Projects

Energy and Weather Data Integration Pipeline

Collaborated with 5 others to create an ETL data pipeline in Google Cloud Platform (GCP) that integrates data from five live sources of data, processing millions of rows in real-time.

Technologies:

PythonPySparkGoogle Cloud PlatformETLAPI Integration

Key Outcomes:

  • Developed python code that runs on a scheduler to fetch data from APIs at regular intervals
  • Created scalable pyspark code that runs on clusters to clean, process and integrate from various sources in Google Cloud Platform
  • Processed millions of rows of data in real-time

An Observational Study of iPhone Users

Conducted an in-depth study of iPhone usage patterns to understand the factors that influence purchase decisions. Interviewed over 30 users and analyzed market trends to identify key drivers of adoption.

Technologies:

Research MethodologyData AnalysisPowerBIUser Interviews

Key Outcomes:

  • Developed a research plan and methodology
  • Collaborated with a team to collect and analyze data
  • Used PowerBI to visualize data and communicate findings to stakeholders
  • Identified key findings, including the importance of iMessage for iPhone users
  • Recommended Apple to adopt cross-platform messaging standards

An Observational Study of iPhone Users

Conducted an in-depth study of iPhone usage patterns to understand the factors that influence purchase decisions. Interviewed over 20 individuals and analyzed market trends to identify key drivers of adoption. Developed a research plan and methodology, and collaborated with a team to collect and analyze data. Used PowerBI to visualize data and communicate findings to stakeholders.

Technologies:

Research MethodologyData AnalysisPowerBIUser Interviews

Key Outcomes:

  • Identified key drivers of iPhone adoption
  • Highlighted the importance of iMessage for iPhone users
  • Recommended Apple to adopt cross-platform messaging standards

Shift Your Focus: Spreading Awareness for Safe Driving in the Digital Age

As part of the Info Challenge at UMD, collaborated with a team of 4 to analyze a survey dataset from the Washington Traffic Safety Commission (WTSC) in order to evaluate public knowledge and adherence to traffic laws enacted in 2018.

Technologies:

PythonTableauPowerBIData Analysis

Key Outcomes:

  • Utilized Python, Tableau, and PowerBI to identify key parameters and subgroups within the dataset
  • Recommended social media campaigns on YouTube and Facebook to raise awareness among 18-29 year-olds
  • Based recommendations on insights from PewResearch center social media usage dataset

Socioeconomic Disparities in California's Water Quality

Conducted a data-driven research project comparing water quality between counties in California to analyze potential socioeconomic disparities.

Technologies:

Data CleaningStatistical AnalysisTwo-sample t-test

Key Outcomes:

  • Utilized multiple data sources and data cleaning techniques
  • Performed a two-sample t-test to assess differences in water quality parameters
  • Provided insights for policy recommendations and suggested further research

TerpGymBuddy

Led the product direction for a team of 4 to design a website that recommends exercises and time slots to UMD students based on their class schedules.

Technologies:

AngularJSMySQLProduct Management

Key Outcomes:

  • Scoped out features/user requirements
  • Built a product roadmap
  • Created a detailed design report before implementing the project

Distance Estimation Technique for Autonomous Vehicles

Led the development of a vision-based system for autonomous vehicles to identify, track, and estimate distances from neighboring vehicles in real-time using YOLOv4 and Deep SORT algorithms.

Technologies:

PythonTensorFlowOpenCVYOLOv4Deep SORT

Key Outcomes:

  • Devised a method for estimating distance by correlating parameters of bounding boxes with the distance between vehicles
  • Implemented the solution using a combination of Python, TensorFlow, and OpenCV libraries

Smart Cart

Collaborated with three others to develop a Shopping Cart that works in real-time with the Android Application.

Technologies:

Raspberry PiIoTFirebaseAndroid

Key Outcomes:

  • Used Raspberry Pi, camera, LiDAR sensor as hardware and Firebase as a database
  • Automated the Supermarket shopping experience for the customer using IoT

Loan Eligibility Predictor

Designed a Loan Eligibility Predictor as part of Oracle Build-A-Thon that enables banks to sanction loans easily.

Technologies:

Machine LearningLogistic RegressionData Pre-processing

Key Outcomes:

  • Performed data pre-processing to fill missing values, removed irrelevant fields
  • Used Logistic Regression Machine Learning model to predict with a high accuracy rate

Appointment Application for Hospital

Built an Android App for the Ministry of Aayush that enables patients to book an appointment with a doctor and their preferred time as part of the Smart India Hackathon in 2020.

Technologies:

Android StudioJavaFirebase

Key Outcomes:

  • Developed an Android application for booking doctor appointments
  • Used Firebase for authentication and database