Mihir Kulkarni Email & Phone Number

Oklahoma City, Oklahoma, United States

At Drōv, I lead advancements in automotive engineering, specializing in functional testing & Bluetooth Low Energy integration to ensure the reliable performance of advanced systems like Camera ECU and Tire Pressure Monitoring System. By integrating IoT principles in automotive engineering, I developed robust testing protocols & automation scripts, significantly enhancing product efficiency and reliability.Key Contributions:1) Automated BLE Quality Control for TPMS Sensors: Developed a custom C script on a Raspberry Pi using BlueZ software, replacing a unstable mobile app and achieving an 88% reduction in quality control time, from 8 min to 1 min per sensor. Leveraging IoT, this solution automated scanning, reconnections, and real-time data display for tire temperature and pressure, eliminating manual intervention. The process increased QC throughput by 200%, enhancing both validation speed and reliability.2) Comprehensive Functional Testing for Camera PSU: Designed and implemented a rigorous testing protocol for the new Camera ECU to validate functional and custom requirements under simulated and field conditions. Utilizing PyVisa, I wrote a Python script to control a RIGOL DP711 programmable power supply and DL3021 digital load, simulating field-specific power fluctuations. This setup confirmed resilience in power cycling without manual reset, reduced manual intervention and verified the ECU's reliability. This work met stringent quality and durability standards (ISO standards).3) BLE Testing and Debugging for Camera PSU: Enhanced BLE connectivity between the Camera PSU and the AirBoxOne central unit by developing a robust Python script using BluePy. The script continuously reads sensor data, logs it, and includes automated recovery handling for connection failures, reducing connection drops by 90%. By optimizing broadcast frequency, I minimized false readings, improved debugging efficiency, and contributed to developing a higher-quality, reliable product.

San Diego, California, United States

At the Multi-Agent Robotics Lab, my focus has been on pioneering research and practical applications within the realm of autonomous systems, specifically leveraging the capabilities of Crazyflie nano-drones. My role has encompassed a broad spectrum of responsibilities and achievements:1) Autonomous Control Integration: Spearheaded the integration of ROS2 Humble with Crazyflie nano-drones using the Crazyswarm2 platform, enabling advanced autonomous control functionalities. This breakthrough was pivotal in managing multiple drones simultaneously, significantly enhancing the lab’s research capabilities in drone autonomy.2) Algorithm Implementation: Led the development of cyclic pursuit algorithms tailored for the autonomous navigation of drone fleets. This involved intricate problem-solving for multi-agent communication using VICON motion capture in real-time, contributing to the lab's pursuits in complex, coordinated drone movements.3) Flight Stability Improvement: Played a key role in integrating VICON motion capture technology with the Crazyflie nano-drones. This integration was crucial in achieving a notable 90% increase in flight stability, primarily by minimizing drift issues. The outcome not only enhanced the drones' performance but also provided valuable insights into the interplay of external sensing systems and autonomous flight control.4) Collaborative Research: Actively collaborated with a team of skilled researchers, contributing to a dynamic environment of learning and innovation. My role involved both technical expertise and collaborative skills, working closely with peers to drive forward the lab's ambitious projects.5) Research Dissemination: Engaged in the documentation and dissemination of research findings. My contributions in this area ensured that the lab's advancements were effectively communicated within the academic community, fostering further research and collaboration opportunities.

Pune, Maharashtra, India

Conducted in-depth research on hardware and software solutions for deploying deep learning Automotive Vision algorithms on an embedded processor. Collaborated with senior engineers and suppliers to identify hardware requirements.Gained hands-on experience in automotive vision systems and ADAS. Developed strong research and documentation skills in a collaborative environment. Passionate about advancements in autonomous vehicles and intelligent transportation systems.Key Contributions:1) Research: Conducted in-depth research on hardware and software solutions for deploying deep learning Automotive Vision algorithms on an embedded processor.2) Hardware Evaluation: Collaborated with senior engineers and suppliers to identify hardware requirements for efficient execution of deep learning algorithms on embedded systems. Evaluated various processors and GPUs for computational capabilities and power efficiency.3) Documentation: Created comprehensive documentation of the entire development process, including methodologies, algorithms, and system architecture. Produced a reference document for future research and development efforts.Skills Developed:1) Strong research and documentation skills.2) Hands-on experience in automotive vision systems and ADAS.3) Collaborative work in a team of experts.

India

VCSE was a learning opportunity provided by Dorle Controls LLC, consisting of an intense training phase followed by an industrial project on the ADAS domain.Training Phase:1) Fundamentals of Autonomous Mobility2) High-level architecture of Perception module involving functionality of LIDAR, Camera for Object Detection, Classification, and Localization using traditional (Sliding template) and deep learning (R-CNN and YOLO algorithm) approach3) Sensor Fusion using Multi-Object Tracker4) Prediction module consisting of an Autonomous Multi-Model approach.5) Model-based design approach to the development of ADAS features along with System architecture and testing using MiL and SiL test harnesses.Project Phase:1) Design of Forward Collision Warning (FCW) and Automated Emergency Braking (AEB) features in Simulink environment2) Extracting data from synthetic sensors using Automated Driving Toolbox for perception and prediction subsystems3) System architecture: Requirements Generation for linking the stakeholder requirements to the Controller test harnesses for verification through Mil and SiL tests

Pune, Maharashtra, India

Intern in Grinding Shop of Production Department of EagleBurgmann India Pvt Ltd.Project Title: Streamlining of grinding shopRole Objectives: 1. Identified potential areas of improvements and possible solutions to increase OEE2. Researched Universal Grinding Machines and their capacities, workflow and operations involved3. Studied production plan of grinding shop to find the theoretical process time4. Improved setup process by implementing alternative clamping methods

Pune, Maharashtra, India

Design- Development and Validation of Off-Road Powertrain componentsResponsibilities:Execute the development of the powertrain components and deliver bespoke solutions providing high performance on rough terrainsAchievements:1) Improved the performance of Continuously Variable Transmission (CVT) by eliminating slip by 100% using MATLAB modeling of Clamping force on the V belt2) Pioneered weight reduction of Powertrain assembly by 5.6 kg by optimizing fatigue life of shafts, gears, and bearings, performing DFMEA on powertrain components, and produced manufacturing-oriented CAD designs3) Validated powertrain models by designing tests and increased vehicle acceleration and transmission shift characteristics by working with Lasers, IR Sensors, and Ultrasonic sensors4) Spearheaded team to 2nd place of 250 teams in SAE BAJA and ATVC competitions cross functioning with all the subsystems (Endurance 1st, Acceleration 2nd, Cost and Design evaluation 2nd) and a cash prize of Rs. 1.75 lacs and trophies

India

Master Of Science - Ms, Mechanical Engineering, 3.671

Bachelor Of Technology, Mechanical Engineering, Cgpa 9.39/10

Activities and Societies: 1) Head Speaker AutpSpark Technical Workshop 2) SAE BAJA Team - Team Lead: Powertrains

90.31 %

5th Highest Ranker among 300 students

Ssc, 93%

Among the top 20 at the school, presented with a trophy.