Vedant Patel

Experience

• 

  Artifintel Private Limited

  Nov 2021 - Dec 2021

  Data Science Intern

  Developed a Minor Project related to Boston Housing Pricing Prediction with a regression score of 0.815. Following that our team worked on a Major Project which involved Predicting Breast Cancer. We also created a web app UI for the major project. I learned various Data Science libraries such as Pandas, Numpy, Matplotlib, Scikit-learn, Streamlit, etc.

• 

  Google Developer Student Club @ UC Davis

  Sept 2022 - Sept 2024

  • Spearheaded AI/ML projects including a music recommender and medical chatbot, while organizing industry expert lectures, resulting in 35% increase in user engagement and 40% growth in professional network. Led a team of 5 tech developers to develop and deploy cloud computing projects

  • Technical Director

    Sept 2023 - Sept 2024

  • Executive Technical Lead

    Sept 2022 - Sept 2023
• 

  UC Davis John Muir Institute of the Environment

  Jan 2024 - Jul 2024

  IT Support Specialist

  • Managed and streamlined the IT ticketing system for the Institute of Environment at UC Davis, ensuring timely and effective resolution of technical issues faced by faculty and researchers.• Developed an automated script to integrate software-generated diagnostics for error and malware detection into the ticketing system via email, enhancing issue tracking efficiency and reducing response times by 15%.

• 

  CodeLab

  Jan 2024 - Mar 2024

  Project Manager

  • Led the Summarizit project team to develop an innovative web application that analyzes and summarizes extensive video content, resulting in a 40% increase in user productivity and information accessibility.• Engineered scalable web applications with React, NodeJS, Express, and MongoDB optimizing CRUD routes to increase data retrieval speed by 40% and enhance overall system performance by 25%

• 

  University of California, Davis

  Feb 2024 - now

  Machine Learning Research Assistant

  • Achieved efficient binary classification of ECG signals with 92.8% accuracy by ensemble Random Forest Classifier (TinyML) while significantly enhancing battery life through efficient low-power algorithms.• Employed advanced feature engineering and XGBoost ensemble modeling, achieving a remarkable 93.6% accuracy in predictive analysis through fine-tuning and strategic hyper-parameter optimization with GridSearchCV, enhancing the robustness of anomaly detection.• Implemented SHAP and LIME techniques to refine Multi-layer Perceptron, Deep Neural Network, and Recurrent Neural Network models for time-series data, resulting in a 7% accuracy boost ensuring optimal operation in constrained wearable device environments. Show less

• 

  Drevol

  Oct 2024 - now

  Software Engineer Intern

  • Developed and optimized automation solutions using C#, .NET, and SQL for core business processes, achievinga 20% improvement in task efficiency through collaboration with cross-functional, multi-shore teams• Enhanced system reliability by implementing advanced analytical tools for pattern recognition and anomalydetection, contributing to a 30% reduction in operational bottlenecks and providing actionable insights tostreamline workflows• Researched and deployed new automation and ML-driven tools, documenting progress and achieving a 15%improvement in project tracking accuracy on Azure DevOps Show less