info.json

{
  "name": "Sam Zhang",
  "contacts": [
    { "text": "+1 (438) 630-2638" },
    {
      "text": "sam.zijing.zhang@gmail.com",
      "link": "mailto:sam.zijing.zhang@gmail.com"
    },
    {
      "text": "linkedin.com/in/zhang-sam",
      "link": "https://linkedin.com/in/zhang-sam/"
    },
    {
      "text": "github.com/SamZhang02",
      "link": "https://github.com/SamZhang02/"
    },
    {
      "text": "cs.mcgill.ca/~szhang139",
      "link": "https://cs.mcgill.ca/~szhang139/"
    }
  ],
  "education": [
    {
      "institution": "McGill University",
      "link": "https://mcgill.ca/",
      "degree": "B.A., Joint Computer Science and Statistics",
      "location": "Montreal, Canada",
      "date": "Aug. 2022 - May 2026 (Expected)"
    },
    {
      "institution": "National University of Singapore",
      "link": "https://nus.edu.sg/",
      "degree": "Exchange Student",
      "location": "Singapore",
      "date": "Aug. 2024 - Dec. 2024"
    }
  ],
  "experience": [
    {
      "title": "Software Developer Intern",
      "company": "Dayforce",
      "link": "https://www.dayforce.com/",
      "technologies": ["TypeScript", "React", "C#", ".NET", "SQL"],
      "date": "Sept. 2023 - Apr. 2024",
      "bulletpoints": [
        "Contributed to the new Position Management module of the Dayforce application as a full-stack web developer.",
        "Implemented a new frontend UI using internal component libraries with \\textbf{TypeScript, React}, enhancing user experience and accessibility.",
        "Led the refactor of the frontend state management framework based on \\textbf{Redux}, \\textbf{reducing prop drilling and unnecessary client-side rendering}, resulting in improved developer efficiency and application performance.",
        "Resolved bugs in the backend microservice built with \\textbf{C\\# and .NET}, focusing on data accuracy and integrity, which improved data reliability for end users.",
        "Designed and implemented unit tests and integration tests for new features using \\textbf{Cypress} and \\textbf{Specflow}, ensuring a code coverage of \\textbf{85\\%+}, thereby increasing application reliability and code robustness."
      ]
    },
    {
      "title": "Machine Learning Engineer Intern",
      "company": "Meituan",
      "link": "https://meituan.com/",
      "technologies": ["Hadoop", "TensorFlow", "Python", "Scala", "SQL"],
      "date": "May 2023 - Aug. 2023",
      "bulletpoints": [
        "Engaged in \\textbf{recommendation algorithms research and development} for a lifestyle and consumer reviews application, focusing on optimizing the advertisement recommender system.",
        "Led \\textbf{two comprehensive machine learning projects from data engineering to model evaluation}, ensuring adherence to strict project timelines and delivering high-quality results.",
        "Engineered and managed over \\textbf{150TB of data using HiveQL, Spark, and MapReduce}, handling complex data pipelines and ensuring efficient processing and storage of massive datasets.",
        "Achieved \\textbf{significant improvements in the Click-Through-Rate (CTR) model's performance} by integrating new image and natural language features using TensorFlow, enhancing the model's understanding of ad and user context."
      ]
    }
  ],
  "projects": [
    {
      "name": "mcgill.courses",
      "link": "https://mcgill.courses/",
      "technologies": ["TypeScript", "React", "Rust", "MongoDB"],
      "bulletpoints": [
        "Co-created and maintaining an open-source platform built in \\textbf{TypeScript, React and Rust} for McGill University students to efficiently search and review courses, solving the problem of fragmented academic ressources for students and currently serving \\textbf{thousands of active users}.",
        "Created and maintained a rigourous automated testing pipeline using \\textbf{GitHub Actions}."
      ]
    },
    {
      "name": "Llmbda",
      "link": "https://github.com/SamZhang02/llmbda",
      "technologies": ["PyTorch", "Python"],
      "bulletpoints": [
        "Fine-tuned and prompt engineered Meta's open-source \\textbf{Large Language Model (LLM) Llama 2} to investigate LLM's ability to understand logical semantics in semiformal natural language, with independently developed metrics and evaluation pipeline built in \\textbf{Python}."
      ]
    },
    {
      "name": "Protect your Home",
      "link": "https://github.com/orgs/CS3237-Smart-Lock/repositories",
      "technologies": ["C++", "Arduino, Python, TensorFlow, TypeScript"],
      "bulletpoints": [
        "Developed a two-factor authentication smart lock prototype by programming three independent ESP32 microcontrollers and their sensors in \\textbf{Arduino C++}, designing and implementing a cloud backend for real-time deep learning inference in \\textbf{Python}, and building a user interface for adding/removing users and viewing log-in data in \\textbf{TypeScript React}."
      ]
    },
    {
      "name": "Resume Generator",
      "link": "https://github.com/SamZhang02/resume-generator",
      "technologies": ["Python"],
      "bulletpoints": [
        "Developed a command-line tool in Python enabling job seekers to efficiently tailor their resumes for specific job positions by dynamically generating tailored content from a centralized experience repository."
      ]
    }
  ],
  "technical_skills": {
    "Languages": [
      "Python",
      "TypeScript",
      "JavaScript",
      "Java",
      "Scala",
      "C",
      "C++",
      "C\\#",
      "Rust",
      "Go",
      "SQL"
    ],
    "Databases": ["SQLite", "HiveQL", "MySQL", "MongoDB"],
    "Frameworks \\& Libraries": [
      "React",
      "TailwindCSS",
      "TensorFlow",
      "PyTorch",
      ".NET",
      "Flask",
      "FastAPI"
    ],
    "Tools": [
      "Bash",
      "Linux",
      "Git",
      "GitHub",
      "Azure DevOps",
      "Docker",
      "Spark",
      "Hadoop",
      "HDFS"
    ]
  }
}