Engineer Python

JASH KIRITBHAI PATEL

Dearborn, MI +1-313-***-**** ********@*****.*** LinkedIn Profile Portfolio Website SUMMARY

Penchant for leveraging next generation ADAS & Self Driving Car technologies to drive benefits for society

Proficient in technical documentation & preparation of statistical reports using MS Office

Reinforced my programming skills by completing more than 20 projects using MATLAB, Python & C++ EDUCATION

The University of Michigan-Dearborn GPA: 3.74/4.0

Master of Science in Automotive Systems Engineering Apr 2021 (Expected) Nirma University, Ahmedabad, India First Class with Distinction Bachelor of Technology in Mechanical Engineering Graduated on: May 2019 TECHNICAL SKILLS

Software & language: Python, C/C++, Tableau, Matlab-Simulink, Stateflow, MS Office, ROS-Gazebo, Linux, Git. Autonomous Driving: Perception, Sensor fusion, Localization, Path planning (A*, RRT*), Behavioral planning, SLAM. Control Systems: PID, LQR, MPC, Pure Pursuit Controller, Stanley Controller, PMP, Fuzzy logic control. Machine Learning: CNN, Hyperparameter tuning, Computer Vision, Regression & Classification modelling. Others: Digital Signal Processing, Vehicle dynamics, Agile, Battery modelling, Bayesian filtering, Embedded Systems. EXPERIENCE

University of Michigan – Dearborn Research Assistant Dearborn, MI Sep 2020 - Present

Implementation of signal processing techniques to match two time series data

Solid state on-chip Lidar for autonomous driving: High-efficiency end-fire 3D optical phased array based on multi-layer Si3N4/SiO2

platform

Dorle Controls LLC ADAS- Controls Software Engineer Intern Farmington Hills, MI Aug 2020 - Oct 2020

Localization of Autonomous Vehicle using Sensor Fusion & Nonlinear Filtering o Synthesized artificial driving environment for feature testing o Enhanced the reliability of data coming from IMU & GPS using sensor fusion algorithms o Estimated the location of ego vehicle within 10 cm of error using EKF & Particle Filter algorithm

Modelling & Simulation of Behavioral Planner for Robust Autonomous Highway Driving o Orchestrated the selection of highway maneuvers using Prediction & Cost function-based algorithm o Concatenated & clustered RADAR data using sensor fusion techniques o Innovated high level task of decision making using Finite State Machines

Development & Execution of Testing Scenarios for ADAS L-2 Features (AEB, FCW, ACC, LKA) o A Truck steers into the same lane as the Ego Vehicle o Ego Vehicle comes across the intersection where other cars are passing by o Left lane change with no vehicle coming beside for 4 sec Tata Motors Limited Project Engineer Intern Ahmedabad, India Jan 2019 - May 2019

Optimized PVC & sealant application process employing VA-VE (Value Analysis-Value Engineering) techniques resulted into annual savings of $85,000 & $53,000 respectively Ford Motor Company Project Engineer Intern Ahmedabad, India June 2018 - July 2018

Streamlined manpower by conducting work study analysis to increase average utilization of each worker from 65.2% to 81.5% without affecting production volume ACADEMIC PROJECTS

Home Service Robot to pick up and deliver objects (C++, ROS, Gazebo) Mar 2021

Implemented Adaptive Monte Carlo Localization algorithm to localize the robot in simulation environment

Boosted the localization efficiency by tuning process parameters

Implemented GraphSLAM algorithm with RTAB map for 2D & 3D mapping of environment

Incorporated Dijkstra’s algorithm for trajectory planning and navigate to goal Lidar & Radar Sensor Fusion using Unscented Kalman Filter (C++) Feb 2021

Detected the nonlinear motion of traffic vehicles around ego vehicles on 3-lane highway road within accuracy of less than 30 cm using UKF & CTRV (Constant Turning Rate & Velocity) motion model Development of Collision Detection System (C++) Jan 2021

Clustered LiDAR point clouds within bounding boxes generated using YOLO object detection on camera images

Estimated TTC (Time to Collision) of 3D objects based on Lidar & Camera measurements Object detection using Lidar sensor data (C++) Jan 2021

