Perception Software Engineer @ Zoox
San Francisco Bay Area
Zoox
Software Engineer
Foster City, CA
IBM
CVD Process Engineering Intern
May 2014 to August 2014
Essex Junction, VT
Intel Corporation
Computer Vision Software Developer
June 2017 to October 2018
Phoenix, AZ
Systems & Technology Research
Video & Image Understanding Intern
June 2015 to August 2015
Woburn, MA
Rensselaer Polytechnic Institute
Computer Vision Research Assistant
January 2014 to May 2014
Troy, NY
Stanford University
Master of Science (M.S.), Electrical Engineering, GPA: 3.97
2015 to 2017
Rensselaer Polytechnic Institute
Bachelor of Science (B.S.), Electrical Engineering, GPA: 3.93
2011 to 2015
University of Leeds
Study Abroad Program
2013 to 2013
What company does Robert Mahieu work for?
Robert Mahieu works for Zoox
What is Robert Mahieu's role at Zoox?
Robert Mahieu is Software Engineer
What industry does Robert Mahieu work in?
Robert Mahieu works in the Automotive industry.
Who are Robert Mahieu's colleagues?
Robert Mahieu's colleagues are Daniel Holmlund, Yi-Hsiang Wang, Dan Stein, Sandeep Narayana, Harshitha Gunalan, Saniya Shah, KristĂłf Tahy, Barbara Hochgesang, Anish Kumar, and Mark Firstenberg
đź“– Summary
Software Engineer @ Zoox Lidar / Perception Team Foster City, CACVD Process Engineering Intern @ IBM Ran experiments to optimize the time and material usage of different processes in the chemical vapor deposition (CVD) operations on silicon wafers. This work additionally contributed to improving the availability of the tools. I also worked with my team to characterize newly installed tools and to establish guidelines for implementing new procedures. From May 2014 to August 2014 (4 months) Essex Junction, VTComputer Vision Software Developer @ Intel Corporation Worked with Intel's Autonomous Driving Group (ADG) to develop algorithms for automated driving policy. Reinforcement learning methods and their application to this problem was our primary focus. We worked on applications for both the behavioral and motion planning stages of the system where the vehicle must decide what local goal is required and then how best to accomplish that directive. This work allowed us to benchmark the performance of state-of-the-art algorithms in order to directly communicate the strengths of Intel hardware to our customers. Also worked on benchmarking and optimization of deep neural networks for object detection and localization for deployment on Intel vision accelerator hardware. Through this work, we also produced and submitted a patent application regarding methods for distributed object detection processing.Additionally played a part in the analysis and optimization of a customer algorithm for occupancy grid mapping based on particle filtering. As a result of the success of our work, I received a division recognition award (DRA) for my contributions.[Experience with TensorFlow, Keras, ROS, Python, C++] From June 2017 to October 2018 (1 year 5 months) Phoenix, AZVideo & Image Understanding Intern @ Systems & Technology Research Developed software for an airborne surveillance tracking system that enabled the detection of areas of shadow and occlusion within 2D imagery. My algorithm utilized LIDAR data (automatically selected from a large set based on the geographical location of the photo) to generate a 3D rendering of the visible scene using C++, OpenGL, and OpenCV, in which we could cast virtual shadows then refer the results back to the original image. This environmental information then represented one part of a larger "context-aware" multi-target tracker system being developed at the company for DoD airborne surveillance applications. From June 2015 to August 2015 (3 months) Woburn, MAComputer Vision Research Assistant @ Rensselaer Polytechnic Institute Worked as an undergraduate research assistant on a research project under the supervision of Dr. Rich Radke. The product was a computer vision system with the ability to track the movement of objects traveling through the field of view of multiple (distorted) camera lenses. Video streams from each camera were processed separately, then accordingly stitched together into a single mosaic video showing the entire scene, onto which bounding boxes were superimposed around subjects of interest. From January 2014 to May 2014 (5 months) Troy, NY
Introversion (I), Sensing (S), Thinking (T), Perceiving (P)
0 year(s), 7 month(s)
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