Divyansh Jha

Divyansh Jha has work experience in various roles and companies. Divyansh started working as a Web Developer at Timebazaar in November 2016, where they implemented Bootstrap, JavaScript, and data rendering. In 2017, they interned as a Machine Learning Intern at TWF Flours, developing backend systems for data collection and an intelligent CRM system.

In 2018, Divyansh joined Esri as a Machine Learning Intern, where they worked on various projects, including being a core developer of the learn module of the ArcGIS Python API for ArcGIS Enterprise. Divyansh added support for Deep Learning models and an End to End framework for data exporting to deployment. Divyansh later became a Data Scientist II at Esri, responsible for developing the learn module.

In 2020, they were a Visiting Research Intern at KAUST, where they worked on understanding the correlation between generated art and real art with Wölfflin principles and emotions, as well as organizing a hackathon. In 2021, they worked as a Visiting Research Intern at The University of Texas at Austin, focusing on integrating the iGibson renderer to Robosuite for robot learning.

Divyansh'smost recent position is as a Machine Learning Engineer at Woven by Toyota, starting in December 2021.

Divyansh Jha completed their Bachelor of Technology (B.Tech.) degree from Maharaja Agrasen Institute Of Technology, Delhi, from 2015 to 2019. During this time, they did not specialize in any particular field of study.

In 2017, Divyansh Jha pursued a fast.ai International fellowship in Deep Learning from the University of San Francisco, where they studied deep learning techniques.

Prior to their university education, Divyansh Jha completed their high school education at AVB public school from 2008 to 2015, following the CBSE course.

Divyansh Jha also obtained several certifications, including "Entrepreneurship 1: Developing the Opportunity" from Coursera in January 2022. Additionally, they obtained various certifications related to machine learning, algorithms, neural networks, and databases from Coursera between 2016 and 2017.