Ujjwal Saxena
Evaluator And Automation Development Manager - Automotive
Pune, Maharashtra, India
Summary
👤
Senior🎓
Top SchoolUjjwal Saxena is an automotive software leader with eight years of experience building and scaling perception validation and automation for autonomous driving at NVIDIA and Infosys. He currently manages Analyzer development and Drivesim test creation for AV integration verification, focusing on functional evaluators, KPI calculation, and geo-specific DNN validation across regional products. His background blends hands-on image processing and deep learning model development with process optimization, crowdsourced simulation testing, and rapid automation bring-ups. Known for closing gaps between requirements and implementation, he reduces turnaround time while stabilizing complex digital test suites. Pune-based and technically versatile, he pairs an engineering degree and a Udacity Self-Driving Car Nanodegree with a track record of shipping practical, auditable AV validation solutions.
8 years of coding experience
9 years of employment as a software developer
Bachelor of Engineering (B.E.), Electrical, Electronics and Communications Engineering, 9.36 CGPA, Bachelor of Engineering (B.E.), Electrical, Electronics and Communications Engineering, 9.36 CGPA at ITM UNIVERSITY, GWALIORHigher secondary, Science, 90.28%, Higher secondary, Science, 90.28% at Christ church collegeself driving car nanodegree, autonomous vehicles, self driving car nanodegree, autonomous vehicles at UdacitySenior secondry, PCM with computers, 83.16%, Senior secondry, PCM with computers, 83.16% at Lamartiniere college, Lucknow
English, Spanish, Hindi
Github Skills (14)
computer-vision10
scenarios10
pose10
python9
machine-learning9
autonomous-vehicles9
pytorch9
deep-learning8
sentiment-analysis1
sentiment1
nlp1
tensorflow1
self-driving-car1
natural-language-processing1
Programming languages (4)
Github contributions (5)
UjjwalSaxena/Automold--Road-Augmentation-Library
Apr 2018 - Feb 2022
This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.
Contributions:37 commits, 3 PRs, 29 pushes in 3 years 11 months
pythontrainingscenariosconditionsautonomous
UjjwalSaxena/CarND-Advanced-Lane-Lines-Detection-T1P4
Mar 2018 - Jul 2018
Contributions:48 commits, 40 pushes, 1 branch in 4 months
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