Projects

saFe-n-b | Web Application

  • Developed a web application for businesses in F&B industry to aid them with their operations in COVID-19 times.
  • Web scraped latest COVID-19 regulations and statistics using jsoup and displayed them in a dashboard
  • Added employee management to allow businesses to track employees’ vaccination and COVID test details

PSA Vessel Schedule Tracking | Web Application

  • Developed a web application to allow PSA to track its vessels.
  • Features include automatic scheduling of API calls, table sorting/ filtering, user login and registration using JWT.

Jobility | Web Application

  • Developed a prototype for a platform that bridges the employment gap for Persons with Disability (PWDs).
  • It uses AI technology to tailor the matching process between skillful PWDs and suitable employers
  • Features include a deep learning recommender, speech recognition and employee leaderboard.

Portfolio Performance | Android Application

  • Developed an Android application which downloads historical stock data from finnhub for a given stock, persists it in SQLite database and calculates performance metrics.
  • Utilized various Android components, such as Activities, Services, Content Providers, Broadcast Receivers and Intents
  • Performed concurrency, synchronization and multithreading to optimize performance and improve interactivity

Understanding Location-Based Recommendations | Data Structures Research Project

  • Implemented unbalanced k-d tree, balanced k-d tree, and vantage point trees in Java to find the list of businesses in the Yelp Business Dataset within a cutoff distance from a given input coordinate.
  • Thoroughly analysed the time and space complexities of the data structures; adapted latest research on balancing k-d trees using recursive partitioning and presorting.

Behind the Scenes | Computer Networking Research Project

  • Used Wireshark to evaluate the efficacy of Android’s restricting background network activity feature.
  • Ran tcpdump on a VPN server to capture network packet information; used iptables to configure firewall rules to block destination ports 80 and 443; compared the network traffic of common messaging applications
  • Identified the servers messaging applications communicate with and frequency of communication with server.

Self-Trained Knowledge Distillation | Deep Learning Framework

  • Proposed a novel framework combining self-training with knowledge distillation for semi-supervised few-shot classification. Experimented with various knowledge distillation mechanisms.
  • Evaluated the method on a popular few-shot benchmark- miniImageNet- and achieved results comparable to state-of-the-art methods for semi-supervised few-shot classification.

Data Modelling of Wine Quality | Machine Learning Model

  • Built a multiple linear regression model to model the relationship between wine’s chemical attributes and quality
  • Performed EDA and correlation analysis for feature selection, 100-fold cross-validation and subsequently sensitivity analysis to select the best models, and clustering to further investigate the effect of features on wine quality rating

Sarcastic Headline Detector | Machine Learning Model

  • Built a binary decision tree classifier with 91% ROC AUC score of detecting whether a news headline is sarcastic.
  • Used spaCy for natural language processing, scikit-learn to generate n-grams and to train and evaluate multiple models, including Naıve Bayes, Logistic Regression etc.

Attendo | Android Application

  • Developed an Android application which automates employee attendance tracking using geofencing
  • Used Java for backend, Firebase Authentication for user authentication, Firebase Realtime Database to store employee and employer data, and radar.io API to integrate the geofencing technology.