CHASE T GURCAN

631-***-**** admxo3@r.postjobfree.com

www.linkedin.com/in/Chase-Gurcan www.github.com/ChaseGurcan www.youtube.com/ChaseGurcan EDUCATION

Master of Science: Automotive Engineering, 05/2021 Clemson University - Greenville, South Carolina

• Dual specialization autonomy and vehicle manufacture engineering

• 3.85/4.0 GPA

• Elected member of the Student Ambassador's board

• Lean Six Sigma Green Belt Quality Certified, Clemson University certified in Automotive Quality Bachelors: Applied Mathematics and Engineering Sciences, 05/2019 Assumption College - Worcester, MA

• Brother Gerard Brassard Scholarship Recipient, Brother D'Alzon Scholarship Recipient (Highest scholarship)

• 4 Year scholarship student athlete on Men’s varsity soccer

• Dean's List Honoree Fall 2016, Fall 2018, Fall 2019 SKILLS

• Machine Perception/Intelligence

• MATLAB

• Python

• Machine Learning/ Deep Learning

• Motion Planning Algorithms

• Systems engineering

• Linux experience

• CAD: Solidworks, Catia, Siemens NX

• ISO, Quality

• Lean Manufacturing

WORK HISTORY

Manufacturing Engineering intern at Rivian Automotive, 01/2021 to 05/2021 (Current)

• Develop and adjust computer vision algorithms to decrease time for camera calibration by 36%

• Develop and perform vehicle end of line testing on camera system calibrations and vehicle dynamics tuning.

• Address and maintain EBOM, MBOM, and Catia files such that vehicles are ready for SOP by June 2021

• CAD modeling in Solidworks and Catia V6 for proprietary camera system holders

• Development of Ishikawa diagrams, PFMEA, Gauge R&R and ANOVA for vehicle centering system Deep Learning Graduate Research Intern, 06/2020 to 09/2020 Brookhaven National Laboratory, Dept. of Energy – Brookhaven, NY(Remote)

• Application of Deep Learning algorithms for object detection and tracking of nuclear materials to supplement the need for human surveillance during transportation.

• Developed and trained a custom dataset with 3 classes of nuclear waste material and applied it to YOLO v3 algorithm to reach an accuracy of 86% in a linux environment. Graduate Research Assistant, 09/2019 to 12/2019

Clemson University ICAR – Greenville, SC

• Research for Dr. Laine Mears (BMW Endowed Chair in Automotive Manufacturing) in partnership with Honda Motor Company on friction element welding(FEW) study.

• Conducted and analyzed the finite element analysis of martensitic steel grain structure formed during and after the friction element welding process obtaining images of 20 micrometers scale.

• Results concluded that the friction element welding process is capable of welding dissimilar metals such as steel to aluminum, however the process needs more fine tuning to pass ISO standards Manufacturing Plant Layout Design

PROJECTS

• Using Siemens Tecnomatix to design and optimize production of a synthetic manufacturing company

• Achieved reduction in TAKT time by 23% and mitigated unnecessary job elements using Lean Six Sigma approaches.

• Allocate and eliminate bottle necks in the line and promote 5s standards to increase production Arduino Autonomous Robot:(Video on youtube)

• Using Siemens NX, designed and printed a 3D body for the car that would support and hold a multitude of ultrasonic sensors, Arduino IDE and breadboard, while reducing overall sprung mass by 30%.

• Using C++, developed modern active autonomous safety feature algorithms such as Lane Keep Assist and Adaptive Cruise Control that operated with an accuracy of .01 meters

• Correctly implemented signal processing such as Kalman FIltering to remove ~99% of Gaussian noise and other unwanted noise

• Developed a pulse width modulator to control the servo motor output and create a threshold such that the motor output would not be greater than 40%.

Autonomous Lane Keeping featuring Steering Control/ Road Sign Detection:

• Using MatLab, uploaded a video of a vehicle driving between two lane lines and programmed the vehicle to calculate and maintain the middle of the two lanes at all times. (video used during Corona quarantine to supplement hands on experience)

• Extensive image processing such as applying a regional mask to eliminate unwanted figures, downsampling and applying a gaussian filter to speed up calculation time and eliminate unwanted noise, converting to grayscale then black and white to apply a Canny filter for edge detection.

• Implement YOLO v3 for real time object detection of stop signs and school zone signs, including calibration of positive and negative images in MatLab and training of object detector.

• Implemented a Stanley Controller by calculating the alpha steering angle for each frame of the video to accurately steer the vehicle around bends and turns. TurtleBot 3 Burger:

• Operating in Linux, developed LiDAR Python algorithms to correctly allow the robot to perform simultaneous localization and mapping with no collisions even when placed in an unknown environment.

• Implemented PID controllers to allow the robot to maneuver smoothly with no sharp turns or staggering velocity.

• Documented and analyzed all 3D simulations using Gazebo and Rviz to share and collaborate with my peers.

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