State University Software Engineer

NEHA JAYAPRAKASH

*************@*****.*** 657-***-**** https://www.linkedin.com/in/neha-jayaprakash-247a06135/

Highly skilled technology professional with experience in building complex applications leveraging machine learning & deep learning frameworks; proficient in python and solving complex problems with a proven track record of using unconventional and innovative methods to develop new solutions. Adept at application development using: HTML/CSS and JavaScript.

CORE COMPETENCIES

Programming Languages & Libraries: Python, C,C++, CUDA, OpenCV4Tegra, Visionworks, R,

Deep Learning Tools & Frameworks: Jetson Tx2 Jetpack, Caffe, Tensorflow, NVIDIA DIGITS, Theano, Yolov2, PyTorch, Vim, OpenCV.

Tools & Servers: Anaconda Navigator, Spyder IDE, Flask, RStudio, VS Code, MATLAB, Toad, Microsoft Suite (Word, Excel, PowerPoint, Access)

EDUCATION

Master of Science in Computer Engineering May 2018

California State University, Fullerton GPA: 3.9

Coursework

Computer Vision, Machine Learning, Artificial Intelligence, Operating System Design, Advanced Computer Architecture, Modern Software Management, Advanced Computer Networking,

Bachelors in Telecommunication Engineering May 2015

Dayananda Sagar College of Engineering, Visvesvaraya Technological University GPA: 3.8

PUBLICATIONS

Harkishan Singh Grewal, Neha Thotappala Jayaprakash, Aaron Matthews, Chinmay Shrivastav, and Kiran George, “Autonomous Wheelchair Navigation in Unmapped Indoor Environments”, Paper accepted in IEEE I2MTC 2018 Conference and anticipated to be published in May 2018

H.N.Shruthi, Lingaraju.B.R, Neha Jayaprakash, Vaibhavi.D.R, Smitha Sasi, “A Robustic Cryptosystem using Astroid Curve over Prime Field”, International Journal of Engineering Research And Management (IJERM)ISSN : 2349- 2058, Volume-02, Issue-05, May 2015

WORK EXPERIENCE

Associate Software Engineer, Accenture, Bangalore, India June 2015 – July 2016

Was Involved in the development and testing of a tool called We@Accenture.

Involved in code reviews and mentored the team in resolving issues. Involved in configuring and deploying the application using WebSphere.

Integrated solutions to the database and kept track of updates, errors occurred in the tool and rectified them immediately

Graduate Web Assistant, California State University, Fullerton May 2017-Present

Expert in programming languages including C, Python, HTML5, CSS, Bootstrap, jQuery, JSON.

Demonstrated expertise in UI design for Library website and integrated UI Components in text editing environment.

Demonstrated expertise in development and test automation of web applications using QUnit and Dojo third party libraries.

Worked on Optical Character Recognition to digitize the books.

PROJECTS

Object Detection for Autonomous Navigation in Unmapped Indoor Environment, California State University

Created and developed custom object detection models using Tensorflow, DIGITS, YoloV2 and MATLAB where it was used by autonomous wheelchair for navigation in an unmapped indoor environment.

Adapted the trained model to work on recorded as well as real time video streams using OpenCV.

Demonstrated Expertise in path planning for unmapped navigation integrated with Robert Operating System(ROS) using RPLIDARA2.Worked on Proximity Sensors and rotary encoders for safety mechanism of wheelchair.

Robotic arm was built for the computer vision system to pick up the destination and send it to ROS.

Experienced in working with ZED Stereo Camera for positional tracking and spatial mapping embedded with Jetson Tx2.

Incorporated HMC5883l magnetometer to know about the path traversed by the wheelchair to the destination.

Facial Expression Recognition, California State University

Developed a robust facial expression recognition system based on extraction of facial features using suitable algorithms of the face geometry and approximation techniques such as Convolution algorithms.

Adapted the system to work on picture, recording & live stream. Integrated audio module which speaks out the average expression of respective file.

The proposed method achieves competitive results with an accuracy of 91%. Used Python and Flask.

Sentiment Analysis of Opinionated Data, California State University

This project focused on predicting positive or negative orientation of tweets based on sentiment lexicon using R programming language.

A GUI was developed using R-Shiny & all the visualization graphs and charts were rendered on user interface. Data cleaning, transformation and manipulation was done using R.

Contact this candidate