My Cousin is an HR exec and she always complained about poor aptitude along with other lacking traits of potential candidates a few steps further in the interview process.

This lead me to build GenomeHR that scans images (lets say from LinkedIn) and uses GENOME LINK api to get insights (PHENOTYPES) such as

  • Intelligence,
  • Anger,
  • Childhood intelligence,
  • Mathematical ability
  • Openness . .

etc to scout for better candidates.

What it does

AI Module classifies candidates by ethnicity ------> *GENOME LINK uses this to predict the "Smartness" & eligibility of candidates *

How I built it

Uses a Tensorflow image model to predict the persons ethnicity. Uses GENOME LINK api to get traits Python web app to showcase the product.

Challenges I ran into

Training data and training the module was challenging to achieve accuracy

Accomplishments that I'm proud of

The AI / ML model's accuracy

What I learned

Genome api functionalities. How to build image recognition models.

What's next for GenomeHR

  • This can be used as a tool / browser extension that activates when HR personnel are scouting on Linkedin or any other website of similar kind

  • Can be used to train the model specific to organizations.

  • Can be used to identify employees who potentially could be recommended -mathematical programs -reading programs -anger management programs -mental health programs.


Built With

Share this project: