I am advised by Prof. Neil Heffernan and work in ASSISTments Lab to help develop and perform research within the adaptive online tutor.
My research interests are in application of deep learning, contextual bandits, and domain adaptation. I have applied deep learning models to solving various tasks (e.g. time-series prediction, text classification with memory networks, estimation of treatment effects using domain adaptation).
During summer 2016, I interned at Philips Research North America advised by Sadid Hasan. During summer 2017, I interned at Amazon as Applied Scientist mentored by Aaron Fraenkel in Transaction Risk Management Systems (TRMS) group.
I expect to finish my Ph.D. in May 2018 and am seeking a full-time position in machine learning or related areas.
PhD, 2013-2018 (expected)
Worcester Polytechnic Institute
South China University of Technology
Amazon (June 2017-August 2017) - San Diego, CA
Philips Research North America (May 2016-August 2016) - Cambridge, MA
ASSISTments Lab (2014-present) - WPI
Implemented automated essay grading system in Tensorflow using memory networks.
Implemented key value memory networks from Key-Value Memory Networks for Directly Reading Documents in Tensorflow
Implemented deep knowledge tracing from Deep Knowledge Tracing and Going Deeper with Deep Knowledge Tracing
This app helps teachers in Google Classroom to access to educational content that used to be available at assistments.org
This infrastructure allows distributing educational content available at assistments.org to teachers and students who don’t have an account and to embed content into any other learning management systems (e.g. Edx, Blackboard).