refactor(ta): update CV style from main branch

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Murtadha 2025-09-15 11:57:24 -04:00
parent b768c66145
commit c2a6ac655e
2 changed files with 89 additions and 55 deletions

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\begin{document}
%----------HEADING----------
\begin{tabular*}{\textwidth}{ @{\extracolsep{\fill}}l @{\hspace{-1ex}}l @{\hspace{-1ex}}l}
\textbf{\href{http://m.nisyif.com/}{\huge\color{blue}Murtadha Nisyif}} & \faIcon{map-marker-alt} Ontario, Canada & \faIcon{link} \href{https://m.nisyif.com/}{m.nisyif.com} \\
\emph{\Large } & \faIcon{at} \href{mailto:mnisyif@gmail.com}{mnisyif@gmail.com} & \faIcon{linkedin} \href{https://www.linkedin.com/in/mnisyif/}{linkedin.com/in/mnisyif}\\
& \faIcon{phone-square-alt} +1 (519) 502-8463 & \faIcon{github} \href{https://www.github.com/mnisyif}{github.com/mnisyif}
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\textbf{\href{http://m.nisyif.com/}{\Huge\color{blue}MURTADHA NISYIF}} \vspace{2pt}\\
\href{mailto:mnisyif@gmail.com}{\faIcon{at} mnisyif@gmail.com} $|$
\faIcon{phone-square-alt} +1 (519) 502-8463 $|$
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\href{https://www.linkedin.com/in/mnisyif}{\faIcon{linkedin} linkedin.com/ln/mnisyif} $|$
\href{https://github.com/mnisyif}{\faIcon{github} github.com/mnisyif}\vspace{12pt} \\
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\vspace{-20pt}
%----------Experience----------
\section{\color{blue}Relevant Work Experience}
\section{\color{blue}WORK EXPERIENCE}
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\resumeSubheading
{Teaching Assistant - ENGG*3640: Microcomputer Interfacing}{Sep 2024 -- Dec 2024}
@ -128,62 +146,78 @@
\resumeItem {Addressed student inquiries related to both lectures and lab work, reinforcing theoretical concepts through practical applications}
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{ML Engineer - Researcher}{Jan 2024 -- Present}
{University of Guelph}{Guelph, Ontario}
\resumeSubheading
{Software Engineer—Machine Learning}{Jan 2024 Aug 2025}
{University of Guelph}{ Guelph, Ontario}
\resumeItemListStart
\resumeItem {Performed latency data acquisition and thorough dataset diagnosis across diverse hardware setups, applying advanced analysis and feature engineering to identify key correlations-enabling the model to determine optimal transformer configurations for varying networks conditions}
\resumeItem {Designed, implemented, and trained an adaptive model extension to the existing semantic communication transformer, improving real-time responses to network bandwidth fluctuations while maintaining at least 96\% model accuracy}
\resumeItem {Deployed Swin Transformer-based models in edge-cloud systems to offload processing from the core network, achieving higher throughput and reducing end-to-end communication latency by up to 29\%, alongside a 30x reduction in network bandwidth utilization}
\resumeItem {Deployed existing PyTorch-based implementations onto Kira SoCs using Vitis AI™, to leverage SoC's hardware acceleration}
\resumeItem {Spearheaded the integration of a Swin-Transformerbased compressor into a sophisticated edge-to-cloud pipeline, achieving a 30× reduction in bandwidth usage and a 29\% decrease in latency under variable network conditions}
\resumeItem {Architectured and trained an adaptive model extension to the existing semantic communication transformer,improving real-time responses to network bandwidth fluctuations while maintaining at least 96\% model accuracy}
\resumeItem {Quantized PyTorch models via Vitis AI to ONNX for deployment on Xilinx Kria SoCs, leveraging hardware acceleration for 3× faster inference}
\resumeItem {Published a first-author paper in IEEE conference proceedings, detailing the novel integration of semantic communication with edge computing for real-time applications}
\resumeItem {Extended semantic communication models with predictive adaptation mechanisms for network anomalies, sustaining 96\% task accuracy under fluctuating conditions}
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{Software Developer}{Oct 2022 -- Oct 2023}
{University of Guelph - Robotics Institute}{Guelph, Ontario}
{Software Developer}{Oct 2022 Oct 2023}
{University of Guelph Robotics Institute}{ Guelph, Ontario}
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\resumeItem {Implemented a server-client backend system for an Assistive Robotic Feeding System in ROS2, utilizing Python and C++ packages to integrate robotic components with system software}
\resumeItem {Designed and deployed a wheelchair-friendly smart door system with geo-fencing and automated operations, leveraging ESP32 microprocessors, PIR sensors, and smartphone control via a React Native app, showcasing systems integration}
\resumeItem {Enhanced and maintained the smart door system's full-stack codebase, including a Node.js backend, React Native app, and Vue Dashboard, incorporating advanced features like voice recognition and passive BLE scanning and real-time user analytics for seamless user experience}
\resumeItem {Deployed scalable, reliable full-stack app on AWS EC2 instances and S3 storage using Terraform for Infrastructure as Code (IaC), and Jenkins for CI/CD cloud infrastructure and automated deployment}
\resumeItem {Architected and containerized a multi-technology stack combining ROS2, Node.js, and Vue to enable seamless real-time control across distributed robotic systems}
