Nov 2019 – May 2021 · 1 yr 6 mos

Jul 2019 – Oct 2019 · 3 mos

Jul 2018 – Jun 2019 · 11 mos

Jan 2017 – Jun 2018 · 1 yr 5 mos

Jul 2016 – Dec 2016 · 5 mos

Mar 2015 – Jun 2016 · 1 yr 3 mos

• Created a platform for Declarative Config based extraction of E-commerce verticals. Keys characteristics of the system
• 1) Easy to create Config for doing shallow or deep extraction.
• 2) Should support historical extraction i.e. System should able to extract information given the historical webpages.
• 3) Ease of debuggability in case of in-correct/in-complete data is getting extracted
• Automated Layout Element Detection from E-commerce Pages
• 1) For doing deep extraction1, identification of Layout element was automated. This helped us in automatically identifying such element, and benefited us in multiple scenarios mentioned below. These findings also got published in NIPS 2015 workshop.
• Less manual effort for robot developer
• Generating report for new types of Layouts
• While implementing this, multiple technology are used from Selenium, Python, Classification algorithms

Sep 2013 – Feb 2015 · 1 yr 5 mos · New Delhi Area, India

Jun 2011 – Aug 2013 · 2 yrs 2 mos

• Information Retrieval
• Scalable Crawling System

May 2010 – Jul 2010 · 2 mos · Hyderabad Area, India

• Machine Learning Algorithms on Cloud:- We implemented various Machine Learning algorithms using Divide and Conquer Approach in a distributed environment using Hadoop. Basic concept was to divide the data into multiple chunks of smaller size, do learning on each of them and combine it using different methods such as majority.