Vijil Chenthamarakshan  Vijil Chenthamarakshan photo         

contact information

IBM AI Research
Thomas J. Watson Research Center, Yorktown Heights, NY USA


Professional Associations

Professional Associations:  ACM  |  IEEE


I am a member of the AI Foundations Lab at IBM T.J. Watson Research Center. My research interests are in the broad areas of Machine Learning and Natural Language Processing.

Over the years, I have worked on many different aspects of Machine Learning including Machine translation, Information Extraction, Transfer Learning, Paraphrase detection, etc and have applied these techniques to solve problems in a wide variety of industries like Finance, Oil and Gas, Insurance and Construction. I have also worked on projects for various government agencies in the areas of National Security and Healthcare. My recent work is focussed on transfer learning scenarios for various NLP tasks where the amount of training data is extremely small.

I have several peer reviewed publications in international journals and conferences, and 13 granted patents. More than 15 patent applicants are also pending with US Patent and Trademark Office. 


Granted Patents

  • US 9727344 Mining Dependencies from Disk Images
  • US 8422786 Analyzing Documents using Stored Templates
  • US 8205153 Information extraction combining spatial and textual layout cues
  • US 8713521 Discovery Analysis and Visualization of Dependencies
  • US 9547860 System for processing feedback entries received from software
  • US 8990128 Graph-based framework for multi-task multi-view learning
  • US 8856050 System and method for domain adaption with partial observation
  • US 7890591 Method for an efficient electronic messaging system

Media Coverage

U-Report saves lives - says Maureen Achia, Child Protection Officer with 'Save the Children-Uganda'

A case study by Center for Public Impact

UNICEF Draws on IBM Analytics to Give a Voice to Youth in Africa

"Big data" heralds a new kind of analyst

How Cognitive Technologies Boosted UNICEF’s Social Networking in Africa

Are Data Miners Ready to Hang Up the Hard Hat and Put on a Lab Coat?

Leveraging data to change cities as we know them - the social impact