\resumeItem {Implemented automated AWS infrastructure provisioning with Terraform and integrated CI/CD pipelines via GitLab and Jenkins, reducing manual deployment steps by 80\%}
\resumeItem {Created a secure certificate management workflow that streamlined Let's Encrypt renewals and configured a Nginx reverse proxy to enforce HTTPS and granular CORS policies}
\resumeItem {Led the design and implementation of an accessible smart door system using ESP32, PIR sensors, and React Native, achieving over 95\% reliability in extensive field tests}
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% \vspace{-8pt}
%-----------SKILLS-----------
\section{\color{blue}Skills}
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\textbf{\color{black}Languages:} & C/C++, Python, Rust, Java, SQL, Bash, JavaScript, HTML, CSS, CMake \\
\textbf{\color{black}Frameworks:} & PyTorch, TensorFlow, Node.js, React, Express.js, ROS \\
\textbf{\color{black}Cloud and DevOps:} & AWS, Docker, Kubernetes, Terraform, Jenkins, PostgreSQL, MongoDB, SQLite \\
\textbf{\color{black}Tools and Protocols:} & Git, Postman, Flask, Swagger, Jira, CMake, HTTP, TCP, Ladder Logic (PLC) \\
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%-----------EDUCATION-----------
\section{\color{blue}EDUCATION}
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\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{Dec 2025}
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{Apr 2023}
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% \vspace{-8pt}
%-----------SKILLS-----------
\section{\color{blue}CERTIFICATIONS, SKILLS, TECHNOLOGIES, INTERESTS}
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\textbf{Certifications: } & AWS Solutions Architect\\
\textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\
\textbf{Technologies: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash; Flask; FastAPI; Swagger; Node.js; React; PyTorch; MongoDB; PostgreSQL; SQLite; Docker; Kubernetes; Git; Jenkins; Terraform; AWS \\
% \textbf{Languages: } & English (Fluent); Arabic (Fluent)
\end{tabularx}
\vspace{-7pt}
%-----------PROJECTS-----------
\section{\color{blue}Projects}
\section{\color{blue}PROJECTS}
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\resumeSubItem{\textbf{\color{black}Full-stack application}}
{Built and Dockerized a full-stack portfolio using React and Java (microservices architecture), hosting it on a home server via a Jenkins CI/CD pipeline and Minio S3 bucket}
\resumeSubItem{\textbf{\color{black}DevOps Homelab}}
{Setup dockerized applications, virtual machines, and Kubernetes clusters sing Terraform scripts. Managed personal Jenkins CI/CD pipelines, and implemented Ceph for distributed storage}
\resumeProjectHeading {\textbf{\color{black}Personal Portfolio Website} $|$ \color{blue} \emph{React, Rust, Async, Jenkins, Docker}}{}
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\resumeItem{Built a portfolio website featuring a React frontend coupled with a resilient Rust backend}
\resumeItem{Integrated comprehensive Jenkins CI/CD pipelines and Docker-based deployment, slashing manual release efforts by 70\% and ensuring high availability}
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\resumeSubItem{\textbf{\color{black}RL Dynamic Noise Cancelling:}}
{Implemented real-time Automatic Noise Filtering using Reinforcement Learning and Dynamic Sparse Training in PyTorch}
\resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{}
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\resumeItem{Orchestrate a comprehensive home lab environment managing 15+ Docker containers for media, web, and gaming services, configured auto-renewal SSL/TLS certification with Lets Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics}
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\vspace{-8pt}
\resumeProjectHeading{\textbf{\color{black}HAM10K Skin Cancer Classifier} $|$ \color{blue} \emph{Python, PyTorch, SciPy, Pandas}}{}
\resumeItemListStart
\resumeItem{Engineered a comprehensive deep learning pipeline integrating a PCA-enhanced MLP, a custom-designed DCNN, and the RegNetY-320 architecture}
\resumeItem{Applied systematic class rebalancing and extensive data augmentation to achieve 96.9\% accuracy, an optimal F1-score, and a flawless 1.00 AUC}
\resumeItemListEnd
%-----------EDUCATION-----------
\section{\color{blue}Education}
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\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{}
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Comp. - Computer Science}}{}
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{}
\resumeProjectHeading{\textbf{\color{black}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{}
\resumeItemListStart
\resumeItem{Developed a scalable Flask-RESTful API paired with an interactive HTML/JS frontend while leveraging the UCI dataset and implemented real-time feature scaling with hyperparameter tuning to deliver a 95\% prediction accuracy, supporting timely clinical decision-making}
\resumeItemListEnd
\resumeProjectHeading{\textbf{\color{black} Real-Time Noise Cancellation with RL} $|$ \color{blue} \emph{Python, PyTorch, Gymnasium, SciPy, librosa}}{}
\resumeItemListStart
\resumeItem{Created a bespoke OpenAI Gym environment incorporating FFT-based audio processing and trained a PPO agent to perform adaptive noise cancellation in real time, achieving processing speeds exceeding 5,200 FPS for high-fidelity audio performance}
\resumeItemListEnd
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% \vspace{-8pt}
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