Nishit Mistry

Nishit Mistry has worked in various roles in the tech industry. In 2023, they were a Data Scientist at SimpTek. In 2022, they were a Teaching Assistant at Dalhousie University. In 2019, they were a Data Scientist at Bombay Leprosy Project - India, where they executed Deep Learning Models for the identification of leprosy using TensorFlow and led a team of 6 people. Nishit also worked as a Data Scientist at Shah And Anchor Kutchhi Engineering College, where they developed Machine Learning models to predict whether a student requires any help. In 2018, they were a Research And Development Engineer at Eduprime Technologies Pvt. Ltd., where they worked on multiple sensors and hardware devices using Arduino Uno-based Uniko Ekam micro-controller board with Arduino (C++) as the programming language.

Nishit Mistry's education history includes completing a Secondary Education from Dr. Sarvepalli Radhakrishnan International School, Malad West from 2006 to 2015. Nishit then attended Mithibai College of Arts Chauhan Institute of Science and A.J. College of Commerce and Economics and obtained a SYJC in Computer Science from 2015 to 2017. After that, they attended Shah And Anchor Kutchhi Engineering College and obtained a Bachelor of Engineering - BE in Information Technology from 2017 to 2021. Nishit is currently pursuing a Master's degree in Applied Computer Science at Dalhousie University, which they started in 2022. Additionally, Nishit has obtained certifications in Python (Basic) from HackerRank in August 2022, the Consulate General of India Toronto Quiz from the Consulate General of India in January 2022, Complete Python Developer in 2021: Zero to Mastery from Udemy in April 2021, AI For Everyone from Coursera in November 2020, Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning from Coursera in October 2020, Natural Language Processing in TensorFlow from Coursera in October 2020, The Complete Web Developer in 2020: Zero to Mastery from Udemy in July 2020, Introduction to Deep Learning (with Honors) from Coursera in May 2020, and Introduction to Machine Learning from NPTEL in September 2019.