resume-cv

Unnamed repository; edit this file 'description' to name the repository.
Log | Files | Refs | README

commit b7168173c2224bc6027087cf95ae388ac24b41a6
parent a7c331a27060d86d1498c0f68ad88fd9fac65d55
Author: AndrewLockVI <andrew@laack.co>
Date:   Tue, 10 Jun 2025 13:24:45 -0500

migration

Diffstat:
Mresume.tex | 135++++++++++++++++++++++++++++++++++++++++++-------------------------------------
1 file changed, 71 insertions(+), 64 deletions(-)

diff --git a/resume.tex b/resume.tex @@ -184,83 +184,43 @@ \kern 0.25 cm% \AND% \kern 0.25 cm% - \mbox{\hrefWithoutArrow{https://github.com/andrewlaack}{\color{black}{\footnotesize\faGithub}\hspace*{0.13cm}andrewlaack}}% + \mbox{\hrefWithoutArrow{https://git.laack.co/}{\color{black}{\footnotesize\faGithub}\hspace*{0.13cm}andrewlaack}}% \end{header} \vspace{0.3 cm - 0.3 cm} + \section{Skills} - \section{Education} - - \begin{twocolentry}{ - - - \textit{Aug 2023 – May 2025}} - \textbf{University of Wisconsin-Superior} - - \textit{BS in Computer Science} - \end{twocolentry} - - \vspace{0.10 cm} - \begin{onecolentry} - \begin{highlights} - \item GPA: 3.96/4.00 - \item \textbf{Relevant Coursework:} Data Structures \& Algorithms, Theory of Computation, Computer Graphics, Individual Capstone Project (developed a novel ML algorithm), Assembly Language Programming - \end{highlights} - \end{onecolentry} - - - \begin{twocolentry}{ - - - \textit{Aug 2021 – Dec 2023}} - \textbf{University of Wisconsin-Superior} - - \textit{AS in Cybersecurity} - \end{twocolentry} - - \vspace{0.10 cm} \begin{onecolentry} - \begin{highlights} - \item GPA: 4.00/4.00 - \end{highlights} + \textbf{Programming Languages:} Python, SQL, R, Java, Kotlin, Dart, C\#, JavaScript, C++ \end{onecolentry} - - \section{Skills} + \vspace{0.2 cm} \begin{onecolentry} - \textbf{Programming Languages:} Python, SQL, Java, Kotlin, Dart, C\# + \textbf{Libraries/Frameworks:} Keras, TensorFlow, PyTorch, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn, React, Node.js \end{onecolentry} \vspace{0.2 cm} \begin{onecolentry} - \textbf{Libraries/Frameworks:} Keras, TensorFlow, PyTorch, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn + \textbf{Tools:} Tableau, Docker, Kubernetes, Git, Power BI, Jupyter Notebooks, LaTeX \end{onecolentry} \vspace{0.2 cm} \begin{onecolentry} - \textbf{Tools:} Git, Jupyter Notebooks + \textbf{Cloud Platforms:} AWS (Lambda, S3, EC2), GCP (Firebase, Vertex AI) \end{onecolentry} - %\vspace{0.2 cm} %\begin{onecolentry} %\textbf{Mathematics:} Statistics, Probability, Linear Algebra, Discrete Mathematics, Calculus %\end{onecolentry} - - - - \section{Experience} - - - \begin{twocolentry}{ - \textit{Madison WI} + \textit{Madison, WI} \textit{Oct 2023 - Present}} \textbf{Lead Software Developer} @@ -271,8 +231,9 @@ \vspace{0.10 cm} \begin{onecolentry} \begin{highlights} - \item Developed a logistic regression model to predict recidivism, utilizing imputation, data augmentation, and one-hot encoding, achieving 96\% accuracy and improving resource allocation for staff. - \item Created a custom Naïve Bayes classifier for user-submitted tickets using Scikit-Learn, achieving 93\% accuracy, and implemented a C\# REST API for predictions, reducing manual classification time. + \item Developed a logistic regression model to predict recidivism, utilizing imputation, data augmentation, and one-hot encoding, achieving 96\% accuracy and improving staff resource allocation. + \item Developed a Naïve Bayes classifier using Scikit-Learn to categorize user-submitted tickets with 93\% accuracy; containerized the model with Docker and deployed it via AWS Lambda, reducing manual classification time and improving operational efficiency. + \end{highlights} \end{onecolentry} @@ -293,6 +254,7 @@ \begin{highlights} \item Created a Python-based data integration script that automated synchronization between off-premises and