PRIYA YADAV
[ addbr8@r.postjobfree.com Ó 735-***-**** Bengaluru, Karnataka
https://www.linkedin.com/in/priyayadav312/
https://github.com/Priya312
PROJECTS
Hydration Reminder:
An app that reminds you of drinking water
when you are not using your phone or basi-
cally if its on charge with the help of a notifi-
cation.
News App:
An app that uses the retrofit to fetch the news
data from newsapi.org and display it on the
app.
URLOC:
An app that helps to locate your indoor posi-
tion using fingerprint matching of already col-
lected data(using the same app) and machine
learning algorithm.
Speech to text/Text to speech:
The app converts the words spoken in En-
glish language into text and shows up on the
screen. Similary the other app which takes in
the input text and reads it aloud in English.
PROGRAMMING SKILLS
Languages : Java C/C++ Javascript
Frameworks : Vertx Spring Boot
HTML/CSS/BootStrap
Databases : HSQL SQL
Tools and IDEs with : LATEX IntelliJ
STS Android Studio
LANGUAGES
English
Hindi
CERTIFICATIONS
Mathworks OnRamp - MATLAB
Udacity - Android Development
EXPERIENCE
Graduate Engineering Intern - Java/Vert.X/Gradle
Dell Technologies
Jan 2020 Bengaluru, Karnataka
Worked on Vertx framework for Java it helps to write concurrent applica- tions i. e., parallel asynchronous calls for collection of data from multiple different machines.
Designed feature which periodically purged the database and file system for above collected values
Worked for the formation of cron jobs to help run the Job scheduled periodi- cally.
Android Developer Intern - Android Studio/Java
Leap and Scale
May 2019 – July 2019 Pune, Maharastra
Under the guidance of Prof. S. Tapaswi and Dr. Neetesh Kumar, worked on an app which was a locator and collector of the travellers data.
Also used to track Hours of Service (according to US mandate), to check on the traffic related rules.
Research
ABV-Indian Insitute of Information Technology and Management, Gwalior
May 2018 – Sept 2018 2018 Gwalior, Madhya Pradesh
Created an Android App URLOC which used the wifi signal data and machine learning algorithms to predict the users’ location in indoors where GPS fails to work.
The accuracy of the prediction was 83%
EDUCATION
B.Tech + M.Tech (CGPA: 8.39)
ABV Indian Institute of Information Technology Gwalior
July 2015 - May 2020 Gwalior, Madhya Pradesh
Higher Secondary (ICSE/ISC: 95%)
Mother Teresa Mission Higher Secondary School
July 2013 - May 2015 Kanpur, Uttar Pradesh