Sankalp Godghate

Full Stack Developer at Qbit (formerly Quifers)
  • Claim this Profile
Contact Information
Location
Nagpur, Maharashtra, India, IN

Topline Score

Bio

Generated by
Topline AI

0

/5.0
/ Based on 0 ratings
  • (0)
  • (0)
  • (0)
  • (0)
  • (0)

Filter reviews by:

No reviews to display There are currently no reviews available.

0

/5.0
/ Based on 0 ratings
  • (0)
  • (0)
  • (0)
  • (0)
  • (0)

Filter reviews by:

No reviews to display There are currently no reviews available.
You need to have a working account to view this content. Click here to join now

Experience

    • Full Stack Developer
      • Oct 2022 - Present
    • United States
    • Software Development
    • 500 - 600 Employee
    • Software Development Engineer - 1
      • Jul 2021 - Oct 2022
    • India
    • Research Services
    • 1 - 100 Employee
    • Additional Secretary
      • Mar 2018 - May 2021

      1. ARIES is a Technical Group under Student Technical Council IIT Roorkee whose focus is on promoting Electronics and AI knowledge among the institute by offering various projects and conducting open Lectures/Workshops. 1. ARIES is a Technical Group under Student Technical Council IIT Roorkee whose focus is on promoting Electronics and AI knowledge among the institute by offering various projects and conducting open Lectures/Workshops.

    • United States
    • Software Development
    • 1 - 100 Employee
    • Machine Learning Engineer
      • Jun 2020 - Aug 2020

      1.Worked on developing computer vision models for detecting closed eyes and open eyes in wedding photographs and albums. 2.Used Image aesthetic models to qualitatively grade the best images in a group of duplicate images. 3.Implemented Neural Image Assessment (NIMA) for the quantification of image quality and aesthetic components of the given set of images. 4.Worked on differentiating candid photos and blur (Out of focus) photos using computer vision models. 1.Worked on developing computer vision models for detecting closed eyes and open eyes in wedding photographs and albums. 2.Used Image aesthetic models to qualitatively grade the best images in a group of duplicate images. 3.Implemented Neural Image Assessment (NIMA) for the quantification of image quality and aesthetic components of the given set of images. 4.Worked on differentiating candid photos and blur (Out of focus) photos using computer vision models.

Education

  • Indian Institute of Technology, Roorkee
    Bachelor's degree

Community

You need to have a working account to view this content. Click here to join now