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refactor: update summary to inclkude billinguality and publications

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%----------HEADING----------
\begin{tabular*}{\textwidth}{@{\hspace{-1ex}}l}
\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 $|$
\faIcon{map-marker-alt} Ontario, Canada $|$
\href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$
\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} \\
\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} +964 775 608 4424 $|$
\faIcon{map-marker-alt} Karbala, Iraq $|$
\href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$
\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} \\
\end{tabular*}
\vspace{-20pt}
%-----------SUMMARY----------
\section{\color{blue}SUMMARY}
Versatile computer engineer and researcher specialized in \textbf{Semantic Communications}.
Explored and implemented methods to optimize AI-driven communication by extracting and transmitting only \textbf{task-critical "meaningful features"} rather than raw pixel data.
This approach enables autonomous systems to maintain high intelligence and operational reliability over congested or weak network environments.
Versatile Computer Engineer and Researcher specialized in Semantic Communications and Edge Computing. First author of two IEEE conference papers focused on optimizing edge-cloud communication through task-driven feature extraction. \textbf{Bilingual in English and Arabic}, with expertise in developing high-efficiency AI pipelines for 5G/6G and Smart City infrastructure. Proven track record of reducing bandwidth demand by \textbf{30$\times$} while maintaining 96\% task accuracy in congested network environments.
\vspace{-7pt}
\vspace{-7pt}
%-----------EDUCATION-----------
\section{\color{blue}EDUCATION}
\resumeSubHeadingListStart
\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}
\resumeSubHeadingListEnd
\resumeSubHeadingListStart
\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}
\resumeSubHeadingListEnd
% \vspace{-8pt}
%-----------SKILLS-----------
\section{\color{blue}CERTIFICATIONS, SKILLS, TECHNOLOGIES, INTERESTS}
\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
\textbf{Certifications: } & AWS Solutions Architect\\
\textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\
\textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash\\
\textbf{Tech Stacks: } & FastAPI; PyTorch; React; Flask; SQLite; PostgresSQL; NumPy; SciPy; Scikit-learn; Matplotlib; MongoDB; Docker; Git; Jenkins; Terraform; AWS; Kubernetes; Express JS; Node.js; Swagger\\
\textbf{Languages: } & English (Fluent); Arabic (Fluent)
\end{tabularx}
\vspace{-7pt}
\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
% \textbf{Certifications: } & AWS Solutions Architect\\
\textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\
\textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash \\
\textbf{Tech Stacks: } & FastAPI; PyTorch; React; Flask; SQLite; PostgresSQL; NumPy; SciPy; Scikit-learn; Matplotlib; MongoDB; Docker; Git; Jenkins; Terraform; AWS; Kubernetes; Express JS; Node.js; Swagger \\
\end{tabularx}
\vspace{-7pt}
%----------Experience----------
\section{\color{blue}WORK EXPERIENCE}
\resumeSubHeadingListStart
\resumeSubheading
{Researcher - Machine Learning \& Semantic Communications}{Jan 2024 – Dec 2025}
{University of Guelph}{ Guelph, Ontario}
\resumeItemListStart
\resumeItem {Developed semantic communication pipelines using Swin Transformer models, achieving a 30× reduction in bandwidth usage and 29\% lower latency while preserving atleast 96\% task accuracy under variable network conditions}
\resumeItem {Extended models with adaptive deterministic mechanisms to handle bandwidth fluctuations and anomalies, ensuring stable real-time performance}
\resumeItem {Quantized encoder models to INT8 during edge–cloud simulations to emulate smartphone hardware constraints (6-core CPU, limited RAM), enabling realistic performance benchmarking}
\resumeItem {Published a first-author paper in IEEE conference proceedings, detailing the novel integration of semantic communication with edge computing for real-time, near real-time and task-offloading applications}
\resumeItemListEnd
\resumeSubHeadingListStart
\resumeSubheading
{Researcher - Machine Learning \& Semantic Communications}{Jan 2024 – Dec 2025}
{University of Guelph}{ Guelph, Ontario}
\resumeItemListStart
\resumeItem {Developed semantic communication pipelines using Swin Transformer models, achieving a 30× reduction in bandwidth usage and 29\% lower latency while preserving atleast 96\% task accuracy under variable network conditions}
\resumeItem {Extended models with adaptive deterministic mechanisms to handle bandwidth fluctuations and anomalies, ensuring stable real-time performance}
\resumeItem {Quantized encoder models to INT8 during edge–cloud simulations to emulate smartphone hardware constraints (6-core CPU, limited RAM), enabling realistic performance benchmarking}
\resumeItem {Published a first-author paper in IEEE conference proceedings, detailing the novel integration of semantic communication with edge computing for real-time, near real-time and task-offloading applications}
\resumeItemListEnd
\resumeSubheading
{Software Developer}{Oct 2022 – Oct 2023}
{University of Guelph – Robotics Institute}{ Guelph, Ontario}
\resumeItemListStart
\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}
\resumeItemListEnd
\resumeSubheading
{Software Developer}{Oct 2022 – Oct 2023}
{University of Guelph - Robotics Institute}{ Guelph, Ontario}
\resumeItemListStart
\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}
\resumeItemListEnd
\resumeSubheading
{Information Technology Analyst}{Jul 2020 – Dec 2020}
{Kitchener Downtown Community Health Center — SRHC}{ Kitchener, Ontario}
\resumeItemListStart
\resumeItem {Deployed and tuned a centralized Samba file server, increasing file distribution efficiency by 40\% across more than 20 staff and multiple departments}
\resumeItem {Configured and maintained a FortiGate firewall and VPN solution for 60 users, integrating Prometheus-based monitoring for real-time diagnostics and rapid issue resolution}
\resumeItemListEnd
\resumeSubheading
{Information Technology Analyst}{Jul 2020 – Dec 2020}
{Kitchener Downtown Community Health Center - SRHC}{ Kitchener, Ontario}
\resumeItemListStart
\resumeItem {Deployed and tuned a centralized Samba file server, increasing file distribution efficiency by 40\% across more than 20 staff and multiple departments}
\resumeItem {Configured and maintained a FortiGate firewall and VPN solution for 60 users, integrating Prometheus-based monitoring for real-time diagnostics and rapid issue resolution}
\resumeItemListEnd
\resumeSubHeadingListEnd
\resumeSubHeadingListEnd
%-----------PROJECTS-----------
\section{\color{blue}PROJECTS}
\resumeSubHeadingListStart
\resumeSubHeadingListStart
% \resumeProjectHeading {\textbf{\color{black}Personal Portfolio Website} $|$ \color{blue} \emph{React, Rust, Async, Jenkins, Docker}}{}
% \resumeItemListStart
% \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}
% \resumeItemListEnd
\resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{}
\resumeItemListStart
\resumeItem{Orchestrate a comprehensive home lab environment managing 15+ Docker containers for media, web, and gaming services, configured auto-renewal SSL/TLS certification with Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics}
\resumeItemListEnd
\resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{}
\resumeItemListStart
\resumeItem{Orchestrate a comprehensive home lab environment managing 15+ Docker containers for media, web, and gaming services, configured auto-renewal SSL/TLS certification with Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics}
\resumeItemListEnd
\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
\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
\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}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
\resumeSubHeadingListEnd
% \vspace{-8pt}
\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
\resumeSubHeadingListEnd
% \vspace{-8pt}
\end{document}