I’m a passionate Frontend Engineer with 6+ years of experience building beautiful and scalable web applications

rachita bhagchandani  • Peerlist

- Developed a secure Django based social networking web app with a payment portal. The website was secure against various possible attacks like XSS, CSRF, SQL injection, DDos, slowloris etc.
- Used tools like Burp suite, wireshark and snort to find security vulnerabilities in  other websites.

A Secure Social Networking Website and Paymen

- Predicting Twitter trends plays an important role in predicting public opinions on various issues like politics, sports, economy, etc.
- In this research, I have first analyzed which features can be used for trend prediction and then applied various classifiers to predict trends.

Twitter Trends Analysis and Prediction

- Analyzed various statistics and real-time parameters from a real pcap trace file, which was generated while downloading a file in a wireless setup, using python.
- Simulated the same experiment using NS-3 network simulation tool and analyzed the parameters for network trace file of simulated experiment and enhanced simulation model to reflect real life scenario.

Understanding Network Performance in Dense Wi

- Motivation of the project is improving health care facilities in rural India by empowering the ASHA workers. The focus was to leverage smart-phones for providing them a peer-learning platform, keeping in mind the low-bandwidth situation in rural areas. 
- My work was focussed around research for a suitable protocol and working on backend of the mobile application.

LEAP: A Smart-phone based Platform for Delive

Designed and developed an android application “Knapsack” for travel enthusiasts which helps you up your travel quotient and recommends travel destinations to visit according to your interests. It also helps you record your travel log and flaunt it in your circle.

Knapsack Travel App

- Extracted around 10k tweets using Tweepy and annotated them manually as depressive/non-depressive for applying supervised learning algorithms.
- Applied various supervised learning algorithms like Naive Bayes, SVM, KNN and Logistic Regression. Achieved highest accuracy of 78% using Logistic Regression and highest precision of 0.8 using SVM. 
- Analyzed trends in twitter users by extracting their previous tweets and predicted the onset of depression in user. This can prove to be very helpful in early detection of depression trends in users.

Detecting Depression in Twitter Users

- Designed and developed an Android Mobile Application which helps people in finding a nearby parking location, select a booking slot and make an online booking for the same.
- A separate mobile application was also developed for parking lot owners for managing the bookings.

Find A Spot

- Built a desktop application that helps patients in finding a doctor according to their requirements and book an appointment. Doctors, on the other hand, can create prescriptions, manage their schedules and appointments.
- The application was developed using JavaFX and SQL.