Utkarsh Anand Saxena

Utkarsh Anand Saxena, PhD has a diverse work experience spanning several industries and roles. In 2010, they started as a Summer Intern at ROBOSAPIENS TECHNOLOGIES Pvt. Ltd., where they learned the basics of embedded systems and built simple robots. Utkarsh Anand then worked as a Regional Coordinator at Cyborg Creation Limited, teaching implementation of basic robots and supporting promotional activities. In 2011, Utkarsh served as a Summer Intern at Bharat Electronics Limited, where they gained experience with production and fabrication technologies for radar systems.

In 2012, they worked as a Paid Intern at Propene Products Ltd., where they gained practical experience in a professional setting. From 2013 to 2019, Utkarsh worked at The University of Auckland, first as a Graduate Teaching Assistant, where they taught programming and mathematical modeling courses, and later as a Doctoral Research Scholar, where they conducted research on brain pressure dynamics and its relationship with blood pressure.

In 2014, Utkarsh worked as a Regional Coordinator for the IIT Delhi Robotryst Outreach Program at EISystems, where they taught implementation of basic robots and supported promotional activities. Utkarsh Anand then joined Soul Machines in 2019 as an R&D Software Engineer, eventually being promoted to Senior R&D Software Engineer / Manager. During their time at Soul Machines, they were involved in AI research and development.

Currently, Utkarsh is a Tech Lead / Manager at Fuel50, where they specialize in AI and Skills development.

Utkarsh Anand Saxena, PhD, obtained their Masters degree from the Department of Electrical and Computer Engineering at the University of Auckland in 2014. Their field of study during this period was Electronics and Communications Engineering with a focus on Advance Radio and Control Systems. Subsequently, from 2014 to 2017, Utkarsh pursued their Doctor of Philosophy degree at the Auckland Bioengineering Institute, also at the University of Auckland. During this time, their research focused on Signal processing & System identification, Data Analysis, Applied Mathematics & Stats, and Physiology.