Scholar

Mahdi Naddaf

Google Scholar ID: CRHOYxoAAAAJ

Ford Research GFL, Palo Alto

Artificial IntelligenceRoboticsMachine LearningDeep Learning

Citations & Impact

All-time

Citations

301

H-index

i10-index

Publications

Co-authors

list available

Contact

Publications

15 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

Published multiple peer-reviewed papers, including:
“Deep Bayesian-Assisted Keypoint Detection for Pose Estimation in Assembly Automation” (Sensors, 2023)
“Real-Time Explainable Multiclass Object Detection for Quality Assessment in 2-Dimensional Radiography Images” (Complexity, 2022)
“Defect detection and classification in welding using deep learning and digital radiography” (Academic Press, 2021)
“An efficient and scalable deep learning approach for road damage detection” (IEEE Big Data 2020)
Co-PI on Stanley Black and Decker funded project on weld defect detection
Recipient of Lamar University CICE grant for road crack detection project
Recipient of Lamar University CAWAQ grant for lionfish remediation aquatic robot project

Research Experience

Research Scientist at EnRisk
Research Scientist at Ford Motor Company, Greenfield Labs, Palo Alto, California, USA
Postdoctoral researcher at Galban Lab, University of Michigan
Led multiple robotics and deep learning projects, including 3D object pose estimation with YuMi cobot, MOCAP system for Crazyflie drone swarms, and deep learning-based aquatic robot for lionfish detection
Developed industrial applications such as deep learning-based weld defect detection and real-time road crack detection and mapping

Co-authors

19 total