YU WANG

YU WANG

Research Assistant

Followers of YU WANG329 followers
location of YU WANGPrinceton, New Jersey, United States

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  • Timeline

  • About me

    Software Engineer @ Outlier

  • Education

    • Rutgers University–New Brunswick

      2022 - 2024
      Master's degree Data science
  • Experience

    • New Jersey Institute of Technology

      Nov 2020 - Nov 2021
      Research Assistant

      · Collaborated with a team of researchers to troubleshoot and optimize Matlab code, leading to a 20% reduction in processing time.· Utilized SQL to merge and clean large datasets, reducing data processing time by 60%· Utilized R programming to analyze and visualize large datasets, resulting in a 30% improvement in data interpretation efficiency.· Generated monthly reports analyzing database usage and performance metrics, leading to informed decision-making and improved database optimization strategies. Show less

    • DGTAL ADDA

      Jan 2024 - Mar 2024
      Software Engineer

      · Increased frontend and backend system interaction efficiency by 8% through developing RESTful APIs using Django's REST framework.· Developed a data management system using Python, Django for backend, and React for frontend, enhancing efficiency and user experience.· Developed and deployed advanced deep learning models using TensorFlow, Keras, and PyTorch frameworks, resulting in a 5% increase in model accuracy.· Ensured secure access to the application and user data by leveraging Django's authentication system and AWS Identity Show less

    • Radical AI

      Mar 2024 - Nov 2024
      Software Engineer

      As a Software Developer at RadicalX, I am leveraging technologies such as OpenAI, Firebase, Node.js and React to develop ReX, an AI Coach who serves as a steadfast career companion for learners, offering personalized coaching, mentorship, and support throughout the various phases of their career lifecycle

    • Outlier

      Nov 2024 - now
      Software Engineer for AI training

      · Reviewed and optimized over 100 codebases to ensure adherence to industry best practices, reducing bugs by 25% and improving maintainability.· Designed and deployed AI models, processing datasets of 1M+ records, and achieved a 20% improvement in predictive accuracy through advanced preprocessing and fine-tuning techniques.· Built scalable training pipelines, reducing model training time by 30% and enabling real-time performance monitoring; applied iterative enhancements that boosted system reliability by 15%. Show less

  • Licenses & Certifications