Projects Summary

Enterprise Data Infrastructure Enhancement (Nikola Motors)

  • Led a critical infrastructure project, collaborating closely with management

  • Achieved 98% data accuracy and 25% faster processing

  • Expanded database capacity to support 45% fleet growth using PostgreSQL and AWS services

ETL Pipeline Optimization (Nikola Motors)

  • Deployed multiple Python-based ETL pipelines using Apache Airflow

  • Implemented parallel processing techniques, boosting efficiency by 35%

Fleet Summary Dashboard (Nikola Motors)

  • Designed and implemented a comprehensive dashboard to provide real-time insights into Nikola's vehicle fleet

  • Integrated data from multiple sources to create a unified view of the fleet composition

  • Developed a materialized view to efficiently categorize and summarize data on fuel cell trucks and battery electric trucks

  • Created an interactive Power BI dashboard for visualizing fleet statistics and trends

CAN Signal Monitoring System with Power BI Dashboard (Nikola Motors)

  • Developed a sophisticated system to track and analyze truck performance in real-time

  • Created an interactive Power BI dashboard to visualize the percentage of trucks reporting signals

  • Implemented features like real-time tracking, dynamic calculations, and geospatial visualization

  • Achieved significant improvements in fleet management and data reporting compliance

ASU Internship Application Platform

  • Implemented Power Automate Cloud Workflows to automate internship agreement signing process

  • Reduced manual execution time by over 95%, significantly enhancing efficiency

  • Developed SQL scripts to normalize data acquired from AWS Redshift

  • Created Tableau web dashboard for efficient querying of student placement and paid internship agreements

Creating Marketing Profiles for Individuals (Class Project, Spring 2023)

  • Extracted insights from US Census data to boost program enrollment using data visualizations

  • Designed and implemented a Neural Network-powered application for predicting ideal candidate demographics

  • Achieved 98% accuracy in predicting demographics of ideal candidates for college programs

Network Security in IoT Systems (Academic Research)

  • Analyzed machine learning algorithms for detecting DDOS and DNS attacks

  • Evaluated prevention techniques and performance metrics

  • Identified optimal algorithms for various security scenarios

Multispectral Image Super-Resolution (Academic Publication)

  • Conducted research on advanced techniques for enhancing multispectral image resolution

  • Developed and implemented novel algorithms for image processing and enhancement

  • Published findings in a peer-reviewed journal/conference