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jobs/softw
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\textbf{\color{black} #1} & \textbf{ #2} \\
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\textbf{\color{black} #1} & \textbf{ #2}\\
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\textit{#3} & \textit{ #4} \\
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\begin{tabular*}{\textwidth}{@{\hspace{-1ex}}l}
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\begin{tabular*}{\textwidth}{@{\hspace{-1ex}}l}
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\textbf{\href{http://m.nisyif.com/}{\Huge\color{blue}MURTADHA NISYIF}} \vspace{2pt}\\
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\textbf{\href{http://m.nisyif.com/}{\Huge\color{blue}MURTADHA NISYIF}} \vspace{2pt}\\
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\href{mailto:mnisyif@gmail.com}{\faIcon{at} mnisyif@gmail.com} $|$
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\href{mailto:mnisyif@gmail.com}{\faIcon{at} mnisyif@gmail.com} $|$
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\faIcon{phone-square-alt} +964 775 608 4424 $|$
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\faIcon{phone-square-alt} +1 (519) 502-8463 $|$
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\faIcon{map-marker-alt} Karbala, Iraq $|$
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\faIcon{map-marker-alt} Ontario, Canada $|$
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\href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$
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\href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$
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\href{https://www.linkedin.com/in/mnisyif}{\faIcon{linkedin} linkedin.com/ln/mnisyif} $|$
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\href{https://www.linkedin.com/in/mnisyif}{\faIcon{linkedin} linkedin.com/ln/mnisyif} $|$
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\href{https://github.com/mnisyif}{\faIcon{github} github.com/mnisyif}\vspace{12pt} \\
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\href{https://github.com/mnisyif}{\faIcon{github} github.com/mnisyif}\vspace{12pt} \\
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\vspace{-20pt}
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\vspace{-20pt}
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%-----------SUMMARY----------
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\section{\color{blue}SUMMARY}
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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
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\vspace{-7pt}
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%-----------EDUCATION-----------
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%-----------EDUCATION-----------
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\section{\color{blue}EDUCATION}
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\section{\color{blue}EDUCATION}
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\resumeSubHeadingListStart
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\resumeSubHeadingListStart
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\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{Dec 2025}
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\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{Aug 2025}
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\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{Apr 2023}
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\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{Apr 2023}
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\resumeSubHeadingListEnd
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\resumeSubHeadingListEnd
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% \vspace{-8pt}
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% \vspace{-8pt}
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%-----------SKILLS-----------
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%-----------SKILLS-----------
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\section{\color{blue}SKILLS \& TECHSTACKS}
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\section{\color{blue}CERTIFICATIONS, SKILLS, TECHNOLOGIES, INTERESTS}
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\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
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\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
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% \textbf{Certifications: } & AWS Solutions Architect\\
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\textbf{Certifications: } & AWS Solutions Architect\\
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\textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\
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\textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\
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\textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash \\
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\textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash\\
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\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 \\
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\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\\
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\end{tabularx}
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\textbf{Languages: } & English (Fluent); Arabic (Fluent) \end{tabularx}
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\vspace{-10pt}
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\vspace{-7pt}
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%----------Experience----------
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%----------Experience----------
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\section{\color{blue}WORK EXPERIENCE}
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\section{\color{blue}WORK EXPERIENCE}
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\resumeSubHeadingListStart
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\resumeSubHeadingListStart
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\resumeSubheading
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\resumeSubheading
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{Researcher - Machine Learning \& Semantic Communications}{Jan 2024 – Dec 2025}
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{Software Engineer—Machine Learning}{Jan 2024 – Aug 2025}
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{University of Guelph}{ Guelph, Ontario}
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{University of Guelph}{}
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\resumeItemListStart
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\resumeItemListStart
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\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}
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\resumeItem {Developed semantic communication pipelines using Swin Transformer, achieving a 30x reduction in bandwidth utilization and 29\% lower latency while preserving at least 96\% data accuracy post-decoding under variable network conditions}
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\resumeItem {Extended models with adaptive deterministic mechanisms to handle bandwidth fluctuations and anomalies, ensuring stable real-time performance}
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\resumeItem {Extended the functionality of Swin Transformer to adapt to network conditions and handle anomalies, achieving 80\% lower latency by augmenting it with deterministic log-based algorithms}
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\resumeItem {Quantized encoder models to INT8 during edge–cloud simulations to emulate smartphone hardware constraints (6-core CPU, limited RAM), enabling realistic performance benchmarking}
