top of page
Coding

HELLO, I'M

SWARALI CHINE

Software Developer and a perpetual student of life....

swaralichine.jpg

SWARALI CHINE

MS in CS at Arizona State University

schine@asu.edu

​

(480)-803-4692

  • White LinkedIn Icon
  • White Facebook Icon
  • White Twitter Icon
  • White Instagram Icon

ABOUT

MY BACKGROUND

I am a hard-working individual with proven leadership and organizational skills, and minute attention to detail. With an avid interest in software development, I have now worked on various technologies, frameworks, and tools. I constantly challenge myself to develop new ideas and apps.My strong communication skills and leadership abilities have allowed me to take on new endeavors and succeed.

​

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

About

EDUCATION

WHAT I’VE LEARNED

August 2021 - May 2023

Degree :    Master of Science

Course :    Computer Science

University : Arizona State University

GPA : 3.78/4.0

July 2015 - June 2019

Degree : Bachelor of Engineering

Course : Electronics and Telecommunications

College : Pune Institute of Computer Technology

GPA : 8.62/10.0

EXPERIENCE

WHERE I’VE WORKED

Emetric,LLC

DevOps Engineer Intern : May 2022 - Present
  • Working on developing operations, automating operational processes, managing continuous delivery systems, and maintaining cloud services.
  • Technology - Microsoft Azure, DevOps

Arziona State University 

Graduate Statistics Tutor : Dec 2021 - May 2022
  • Tutored 150+ students in the areas of Statistics,Data Analysis,Data Visualization using hypothesis testing (T-test,ANOVA test) and regression models (Logistic, Linear) with the help of Python,SPSS,RStudio,TABLEAU,Microsoft Excel and MATLAB.
  • Technology used - Python , R ,SQL, Excel, PowerBI, TABLEAU

Yardi Software India Pvt Ltd

Software Engineer : Aug 2019 - Aug 2022

  • Understanding requirements, Designing and developing and implementing systems. Coordinating with client, dev ,QA and implementation team to complete the projects. SQL server, BI and Visual studio being the most proficient areas.I was responsible for understanding the custom requirements of international clients and delivering the solutions as per the specifications.
  • Technology-  Python,SQL,MSSQLServer,C#,.Net,SSRS,Excel
Education & Experience

TECHNICAL SKILLS

WHAT I BRING TO THE TABLE

  • Programming — C/C++, Java, Python, R
  • Frontend — JavaFX, HTML, CSS, Bootstrap, Javascript
  • Backend — NodeJS, PHP, SQL/MySQL
  • Industry Knowledge — OOPS, Data Structures, Algorithms, Software Engineering, Machine Learning, Team Software Process, Agile Development, Cloud Computing
  • Technology — Linux, Git (VCS), Android,Azure, AWS
Skills & Languages

PROJECTS

AWS Face Recognition as a Service (PaaS)

  • A real - time face recognition application which is server-less and uses Function as a Service model of cloud computing.
  • Raspberry Pi is used as the edge device to record videos and AWS Lambda function based on a container image(deep learning model) is used to provide the face recognition service.
  • Technology used - Python, Docker, PyTorch, AWS Lambda, AWS S3, AWS DynamoDB, AWS API Gateway , AWS Raspberry Pi

AWS Face Recognition as a Service (IaaS)

  • Designed a face recognition REST Service based on a deep learning model (CNN), AWS services(S3,SQS,EC2) and Java Spring Boot which can scale out and in based on user demand and handle multiple concurrent requests.
  • Technology used - Python, AWS S3, AWS SQS, AWS EC2, Java Spring Boot

Movie Recommendation Engine

  • The entertainment industry today is massively driven by Movies.Ever since the emergence of on-demand platforms like Netflix, Prime-Video, etc. the need to leverage data and technology to streamline the process of content consumption has increased manifold.​
  • With the advent of Machine Learning, these platforms can accurately recommend movies to watch based on our watching habits.
  • These models use clustering techniques to identify data points to make accurate predictions.
  • In this project, we aim to compare such models using Collaborative Filtering and Matrix Factorization and Item-based KNN, and test it on the 20M MovieLens dataset to predict users' movies to watch.
  • Technology used - JavaScript, Jupyter Notebook, CSS, HTML, Python, Perl, Shell

Continuous Glucose monitoring system

  • Developed and trained a machine learning model on various machine learning algorithms viz. Logistic Regression, Random Forest, GaussianNB, SVM, K-Nearest Neighbor to predict the timing of insulin ingestion by guessing meal intake from Continuous Glucose Monitor’s data.
  • Technology used - SARIMA, RNN, KALMAN

Gesture Classification for SmartHome

  • The SmartHome Hand Gestures Classifier; classifies a gesture video of 5 seconds into one of the 17 gestures for controlling SmartHome appliances.
    The prediction is done using the CNN algorithm.
  • Technology used - Python, Deep Learning

SmartHome - Gesture Control Application

  • System to watch and practice SmartHome gesture videos. Functionality to watch, record and send videos to cloud server to store using Restful API.
  • The user is shown a video of a gesture.
    The user can replay the video at least 3 times.
    Upon clicking the “PRACTICE” button, the user can capture his or her own video through the smartphone’s front camera for a period of at most 5 seconds.
    The videos are uploaded to a server.
  • Technology used - Java, Android Studio

COVID-19 Symptom Checker

  • Developed an Android App that measures Heart-Rate, Respiratory-Rate (Using sensor values and Peak detection Algorithm) and collects COVID-19 related symptoms and stores them in a database in the smartphone

  • Android App that collects COVID-19 related symptoms and stores them in a database in the smartphone The app has 2 pages.

  • In the first page it presents the user with two sign measurement techniques: a) heart rate sensing, and b) respiratory rate sensing.

  • Technology used - Java, Android Studio

Handwritten Image Detection with Keras

  • Developed and trained model using CNN to classify data.
  • The dataset used for the famous MNIST dataset.
  • Technology used - Java, Android Studio

Sign Language Conversion For Tiny-Tots

  • Built an educational module to teach English grammar and spellings to physically challenged children by training a dataset of 10000+ images using CNN.
  • Developing a testing platform wherein students displayed the spelling of the word displayed on the screen.
  • The camera captured the images and then classified it using the pre-trained network.
    Based on the classification the results were displayed.
  • Technology used - Matlab, Deep Learning, CNN, HTML,CSS,Javascript
Awards & Interests
bottom of page