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\begin{document}

\begin{center}
    \textbf{\Huge \scshape Lu\'is  Rosa} \\ \vspace{5pt}
    \small +351 935 601 172 $|$ \href{mailto:luis.rosa17@hotmail.com}{\underline{luis.rosa17@hotmail.com}} $|$ 
    \href{https://linkedin.com/in/luisAPR1}{\underline{linkedin.com/in/luisapr1}} $|$
    \href{https://github.com/LuisAPR1}{\underline{github.com/LuisAPR1}} \\
    \small Agualva-Cac\'em, Lisbon, Portugal
\end{center}

\section{Education}
  \resumeSubHeadingListStart
    \resumeSubheading
      {Instituto Superior T\'ecnico}{Lisbon, Portugal}
      {Master's in Computer Science and Engineering}{Sep. 2025 -- Present}
    \resumeSubheading
      {University of Algarve}{Faro, Portugal}
      {Bachelor's in Computer Engineering (Final Grade: 15/20)}{Sep. 2022 -- Jun. 2025}
      \resumeSubHeadingListEnd

\section{Professional Experience}
  \resumeSubHeadingListStart

    \resumeSubheading
      {Software and Web Developer (Trainee)}{Jul. 2022 -- Aug. 2022}
      {DigitSigma}{Loul\'e, Portugal}
      \resumeItemListStart
        \resumeItem{Development of Web applications and Windows Forms (.NET).}
        \resumeItem{Database management and implementation of full-stack features.}
        \resumeItem{Technologies used: C\#, PHP, JavaScript, HTML, Bootstrap, Axios, and Ajax.}
      \resumeItemListEnd

  \resumeSubHeadingListEnd

\section{Projects}
    \resumeSubHeadingListStart
    
      \resumeProjectHeading
          {\textbf{Permissioned Blockchain \& BFT Consensus} $|$ \emph{Java, Hyperledger Besu, Solidity, UDP}}{}
          \resumeItemListStart
            \resumeItem{End-to-end development of DepChain, a highly dependable permissioned blockchain system, implementing both the consensus layer and a transaction processing engine to ensure Byzantine Fault Tolerance (BFT).}
            \resumeItem{Systematic implementation of the Basic HotStuff consensus algorithm over unreliable networks (UDP), building network abstractions such as authenticated perfect links and failure detectors to handle crash and malicious faults.}
            \resumeItem{Integration of EVM (Hyperledger Besu) for executing Solidity smart contracts, featuring a custom gas-fee mechanism and an ERC-20 token implementation  redesigned to prevent Approval Frontrunning attacks.}
          \resumeItemListEnd

      \resumeProjectHeading
          {\textbf{Classification \& Time Series Forecasting} $|$ \emph{Python, Scikit-learn, ARIMA, LSTM}}{}
          \resumeItemListStart
            \resumeItem{End-to-end Data Science pipeline applied to two real-world problems: predicting road accident severity and detecting flight cancellations, supporting decision-making in safety and logistics.}
            \resumeItem{Systematic implementation and comparison of multiple classification models (Na\"ive Bayes, KNN, Decision Trees, Random Forest, Gradient Boosting, MLP) with a focus on imbalanced class scenarios.}
            \resumeItem{Traffic volume forecasting on high-frequency time series, exploring statistical models (ARIMA) and deep learning (LSTM) to support transportation infrastructure planning.}
          \resumeItemListEnd
          
      \resumeProjectHeading
          {\textbf{UK Real Estate Data Warehouse \& Analytics} $|$ \emph{SQL, Pentaho (ETL/OLAP), MySQL, MDX}}{}
          \resumeItemListStart
            \resumeItem{Development of a complete Business Intelligence solution for the analysis of millions of UK real estate transaction records (Price Paid Data).}
            \resumeItem{Data Warehouse design (Star Schema) and implementation of complex ETL pipelines with Pentaho Data Integration for temporal and geographical data transformation.}
            \resumeItem{Creation of OLAP cubes and strategic reports (Saiku/Report Designer) to monitor KPIs such as year-over-year growth and sales by district, enabling data-driven decision-making.}
          \resumeItemListEnd
          
      \resumeProjectHeading
          {\textbf{MNIST Neural Network} $|$ \emph{Python, Multi-layer Neural Network, NumPy}}{}
          \resumeItemListStart
            \resumeItem{Implementation of a Multi-layer Neural Network (MLP) for handwritten digit classification (MNIST).}
            \resumeItem{Development and application of the Backpropagation algorithm for model training and weight adjustment.}
            \resumeItem{Use of cross-validation for optimisation and evaluation of pattern recognition accuracy.}
          \resumeItemListEnd
          
      \resumeProjectHeading
          {\textbf{Distributed Key-Value Store} $|$ \emph{FastAPI, Redis, RabbitMQ, CockroachDB}}{}
          \resumeItemListStart
            \resumeItem{Implementation of a distributed storage solution capable of managing key-value pairs across multiple nodes.}
            \resumeItem{Resilient architecture featuring an API layer, caching, message queues, and a distributed database.}
            \resumeItem{Implementation of monitoring, autoscaling, and health checks to ensure consistency and fault tolerance.}
          \resumeItemListEnd
          
    \resumeSubHeadingListEnd

\section{Technical Skills}
 \begin{itemize}[leftmargin=0.15in, label={}]
    \small{\item{
     \textbf{Languages}{: C\#, Java, Python, JavaScript, PHP, SQL, HTML/CSS, C/C++} \\
     \textbf{Frameworks/Libraries}{: React, Node.js, Express, FastAPI, .NET, Scikit-learn, Material-UI, Bootstrap} \\
     \textbf{Data \& Analytics}{: MySQL, Pentaho (PDI/Report Designer), OLAP, MDX, ARIMA, LSTM, Pandas, NumPy, Redis, RabbitMQ, CockroachDB} \\
     \textbf{Infrastructure \& Tools}{: Git, Docker, Arduino} \\
     \textbf{Spoken Languages}{: Portuguese (Native/C2), English (B2)}
    }}
 \end{itemize}

\end{document}
