IASF – Hackathon

IASF – Hackathon

IASF collaborated with Odisha.ml (an organization promoting Machine Learning) and OSA (Odisha Society of Americas) in organizing a Hackathon in June 2022 at the annual convention in Sacramento. The goal was to promote students in grade 8 through 12 from the Odia community across the world to participate and demonstrate their understanding and entrepreneurial talent.

There were 4 broad categories:

  1. Agriculture and Climate Change
  2. Sanitation and Public Health
  3. Education
  4. Bringing the Odia community together

A total of 20 teams registered for the hackathon of which 4 were from Odisha. The hackathon was done remotely over a period of 4 weeks by the students at home. Students provided a 5 minutes video along with other code or presentation for the evaluation.

Category: Agriculture and Climate change

1st prize: Pixelators ($200)

Rishabh Sahoo

Lynbrook High School – 9th grade

Project: Crop recommendation and price prediction using Machine Learning Models

Aadarsh Jena from Jay M Robinson Middle School – 8th gradeProject: Generating clean energy from things we do daily  2nd prize: The Giants ($100)Nisheet Panda & Smaran MishraMission San Jose High School – 11th grade)Project: Predicting crop yield rate in Odisha using Deep learning

Category: Sanitation and Public health1st prize: Mind Mapper ($200)Sharbani Patnaik (Saint Francis, Mountain View – 10th grade)Elena Patro (Cal High, San Ramon – 10th grade)Fiona Sahoo (Dougherty Valley High, San Ramon – 9th grade)Project: The project is to design a medical alert system for dementia patients.

2nd prize: Hospitality ONLINE ($100)Arihant Swain (Peak Charter School – 10th grade)Project: HospitalityONLINE is a project to create a program that allows doctors to interact withpatients through online meetings, forums, and more.   Category: Odia Community Together1st prize: Saha Katha ($200)Nirvika ChoudhuryBasis Independent Silicon Valley – 8th gradeProject: Translating English to English in Odia language using a deep learning natural languageprocessing model.