstract at the NAACL Cognitive Modeling and Computational Linguistics workshop
  7. February 2019: Our paper on detecting hypoglycemia incidents in secure messages was accepted by JMIR