Ameya Wagh
Staff Machine Learning Engineer at IEEE Standards Association | IEEE SA
Palo Alto, California, United States
Summary
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Senior🎓
Top SchoolAmeya Wagh is a Staff Machine Learning Engineer in Palo Alto with 11 years of experience building real-time perception systems for autonomous vehicles and robotics. He has driven R&D in occupancy estimation, 3D scene reconstruction, and foundation models at Rivian after developing production-ready, low-latency CV and deep learning pipelines for SAE Level 4 trucks at Torc Robotics. His background blends academic research in computer vision and medical image segmentation with hands-on deployment of sensor auto-calibration, BEV lane detection, and realtime 3D point cloud segmentation. An active contributor to standards (IEEE P1955) and a published researcher, he pairs rigorous experimentation with pragmatic engineering to ship onboard models. Colleagues describe him as a roboticist who moves seamlessly from prototype research to production systems, often uncovering robustness gains through uncommon preprocessing and calibration insights.
11 years of coding experience
5 years of employment as a software developer
Master's degree, Mechatronics, Robotics, and Automation Engineering, Master's degree, Mechatronics, Robotics, and Automation Engineering at Worcester Polytechnic InstituteBachelor’s Degree, Electronics and Telecommunication, Bachelor’s Degree, Electronics and Telecommunication at University of Mumbai
English, Marathi, Hindi
Github Skills (38)
pcl10
atlas10
torcs10
darkflow10
classification9
point-cloud9
ros9
object-detection9
3d8
tensorflow8
inference8
robot-control7
classifier7
llama7
robotics6
Programming languages (9)
Github contributions (5)
AmeyaWagh/traffic_sign_detection
Nov 2017 - Jan 2020
Implementation of darkflow on traffic sign detection and classification
Contributions:30 commits, 3 PRs, 24 pushes in 2 years 1 month
classificationdarkflowyolotraffic-sign-classificationtraffic-sign-detection
AmeyaWagh/3D_object_recognition
Feb 2018 - Sep 2019
recognize and localize an object in 3D Point Cloud scene using VFH - SVMs based method and 3D-CNNs method
Contributions:45 commits, 6 PRs, 48 pushes in 1 year 7 months
3dpoint-cloudpclrospointcloud
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