Segmented raw real LiDAR point cloud data using 3D RANSAC algorithm

Performed efficient nearest neighbor search using Euclidean clustering along with KD-Tree Target generation and detection using Radar (MATLAB) Jan 2021

Configured FMCW waveform based on sensor’s requirements

Ascertained target position & velocity using Range & Doppler FFT (Fast Fourier Transform)

Mitigated the noise & clutter using CA-CFAR (Cell Averaging – Constant False Alarm Rate) method Robust Lane Keep Assist System using digital PID Controller (MATLAB) Oct 2020

Implemented 5 DOF lateral vehicle dynamics model & tuned PID controller to control steering angle

Evaluated the performance of the controller by generating oval track using driving scenario designer Localization & path planning of autonomous robot (Python) Sep 2020

Incorporated particle filter algorithm to localize robot in 2D environment

Implemented BFS, DFS, Dijkstra & A* algorithms to find optimal path between any two points in map Modelling & Simulation of Adaptive Cruise Control System (MATLAB) Aug 2020

Integrated longitudinal vehicle dynamics model to ascertain vehicle speed from throttle/brake command

Designed Control system that modulate the vehicle speed to maintain safe distance from lead vehicle

Developed driver warning system to alert the driver to take control of vehicle in emergency situations Modelling, Simulation & Control of 5 DOF & 7 DOF vehicle model (MATLAB) May 2020

Modelled & assessed both models in straight line & steering maneuver in constant speed & acceleration conditions

Synthesized PID controller to attain neutral steer for active front steering system Cruise Control of Tesla Model S P85 using PID Controller (MATLAB) May 2020

Implemented engineering model of DC motor & vehicle dynamics

PID controller was evaluated & tuned to control speed of vehicle Model Predictive Control (MPC) in Self-driving Car (Python) Apr 2020

Built MPC to follow speed limits on highway, for parking control & obstacle avoidance using python Control System Design of Bicycle Model of Vehicle for Steering System (MATLAB) Apr 2020

Designed PID Controller using Ziegler Nichols rules & tuned it using Root Locus Method Object positioning using Sensor fusion & Nonlinear Filtering (MATLAB) Apr 2020

Implemented nonlinear coordinated turn motion model & dual bearing measurement/sensor model

Estimated position of object using EKF, UKF, CKF & Particle Filter Simulation of Fully Functional Self- Driving Car using Computer Vision & CNN (Python) Mar 2020

Trained CNN (Convolution Neural Networks) by driving a car through simulator manually on training track

Evaluated performance of CNN model by driving a car on completely different track

Enhanced accuracy of model by image augmentation & hyperparameter tuning Lane lines Detection using computer vision (Python) Mar 2020

Converted RGB image into Grayscale image to reduce computation time

Mitigated image noise using Gaussian filter & detected straight lines using Hough transform Classification of Road Symbols using CNN (Python) Mar 2020

Trained LeNet CNN model to classify between 43 different traffic signs

Enhanced accuracy of model by hyperparameter tuning Self-driving vehicle control (Python) Dec 2019

Synthesized a controller for Carla simulator with Python to control vehicle to follow preselected racetrack

Established longitudinal & lateral controller using PID controller & Pure Pursuit Controller (PPC) Modeling, simulation & control of Drone (MATLAB) Oct 2019

Implemented mathematical model of rotational dynamics, linear dynamics, DC motors & propellers

Tested & tuned PID controller to control pitch, roll & yaw of drone Development of ABS using PID & Non-Linear Tracking Controller (MATLAB) May 2019

Engineered & incorporated mathematical model of vehicle dynamics, tire model using Pacejka magic formula & hydraulic non-linear tracking control system for Anti-lock Braking System (ABS)

Attained significant reduction in braking distance as compared to average braking distance of vehicles Autonomous Car Model (Python) Dec 2017

Created Working model of car that apply brakes & stop motion in occurrence of any kind of obstacle

Arduino board was used to control motion of vehicle CERTIFICATIONS [Click here to see full list of Certifications] Sensor Fusion & Nonlinear Filtering Applied deep learning in self driving car Python 3 Programming Specialization Machine Learning & Deep Learning by IBM Introduction to Probability by Harvard University Intro to Artificial Intelligence Sensor Fusion Engineer Nanodegree Robotics Software Engineer Nanodegree Reinforcement Learning

Contact this candidate