Srihari Humbarwadi
Lead Engineer, Senior at Qualcomm
Bengaluru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolSrihari Humbarwadi is a Lead Deep Learning Engineer with 9 years of experience building and optimizing low-level perception models for autonomous driving, currently pushing the accuracy-latency-power frontier on Snapdragon Ride AI at Qualcomm. He combines strong research instincts from roles at Bosch and Google Summer of Code with production-facing engineering at Intel and Playment, delivering efficient panoptic and video analytics models for edge deployment. Skilled in model optimization across accuracy, latency, and power, he also brings practical data-science roots from earlier applied computer vision and multi-modal projects. An active contributor to TensorFlow’s model ecosystem (notably Panoptic DeepLab work), Srihari blends research-grade techniques with hands-on microservice and edge deployment experience.
9 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Data Science, Distinction, Master of Science - MS, Data Science, Distinction at The University of EdinburghBachelor of Engineering, Computer Science, First Class with Distinction, Bachelor of Engineering, Computer Science, First Class with Distinction at Gogte Institute of Technology
Stackoverflow
2,572reputation
235kreached
63answers
3questions
tensorflow
top-5%
machine-learning
top-5%
keras
top-5%
deep-learning
top-5%
python
top-5%
Github Skills (12)
computer-vision10
tensorflow10
python9
machine-learning9
deep-learning9
keras9
neural-network6
gradient-descent6
transfer-learning6
image-segmentation6
generator6
predict6
Programming languages (9)
Github contributions (5)
tensorflow/models
Jul 2020 - May 2022
Models and examples built with TensorFlow
Role in this project:
ML Engineer
ML EngineerContributions:7 reviews, 181 commits, 23 PRs in 1 year 9 months
Contributions summary:Srihari primarily contributed to the development and enhancement of a machine learning model, specifically within the context of TensorFlow. Their commits focused on fixing typos and improving the clarity of documentation within the code. The commits included refactoring parts of the codebase and implementing new functionalities related to the Panoptic Deeplab architecture, including the addition of a post-processing layer.
deep-learningtensorflow
srihari-humbarwadi/cityscapes-segmentation-with-Unet
Oct 2018 - Jun 2019
Contributions:14 commits, 10 pushes, 1 branch in 8 months
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