Dushyanta is an Applied Scientist at Amazon. Prior to this, he was a Master’s student in the Computer Science Department at The Ohio State University where he was working under the supervision of Prof. Huan Sun on Weakly Supervised methods for Neural Relation Extraction. In Summer 2017, he worked as an SDE intern at the AWS Deep Learning group in Seattle on prototyping the custom classification tool that was released as part of the AWS Comprehend suite. Prior to joining OSU he was a Research Assistant at the Ubiquitous Knowledge Processing Lab under the supervision of Prof Dr. Iryna Gurevych.
Dushyanta’s Resume
MS in Computer Science, 2018
The Ohio State University
B.Tech in Information Technology, 2014
National Institute of Technology, Kurukshetra
(January, 2018) I ranked 8th out of 20 teams on Semeval,2018 subtask for Relation Classification on Noisy Scientific Data
(December, 2018) Our tutorial on A Convolutional Encoder Model for Neural Machine Translation was accepted at the NIPS workshop on Learn How to code a paper with state of the art frameworks
(November, 2018) My system ranked in Top - 5 submissions for Spanish and French Task in IJCNLP 2017 Shared Task on Multilingual Customer Feedback Analysis
Research Assistant, The Ohio State University
Currently working under the supervision of Prof. Huan Sun on developing techniques for effectively utilizing clean and noisy data in natural language processing.
Software Engineering Intern, AWS Deep Learning
As part of the team that built Amazon Comprehend I worked on the following tasks for deployment of an NLP service (currently not part of the Comprehend suite) on AWS Infrastructure:
Research Assistant, Ubiquitous Knowledge Processing Lab, TU Darmstadt
Research Associate, Precog Research Group, IIIT Delhi, India
Software Engineer, Search Team, Infoedge India
Software Engineering Intern, Samsung Research India
Freelance Software Engineer, FunnelMailApp
Training a smaller neural model using soft targets obtained from a larger model
Extract events in News articles and their participants using a conditional random field classifier and extensive feature engineering
Detecting the stance of the body of an article with respect to its title. Our team (OSUfnc) ranked 7th of the 50 teams that participated