• Hi!
    I'm Vaishnavi

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    Embedded
    Systems Engineer

About Us

Who Am I?

Hi I'm Vaishnavi Patekar a graduate student pursuing my masters in Electrical & Computer Engineering , specializing in Embedded Systems at University of Colorado, Boulder. I have significant years of work experience with the automobile domain where I learnt a lot about model-based design & development, Control Systems and Embedded Systems. With my interest to deep dive and learn embedded systems in detail, I'm looking forward to drive my career in the field of Embedded Systems.

My Specialty

My Skills

Programming Languages:

Python

C, C++

m-script (MATLAB)

Protocols: UART, SPI, I2C, CAN

Hardware:

KL25Z (Cortex M0+), 8051

Blue Gecko EFR32BG22

Simulation Tools:

Simscape, Simulink, Stateflow,Targetlink

MCUExpresso, Simplicity Studio,Keil uVision

Domains:

Embedded - Software/Firmware, Device Drivers

Computer architecture, Embedded - Hardware

Education

Education

Courses: Embedded Systems Design, Practical PCB Design & Manufacturing

Courses: Principles of Embedded S/W, IOT Embedded Firmware

Gogte Institute of Technology, Belgaum, India

Experience

Work Experience

Software Engineer, Body Control Module (BCM) Jul’20 – Jun’22

Mercedes-Benz Research & Development Center, India

  • Developed software for the Automobile Body Control Module (BCM) subsystems - Interior lighting, Electric seat adjustment UI, Power window control, Power sunroof operation
  • Spearheaded software development life-cycle from requirement analysis to validation of multiple features of BCM subsystem
  • Performed and improved code/model coverage for MIL (Model in loop) and SIL (Software in loop)

Software Engineer, Power-train Module for Renault-Nissan Jul’20 – Jun’22

Software Development for Engine Management Control System (Coding and Unit Testing)

  • Performed modeling and simulation of automotive power-train modules - Engine Control Module
  • Development of abstraction architecture in compliance with AUTOSAR (Standardized automotive software architecture)
  • Plant model development for sub-components of power train module - Torque Converter, Gear Box, and Vehicle Dynamics.
  • Expedited the verification and validation timelines by developing novel algorithms for virtual validation of systems, replacing traditional hardware setup for HIL (Hardware-in-Loop) testing
Publications

Publications

Novel Static Multi-Layer Forest Approach and Its Applications

by Vaishnavi Patekar, Ganesh Bhagwat,Shristi Kumari, and Adrian Marius Deaconu

This paper presents a new method for representing multi-layer forest data structure in array format. It also explains various tree operations, unique data compression algorithm and migration algorithm between traditional approach and the proposed data structure. Most of the fundamental algorithms like those from artificial intelligence that employ decision trees are based on trees/forest data structure. The current paper brings a completely new idea in the representation of these data structures without employing recursion and targeting memory optimizations with reduced code complexities.

Projects

Projects

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Nov 25, 2022 | Firware | 4

Pothole Detection System

Designed a real-time pothole detection system using FRDM- KL25Z Cortex M0+ board, interfaced with an I2C-based MMA8451Q accelerometer. Developed a PT1 filter algorithm for real-time data accuracy.

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Dec 01, 2022 | IoT | 4

Automatic Brightness Control System

Bluetooth-based client-server implementation using Blue Gecko EFR32BG22.Interfaced a low-energy BLE device hosting Luminosity Sensor and a client hosting a gesture sensor

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Sept 30, 2018 | Automotive Control System | 4

Automotive Body Control Module Development

Facilitated simulation of car’s body control modules’ software components - Wiper Control Module, Power Window, and HVAC.Acquired skills in understanding and analysis of system requirements, model-based development, unit testing & integration testing

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April 14, 2018 | Deep Learning and AI | 4

Facial Expression Recognition using Deep Learning Techniques

Developed a CNN model using logistic regression to predict and classify facial expressions.Trained the CNN model using standard datasets Ck+ and KDEF and achieved an accuracy of 86%.

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Oct 20, 2017 | Firmware | 4

Navigation Assistance System for visually impaired people

Built an end-to-end low-cost product prototype for a visually challenged person to provide navigation assistance.Raspberry Pi-based wearable equipment consisting of earphones and a hand stick to assist in navigation by aiding in obstacle detection.

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Aug 5, 2020 | Vehicle Prognosis | 4

Vehicle Diagnostics Blog

Collaborated for content and blog creation for Vehicle prognosis and diagnosis in the virtue of Electronics and AI relevance.Contributed to developing the software and testing architecture platform based on a CI/CD workflow.

Get in Touch

Contact

vaishnavipatekar98@gmail.com

Boulder, Colorado - 80303