Prajval Vaskar

+1-864-***-**** adivpn@r.postjobfree.com linkedin.com/in/prajval-vaskar https://github.com/Praj390

SUMMARY

A Self-motivated, Enthusiastic Graduate student focusing on Autonomous vehicle development with a deep understanding of the perception of the vehicle, deep learning, and robotics seeking an internship position to explore career options in the Autonomous Industry.

EDUCATION

Master of Science, Automotive Engineering August 2021

Clemson University- International Center for Automotive Research

Bachelor of Engineering, Mechanical Engineering May 2018

Sinhgad Academy of Engineering, Pune University

ACADEMIC PROJECTS

Behavior Cloning using Deep Learning on f1tenth platform in simulation environment. Nov - Dec 2020

Developed python implementation of end-to-end learning using NVIDIA’s CNN model and CNN-LSTM model architecture and validated the performance in Gazebo using ROS melodic.

Turtlebot3 Simulation in Gazebo environment (ROS kinetic) Mar - Apr 2020

Created Python implementation of Autonomous navigation of Turtlebot3 with wall following and obstacle avoidance deploying digital PID. Line following with OpenCV and stop sign recognition using darknet YOLO ROS package. Human following utilizing leg detection and digital PID for motion.

RRT-A* vs RRT* In A Static Traffic Environment for Urban Driving Mar - Apr 2020

Built simulation scenario of 8 vehicles in 3 unidirectional lanes in Tinker and Pygame environment. Implementation of RRT-A* and RRT* and its performance comparison in python.

Autonomous Navigation on Road Mar - Apr 2020

Performed Autonomous navigation on an on-track camera video in MATLAB. Accomplished Autonomous lane tracking, simultaneous Road Sign detection, communication and Vehicle control, and HMI determination by applying Camera Calibration, Stanley Controller, UDP communication, and Deep learning.

Developed Semantic Segmentation with FCN-VGG16 architecture on France dataset using TensorFlow. Mar-Apr 2020

Training of FCN-VGG16 architecture using pre-trained weights of VGG16 with training and testing examples of 311 and 56 samples. The training and validation accuracy achieved is 88% and 85.94% respectively.

Adaptive cruise control (ACC) and Autonomous lane-keeping (ALK) implementation Nov - Dec 2019

Implemented ACC and ALK in ARDUINO with model-based approach, Kalman Filtering, and PID controller on an RC vehicle.

PUBLICATIONS

Design and Development of Open Differential for Transmission System of Quad Bike - International Research Journal of Engineering and Technology (IRJET), ISSN: 2395-0056, Vol.5, Issue 12. Dec 2018

Design and Development of Automatic Coil Winding Machine - International Research Journal of Engineering and Technology (IRJET) ISSN: 2395-0056, ISSN: 2395-0056, Vol.5, Issue 6. Jun 2018

Design and Development of Three Link Suspension System for a Quad Bike - International Research Journal of Engineering and Technology (IRJET), ISSN: 2395-0056, Vol.5, Issue 1. Jan 2018

Tripod Steering for Better Maneuverability of Quad-Bike Bike - International Research Journal of Engineering and Technology (IRJET), ISSN: 2395-0056, Vol.4, Issue 12. Dec 2017

WORK EXPERIENCE

Company - Vyankatesh Fabricrafts PVT LTD, Nashik, Maharashtra, India Jun 2018 - Oct 2018

Assistant Design Engineer – Deciding specification of pressure vessel according to ASME and pharmaceutical norms.

Competition - FMAE QBDC and ISNEE QUADTORC, India Jan 2017 - Oct 2018

Design and manufacturing of an ATV. Lead team and constructed steering and suspension, customized wheel assembly.

COURSEWORK

Completed - Autonomy: Science and Systems Perception and Machine Intelligence Motion Planning Autonomous Driving technologies Robotic Mobility and Manipulation Automotive Electronics Integration Automotive Systems: An Integrated Overview Automotive Business Concepts Computer Vision Scaled Autonomous Vehicles Artificial Intelligence Analysis of Tracking System.

CERTIFICATIONS

Completed - The Complete Self-Driving Car Course - Applied Deep Learning ROS for Beginners: Basics, Motion, and OpenCV Visual Perception for Self-Driving Cars.

Currently Pursuing – Deep learning Coursera Specialization State Estimation and Localization for Self-Driving cars Autonomous Cars: Deep Learning and Computer Vision in Python Learn Python Programming Masterclass.

SOFTWARE

MATLAB, GAZEBO, RVIZ, ROS Autowave, CARLA simulator, TensorFlow, PyTorch library, PTC CREO, ANSYS, Lotus Shark, AutoCAD, Siemens NX, Arduino, MS Office.

CODING LANGUAGES

Python (Proficient), ROS (Proficient), C (Intermediate), C++ (Intermediate).

Contact this candidate