Engineer Software

Sriharsha

Santhapur

Computer Vision Engineer

Skilled in Machine Learning, Computer Vision.

Experience in Model verification and validation.

Good Understanding of Statistics, Probability.

*********.****@*****.***

+91-998*******

Hyderabad, India

linkedin.com/in/sriharshasanthapur

github.com/harshasanthapur

WORK EXPERIENCE

Specialist

ZF Tech Centre India

08/2017 - Present, Hyderabad, India

Defined performance benchmarking for Vision Fail-Safe algorithms and to evaluate them;

Designed and Implemented an algorithm to compute the level of global blur in an image;

Conceptualized CNNs for Camera Full and Partial

Blockage detection, Blur detection from scratch and designed an architecture to detect Small Obstacles; Implemented a semi-autonomous labeling tool (object detection and object segmentation) using Active

Learning ;

Leading a team of size 4;

Specialist

TATA Elxsi

07/2016 - 08/2017, Bengaluru, India

Designed and developed the concept for Adaptive Front Lighting System with 16X16 grid LEDs ;

Derived the design hypothesis and redesign the model architecture;

Defined the Control Logic to calculate object distance; Defined patterns for LED Illumination based on Object Detection;

Software Engineer

KPIT Technologies

08/2014 - 07/2016, Bengaluru, India

Implemented complex algorithms to simulate sensor

behavior using synthetically generated environment data

(Sensor Simulation);

Responsible for Testing and Validation of algorithms to increase the safety of automated driving;

Saved test drives on an average distance of 1000 miles per month;

SKILLS

Python Machine Learning Deep Learning

Computer Vision MATLAB Simulink C

EDUCATION

Master of Science

Blekinge Institute of Technology, Sweden

02/2009 - 10/2011, Karlskrona, Sweden

PUBLICATIONS

Nandyala, S., Santhapur, S., Kumar, K., and Manalikandy, M., "Controlling LED Based Adaptive Front-Lighting System Using Machine Learning," SAE Technical Paper 201*-**-****, 2018

Simulation of DC/DC Converter: A current sensing

Technique

ISBN10: 384730449, ISBN13: 978**********

COURSES

Convolutional Neural Networks

Coursera

Machine Learning

Stanford University

Deep learning Nano Degree

Udacity

SUPPORTED CAUSES

Child Education Women Safety Clean and Green

INTERESTS

Reading Photography Travelling

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