Dhruv Karnik

Summary

M.S. Mechatronics, Robotics & Automation candidate with experience in EV battery-management validation, CAN/Python test tooling, industrial robotics, and autonomous-vehicle controls. Hands-on with Python, MATLAB/Simulink, PLCs, embedded systems, and robotic integration; current research focuses on MPC-based path tracking, obstacle avoidance, and imminent-collision mitigation.

Education

New York University

M.S. Mechatronics, Robotics & Automation Engineering · May 2027
GPA: 3.5 / 4.0 · Teaching Assistant, Dynamics (Sep 2026 – Dec 2026)

MIT World Peace University

B.Tech. Robotics & Automation · 2025
GPA: 9.04 / 10

Experience

Tata Motors · Battery Management Systems Intern

Jan 2025 – Jul 2025 · Pune

Developed a Python GUI for real-time BMS testing over CAN, supporting live monitoring and EV battery validation. Supported BMS development and validation through system testing, data analysis, debugging, and performance optimization.

Cybernetik Technologies · Robotics Intern

Jul 2024 · Pune

Programmed an ABB industrial robot using Python for palletization and gained hands-on exposure to industrial automation workflows and safety standards.

Innovation Hub, MITWPU · Robotics Research & Development

Oct 2021 – May 2024 · Pune

Designed and developed a river-cleaning robot for floating-waste removal and a mobile mini-gripper robot for obstacle-course navigation and payload handling.

Projects

M.S. Thesis — MPC-Based Autonomous Vehicle Control & Collision Mitigation

Developing an MPC-based controller for path tracking, obstacle avoidance, and imminent-collision mitigation on an Ackermann-steered vehicle. Building simulation and validation workflows in MATLAB/Simulink and MuJoCo while investigating trajectory optimization, physical constraints, and controller computation/reaction-time tradeoffs.

CKF vs. EKF for Nonlinear State Estimation

Implemented Cubature and Extended Kalman Filters in Python for 2D robot localization and coordinated-turn radar tracking; a 75-run radar Monte Carlo study produced 2.19 m average RMSE for CKF versus 3.84 m for EKF.

Collaborative Robot with Physical Teaching

Designed and programmed a collaborative robot capable of learning tasks through physical guidance without manual task coding.

Technical Skills

Programming: Python, Embedded C, MATLAB
Controls & Simulation: MATLAB/Simulink, MPC, Control Systems, MuJoCo, State Estimation
Automotive & Embedded: CAN, Battery Management Systems, Sensors & Actuators, Arduino
Robotics & Automation: ABB (RAPID), KUKA, Yaskawa, Universal Robots, PLC Programming
CAD & Mechanical: Fusion 360, Mechanical Design of Robot Mechanisms

Certifications & Languages

Certifications: NPTEL Automatic Control (IIT Roorkee); Industrial Automation — Siemens (NITTTR Bhopal)
Languages: English, Hindi, Marathi, German