In L@S 2017

In L@S 2017

In NIPS 2016 Workshop on Machine Learning for Education

In AAAI-17

In EDM 2016


Applied Scientist Intern

Amazon (June 2017-August 2017) - San Diego, CA

  • Worked in Transaction Risk Management Systems (TRMS) group.
  • Applied reinforcement learning.

Research Intern

Philips Research North America (May 2016-August 2016) - Cambridge, MA

  • Implemented Key-Value Memory Networks and Gated Attention Readers to classify diagnoses from medical notes
  • Participated in TREC Clinical Decision Support Track 2016

Research Assistant

ASSISTments Lab (2014-present) - WPI

  • Implemented a student model (knowledge tracing) with Long Short-Term Memory (LSTM) to predict the probability of a student making errors on given problems and measure student’s knowledge level on given skills.
  • Built a model for automated assignment grading tasks using memory networks and achieved state-of-the-art results on the Kaggle ASAP dataset.
  • Estimated the individual treatment effect for students using a deep learning model from the dataset collected from randomized control trials running inside ASSISTments.
  • Finished the Comprehensive Exam on topics including Bayesian optimization, Gaussian process, aggregation of crowdsourced labels, and estimation of the treatment effect.