Experience

Institute for Development and Research in Banking Technology (IDRBT)
• India
• Banking
• 1 - 100 Employee
• Assistant Professor

  • Dec 2019 - Present

Indian Institute of Information Technology Lucknow
• India
• Technology, Information and Internet
• 1 - 100 Employee
• Assistant Professor

  • Jan 2019 - Dec 2019


Indian Institute of Technology, Indore

• India
• Higher Education
• 500 - 600 Employee

• Research Scholar

  • Dec 2015 - Jan 2019

  Area of interest:1. Electronic Design Automation (EDA)2. High Level Synthesis (HLS)3. Hardware Security4. Digital Watermarking and Fingerprint5. Evolutionary Computing (PSO, GA, BFOA)6. CAD-VLSI7. Reusable Intellectual Property Core Protection (IPP)

• Teaching Assistant

  • Jan 2017 - Dec 2018

  CS 206: Logic Design (Spring, 2017), CS 256: Logic Design Lab (Spring, 2017)

• Teaching Assistant

  • Jul 2016 - Dec 2016

  Computer Architecture (Autumn, 2016), Computer Architecture Lab (Autumn, 2016)



Amazon

• Bangladesh
• Advertising Services
• 1 - 100 Employee

• SDET Intern

  • Jun 2015 - Nov 2015

  Worked on building new tools and library to automate the test. Work closely with selenium web driver, appium for automation. Worked on building new tools and library to automate the test. Work closely with selenium web driver, appium for automation.



Institute for Development and Research in Banking Technology

• India
• Banking
• 1 - 100 Employee

• Research Associate (M.Tech Final Year Project)

  • Jun 2014 - May 2015

  The project aims to develop a novel technique to enhance the saliency of an intended object, which is not intrinsically salient, in an already captured image. Therefore, the aim is to compute a new feature value for the intended object by maximizing the feature dissimilarity (which is weighted by positional proximity) with other objects. The project aims to develop a novel technique to enhance the saliency of an intended object, which is not intrinsically salient, in an already captured image. Therefore, the aim is to compute a new feature value for the intended object by maximizing the feature dissimilarity (which is weighted by positional proximity) with other objects.