55 lines
3.8 KiB
TeX
55 lines
3.8 KiB
TeX
\datedsubsection{Ongoing}
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{Personal Homelab}
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{%
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Adapted an old PC into a \textbf{Linux Server} for 40+ applications. Serves as a valuable platform for refining skills, learning the latest technologies, while also hosting other personal projects.
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%
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\begin{itemize}
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\item \textbf{Arch Linux} as the base OS with \textbf{MergerFS} and \textbf{SnapRAID} as a storage and backup solution.
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\item \textbf{Docker}, \textbf{Docker Compose}, and \textbf{Portainer} as a container engine and management system.
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\item \textbf{Cloudflare Argo Tunnel}, \textbf{Nginx}, and \textbf{Let's Encrypt} for hosting, proxying, and SSL certificate automation.
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\item \textbf{Grafana}, \textbf{InfluxDB}, and \textbf{Telegraf} for constant system monitoring, stats visualization, and email alerts.
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\item \textbf{DevOps Stack} including a self-hosted \textbf{GitLab} instance and \textbf{VSCode server}.
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\item Public and private \textbf{Wireguard} instances and a \textbf{Tor} relay for remote management and privacy.
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\item Full-stack \textbf{media management server} including indexing, file downloading, metadata editing, and a personal streaming service.
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\item Much more, including a \textbf{blog}, a \textbf{private cloud} service for family/friends, and a URL shortener.
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\end{itemize}
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}
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\datedsubsection{Ongoing}
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{Qrust}
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{%
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An \textbf{algorithmic trading library} written in \textbf{Rust}, leveraging cutting-edge technologies for financial analysis and trading. Short for ``Quantitative Rust''.
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\begin{itemize}
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\item Uses a compartmentalized, \textbf{microservice}-like architecture, enabling flexible and scalable development of components in a robust and isolated manner.
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\item Integrates with the Alpaca \textbf{REST API} and \textbf{WebSockets} for real-time and historical market data acquisition.
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\item Employs \textbf{ClickHouse} for efficient, fully-automated, high-speed storage and querying of trading data.
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\item Conducts \textbf{sentiment analysis} on financial headlines using a custom model based on \textbf{FINBERT}, to gauge market sentiment and inform trading decisions.
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\end{itemize}
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}
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\datedsubsection{Sep 2022 - Apr 2023}
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{Trailblazer}
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{%
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Third Year University Project. Collaborated with a research group from Lancaster University to develop an \textbf{OS performance evaluation platform}. Built using Go and Python. A paper was later submitted to the International Conference on Architectural Support for Programming Languages and Operating Systems \textbf{(ASPLOS) 2024}.
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%
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\begin{itemize}
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\item Designed experiments to benchmark performance of network-based applications such as \textbf{Apache} and \textbf{Caddy}.
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\item Implemented multiple-architecture support using the \textbf{QEMU} virtual machine emulator, focusing on \textbf{x86-64} and \textbf{RISC-V}.
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\item Conducted testing and analysis to derive a memory-optimized \textbf{Linux} kernel configuration.
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\item Performed maintenance and bug fixes on the \textbf{Go} codebase and reduced experiment runtime using \textbf{RAM-based filesystems}.
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\end{itemize}
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}
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\datedsubsection{Sep 2020 - Jun 2021}
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{EazyShop}
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{%
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First Year University Project. Worked in a 6-person team to implement a \textbf{full-stack shopping list application}. Built using Python, Flask, HTML, Bootstrap, and MySQL.
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\begin{itemize}
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\item Configured and hosted a shared \textbf{MySQL} database using \textbf{Docker} for portability.
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\item Implemented \textbf{web scrapers} using \textbf{Python} for the 6 largest UK grocery store chains. Used to extract, parse, and import stock, pricing, and descriptions from all available products.
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\item Integrated the \textbf{MySQL} back-end with the \textbf{Flask} front-end and deployed the app using \textbf{Docker Compose}.
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\end{itemize}
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}
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