on-premises databases, improving data consistency and reducing manual intervention. \item Utilized SQL to troubleshoot and resolve complex database issues, enhancing data integrity and system performance. + \item Developed an iOS application to streamline internal work order tracking, resulting in a reduction in manual processes and improved operational efficiency. % \item Developed an iOS application using OutSystems to streamline internal work order tracking, resulting in a reduction in manual processes and improved operational efficiency. \end{highlights} \end{onecolentry} @@ -300,6 +262,8 @@ \vspace{0.20 cm} \begin{twocolentry}{ + \textit{Los Angeles, CA} + \textit{May 2023 - Aug 2023}} \textbf{Mobile Application Developer (Contract)} @@ -311,39 +275,65 @@ \begin{highlights} \item Implemented an algorithm to predict future occupancy based on historical trends by location, enhancing administrative planning and resource allocation. \item Developed a cross-platform, responsive mobile application for iOS and Android using Flutter and Dart, enhancing user experience across devices. - %\item Designed a Firebase backend architecture to facilitate real-time access to occupancy metrics, enabling end users to make informed decisions based on live data. + \item Designed a Firebase backend architecture to facilitate real-time access to occupancy metrics, enabling end users to make informed decisions based on live data. \item Created a REST API for motion sensors to update room occupancy, streamlining data flow and improving accuracy in occupancy tracking. \end{highlights} \end{onecolentry} + \section{Education} + + \begin{twocolentry}{ + + + %\textit{Aug 2023 – May 2025}} + } + \textbf{University of Wisconsin-Superior} + \textit{BS in Computer Science} + \end{twocolentry} - -\section{Publications} + \vspace{0.10 cm} + \begin{onecolentry} + \begin{highlights} + \item GPA: 3.9/4.0 + \item \textbf{Relevant Coursework:} Data Structures \& Algorithms, Theory of Computation, Computer Graphics, Individual Capstone Project (developed a novel ML algorithm), Assembly Language Programming + \end{highlights} + \end{onecolentry} - \begin{samepage} - \begin{twocolentry}{ - May 2025 - } - \textbf{CART-ELC: Oblique Decision Tree Induction via Exhaustive Search}\\[4pt] - Laack, A. D. (2025). \href{https://doi.org/10.48550/arXiv.2505.05402}{doi:10.48550/arXiv.2505.05402.} (Under Review) + + \begin{twocolentry}{} + + + %\textit{Aug 2021 – Dec 2023}} + \textbf{Madison College} + + \textit{AS in Cybersecurity} \end{twocolentry} \vspace{0.10 cm} - \begin{onecolentry} + \begin{highlights} + \item GPA: 4.0/4.0 + \end{highlights} \end{onecolentry} - \end{samepage} -\section{Talks} + + + + + + + + + +\section{Publications} \begin{samepage} \begin{twocolentry}{ May 2025 } \textbf{CART-ELC: Oblique Decision Tree Induction via Exhaustive Search}\\[4pt] - \emph{Research presentation}, Department of Computer Science \& Mathematics, University of Wisconsin–Superior.\\[4pt] - Laack, A. D. (2025). \href{https://github.com/andrewlaack/cart-elc/blob/master/presentations/uws/presentation.pdf}{Capstone Presentation [Slides].} + Laack, A. D. (2025). \href{https://doi.org/10.48550/arXiv.2505.05402}{doi:10.48550/arXiv.2505.05402.} (Under Review) \end{twocolentry} \vspace{0.10 cm} @@ -352,6 +342,23 @@ \end{onecolentry} \end{samepage} +% \section{Talks} +% +% \begin{samepage} +% \begin{twocolentry}{ +% May 2025 +% } +% \textbf{CART-ELC: Oblique Decision Tree Induction via Exhaustive Search}\\[4pt] +% \emph{Research presentation}, Department of Computer Science \& Mathematics, University of Wisconsin–Superior.\\[4pt] +% Laack, A. D. (2025). \href{https://github.com/andrewlaack/cart-elc/blob/master/presentations/uws/presentation.pdf}{Capstone Presentation [Slides].} +% \end{twocolentry} +% +% \vspace{0.10 cm} +% +% \begin{onecolentry} +% \end{onecolentry} +% \end{samepage} +