Software Engineer Engineering

Mitesh Agrawal

** **** ****** #*, *********, MA-*1602 *********@***.*** +1-774-***-**** www.linkedin.com/in/mitesh-agrawal OBJECTIVE

To secure Robotics Software Engineer position.

EDUCATION

Worcester Polytechnic Institute (WPI), Worcester, MA May 2020 Master of Science in Robotics Engineering. (GPA 3.87/4.0) Shri Ramdeobaba College of Engineering and Management (RCOEM), Nagpur, India May 2016 Bachelor of Engineering in Mechanical Engineering with Distinction (CGPA 7.53/10) Relevant Coursework: Robot Control, Deep learning for advanced robot perception, Motion Planning, Advanced Robot Navigation, Robot Dynamics, Foundation of Robotics (WPI), Optimization problems and algorithms (Udemy), Practical Reinforcement Learning*(Coursera). (*indicates current coursework) SKILLS

Programming Languages: C++, Python, C, Java, SQL

Robotics and Design Software: Tensorflow, Keras, Pytorch, ROS, Gazebo, MATLAB/Simulink, LabView, Git, Creo pro E. PROFESSIONAL EXPERIENCE

Graduate Tutor, Dept. of Electrical and Computer Engineering, WPI, Worcester, MA Mar 2020 – Present

• Tutor for Introduction to Control Systems graduate level course in ECE dept. Graduate Research Assistant, Dept. of Computer Science, WPI, Worcester, MA Jan 2020 – Present

• Using neural networks to detect intoxication in human voice

• Crafting deep learning architectures (LSTMs, RNNs, CNNs) as well as transfer learning from cutting edge audio architectures R&D Automotive Intern, Vehicle Robotics & Optimal Control, Hitachi Automotive Systems Americas, Inc., MI May 2019 – Dec 2019

• Synthesized algorithms for motion planning, maneuver planning and velocity profile estimation on hybrid vehicle

• Developed algorithms for path prediction of environment vehicles

• Employed various ML and Deep learning algorithms, including MDP, Multi-model encoder decoder network and Bayesian optimization using Pytorch and publishing paper on the same at SAE WCX 2020.

• Supported CAN bus, sensor data collection, sensor fusion and HD mapping APIs using C++ and ROS Graduate Student Researcher, Dept. of Robotics Engineering, WPI, Worcester, MA Dec 2018 – May 2019

• Incorporated learning and prediction model of dynamic environment to MPC control at CIRL Lab Application Development Analyst, Accenture Solutions Pvt. Ltd., Bangalore, India Aug 2016 – July 2018

• Implemented automation of regular activities through Blue Prism, robotic process automation software

• Development of various projects in demand and supply planning of client in America region in SAP APO

• Designed a monitoring program with SAP ABAP to reduce human error risk in monitoring daily job schedule Project Intern, Hi Tech Resistors Pvt. Ltd., Nagpur, India July 2015 – May 2016

• Conceptualized and drafted designs for coil winding machine for special purpose resistors

• Led the development of PLC programming using ladder logic and installed the machine in the company Summer Research Intern, RGSTC- TIFAC research internship scheme, Gov. of India, Nagpur May 2015 – July 2015

• Conducted various primary and secondary researches for calculating force-interference graph for rotor- shaft assembly on induction motors and derived an equation to accurately calculate the press fit force

• Ideated and created algorithm and electronic circuit for automated press fit machine

• Published paper on “Algorithm in Automated Press Fit for Rotor-Shaft Assembly of an Induction Motor” in IJIRSET, Vol. 5, Issue 11, ISSN:2319-8753, November 2016

ACADEMIC PROJECTS

Obstacle avoidance pipeline for dynamic environment, CIRL Lab, WPI

• Developing prediction model for dynamic obstacle path using Bayesian change point detection and gaussian process

• Designed motion planning algorithm using stochastic stream functions (adaptation from fluid dynamics) to avoid subjects

• Incorporating scenario-based optimization for stochastic MPC to drive vehicle Developing motion planning for platoon of autonomous vehicles using Deep Reinforcement Learning, WPI

• Creating simulation model for platooning of connected vehicles using UnityML

• Designing and implementing Deep Q learning models for safe platooning of vehicles Implemented motion planning using Deep Reinforcement Learning for autonomous vehicles, WPI

• Developed a concatenated CNN and LSTM model based on sensor and image inputs

• Implemented Deep Q Network (DQN) as well as double dueling DQN to generate actions for safe driving Implementation of MPC on r1/10th car, CIRL Lab, WPI

• Formulated of kinematic and dynamic model of car and dynamically feasible trajectories between given point

• Implemented nominal MPC on car to track trajectory using ROS Frontier algorithm-based navigation for autonomous 3D map generation of indoor environments, WPI

• Generation of 3D map in simulation using RTAB Map and Octomap for Turtlebot Model in Gazebo

• Achieved 2D occupancy grid mapping from point cloud and developed Frontier based algorithm for autonomous exploration in an unknown environment using ROS and Python Trajectory estimation of ball in flight using Deep Learning, WPI

• Employed LSTM to determine the trajectory of ball in flight monitored using VICON state estimation software Human-robot handover motion planning, CIBR Lab, WPI

• Conducted motion study on human-human handover, to establish actions and state variables that affect handover

• Developed MDP model for action sequence and reward matrix for motion planning of handover scenarios by Baxter Robot Hybrid of AGV and ATV, RCOEM

• Conceptualized and developed amalgamation of AGV (anywhere guided vehicle) and ATV (all-terrain vehicle)

• Published a technical paper on the same in IJIRSET, Vol. 5, Issue 12, ISSN: 2319–8753, December 2016

• Won 1st prize in Robotics research project competition

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