Engineer Software

SARALA RAVINDRA

www.linkedin.com/in/sarala-ravindra

**** ****** **, ****, ******** 48083

+1-906-***-**** *******.********@*****.***

SUMMARY

Software Engineer in automotive industry experienced in data analysis (sensor and spatial data), Embedded Software Systems, Image processing, automotive communication systems seeking full-time opportunities. EDUCATION

Master of Science in Electrical Engineering Aug 2016 - May 2018 Michigan Technological University, Houghton MI, GPA: 3.37/4.00 Coursework: Wireless Embedded Sensor Networks, Distributed Embedded Control Systems, In-vehicular communication, Machine Learning, Probability and Stochastic Processes, Image Processing, Robotic vision. Report: Tra c Sign detection methods

Bachelor of Engineering in Electronics and Communication Engineering Aug 2012 - Mar 2016 Visveswaraya Technological University, Karnataka, India, GPA: 3.5/4.00 SKILLS

Python SQL GUI development C++ PySpark

OpenCV CNNs Machine Learning MATLAB/Simulink ECU design/calibration

V2X Linux Image processing CANv2.0 OpenStreetMap, GIS WORK EXPERIENCE

General Motors LLC Nov 2019 - Present

Software Engineer, Connected Vehicle Research (Data and Analytics) - Contingent worker Warren,MI

Analyze vehicle signals from test vehicle CAN messages and company database (real world data) to build new product using python, pandas, SQL, pySpark, Hue environment

Create custom geometric segments using Open Source Routing Machine(OSRM) services to scale and analyze large-scale spatial sensor data and build automated pipelines - geohash, folium

Model applications using crowd sourced data to identify key metrics to produce estimation models based on target market - OpenCV, SciPy modules

Danlaw Inc. Feb 2019 - Oct 2019

Engineering Intern, Connected Vehicle Systems Novi, MI

Prototype python kivy based GUI to demonstrate Connected Vehicle (V2X) applications at Intelligent Transportation Society America 2019 - trade show

Emulate V2X applications(Emergency vehicle requesting tra c light preemption) using micro controllers

Interact with potential clients on V2X products collaborating with the sales team, Market Study on recent trends in connected vehicle sector

Meograph Inc. July 2019 - Dec 2019

Programming Intern Atlanta, GA

Optimize Facial key-point detection and tracking using Objective C for an iOS application ECE lab, MTU Jan 2018 - Apr 2018

Teaching Assistant Houghton, MI

Handled 3 sections of students in Electric Circuits 2 lab.Circuit debugging, code debugging to perform electrical lab experiments and simulate the results NI Multisim software. PROJECT EXPERIENCE

Control Area Network (CAN) Communications Aug 2017 - Dec 2017

Setup CAN communication between multiple CAN nodes using (Arduino 2560 and CAN shield (MCP2515 CAN controller with the MCP2551 CAN transceiver)). 1. CAN node ID ltration and masking

2. Obstacle detection, Buzzer control, DC motor speed control 3. ADAS Autonomous parking using servomotor (to orient sensor),ultrasonic sensor(object distance and presence) with multi-chasis

4. Encode,decode CAN messages transmitted between a laptop and an HEV powertrain control modules using CANking through it’s On-Board Diagnostics-OBD II Remote Electronic Control via CAN to control HEV control modules Jan 2017 - May 2017

Hardware in Loop (HIL) based simulations of Hybrid Electric Vehicle(HEV) control modules: electronic throttle control using PID controller, stepper motor, spark ignition, fuel injection.

Implemented CAN between the Electronic Control Units (ECUs) monitoring the control modules. Cali- brated/validated the model on Freescale MPC565 Woodward’s ECU using MotoHawk, MotoTune and CANKing.

Model logic for Driving mode, Engine static status, engine start/stop, electric motor start/stop, stepper motor, blend factor

Smart Farming via Distributed Sensing Network Sep 2016 - Dec 2016

Designed wireless embedded sensor network using TelosB Nodes & Raspberry Pi to periodically monitor the health of plants in a farm by sensing data (Humidity, Temperature, light)

Monitor changes in farm data both numeric, modelled logic to warn of extreme conditions. Programmed using C++

Research - Study on Various Tra c Sign Detection Techniques Jan 2018 - Apr 2018

Surveyed various tra c sign detection methods as a part of my directed study under Dr.Michael C. Rogge- mann.

The study included color-based(RGB, HSV, IHLS) segmentation, shape-based(Template matching, Hough circle) segmentation, other features (HOG, BRISK, ORB descriptors) based detection and YOLO detection

Introduced to various neural networks such as RCNN, Fast RCNN and Faster RCNN nets to localize objects. Vehicle detection using Machine learning Jan 2018 - Feb 2018

Implemented Support Vector Machine (SVM) classi er trained on Histogram of Oriented Gradients (HOG), color features for vehicle detection on a vehicle onboard video. Programmed in python, Used max suppression method to eliminate redundant detection by sliding window approach Single Object Tracking in a tra c Video based on Correlation Detection Mar 2018

Developed Correlation based object detector to track a moving ball in a game video.

25 percent reduction in per frame processing time by limiting the region of object search compared to traditional correlation based trackers.

The limitation of region of search is achieved by prediction of the possible position co-ordinates of the object in the incoming frame by keeping track of a set of the previous frames position coordinates.

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