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\resumeItem {Explored model quantization to deploy and emulate edge device-server environments, achieving realistic emulation and delivering high accuracy simulation reuslts}
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\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}
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\resumeItem {Published as first author findings in IEEE CCECE '24 and MECOM '25, detailing the novel integration of semantic communications in edge-cloud computing systems}
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\resumeItemListEnd
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\resumeItemListEnd
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\resumeSubheading
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\resumeSubheading
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{Software Developer}{Oct 2022 – Oct 2023}
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{Software Developer}{Oct 2022 – Oct 2023}
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{University of Guelph - Robotics Institute}{ Guelph, Ontario}
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{University of Guelph – Robotics Institute}{}
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\resumeItemListStart
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\resumeItemListStart
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\resumeItem {Architected and containerized a multi-technology stack combining ROS2, Node.js, and Vue to enable seamless real-time control across distributed robotic systems}
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\resumeItem {Architected and containerized a multi-technology stack combining ROS2, Node.js, and Vue to enable seamless real-time control across distributed robotic systems}
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\resumeItem {Implemented automated AWS infrastructure provisioning with Terraform and integrated CI/CD pipelines via GitLab and Jenkins, reducing manual deployment steps by 80\%}
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\resumeItem {Implemented automated AWS infrastructure provisioning with Terraform and integrated CI/CD pipelines via GitLab and Jenkins, reducing manual deployment steps by 80\%}
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\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}
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\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}
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\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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\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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\resumeItemListEnd
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\resumeItemListEnd
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\resumeSubheading
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\resumeSubheading
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{Information Technology Analyst}{Jul 2020 – Dec 2020}
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{Information Technology Analyst}{Jul 2020 – Dec 2020}
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{Kitchener Downtown Community Health Center - SRHC}{ Kitchener, Ontario}
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{Kitchener Downtown Community Health Center — SRHC}{}
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\resumeItemListStart
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\resumeItemListStart
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\resumeItem {Deployed and tuned a centralized Samba file server, increasing file distribution efficiency by 40\% across more than 20 staff and multiple departments}
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\resumeItem {Deployed and tuned a centralized Samba file server, increasing file distribution efficiency by 40\% across more than 20 staff and multiple departments}
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\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}
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\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}
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\resumeItemListEnd
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\resumeItem {Revamped the 3CX PBX system by re-architecting call routing and queue management, reducing patient on-hold times by 30\% and enhancing communication reliability}
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\resumeItem {Led a comprehensive hardware modernization initiative by replacing legacy switches, servers, and workstations, which reduced operating costs by 45\% while boosting network performance and security}
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\resumeItemListEnd
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\resumeSubHeadingListEnd
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% \vspace{-8pt}
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\resumeSubHeadingListEnd
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%-----------PROJECTS-----------
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%-----------PROJECTS-----------
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\section{\color{blue}PROJECTS}
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\section{\color{blue}PROJECTS}
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\resumeSubHeadingListStart
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\resumeSubHeadingListStart
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\resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{}
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\resumeProjectHeading {\textbf{\color{black}Personal Portfolio Website} $|$ \color{blue} \emph{React, Rust, Async, Jenkins, Docker}}{}
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\resumeItemListStart
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\resumeItemListStart
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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 Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics}
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\resumeItem{Built a portfolio website featuring a React frontend coupled with a resilient Rust backend}
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\resumeItemListEnd
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\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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\resumeItemListEnd
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% \resumeProjectHeading{\textbf{\color{black}HAM10K Skin Cancer Classifier} $|$ \color{blue} \emph{Python, PyTorch, SciPy, Pandas}}{}
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\resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{}
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% \resumeItemListStart
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\resumeItemListStart
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% \resumeItem{Engineered a comprehensive deep learning pipeline integrating a PCA-enhanced MLP, a custom-designed DCNN, and the RegNetY-320 architecture}
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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 Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics}
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% \resumeItem{Applied systematic class rebalancing and extensive data augmentation to achieve 96.9\% accuracy, an optimal F1-score, and a flawless 1.00 AUC}
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\resumeItemListEnd
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% \resumeItemListEnd
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\resumeProjectHeading{\textbf{\color{black}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{}
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\resumeProjectHeading{\textbf{\color{black}HAM10K Skin Cancer Classifier} $|$ \color{blue} \emph{Python, PyTorch, SciPy, Pandas}}{}
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\resumeItemListStart
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\resumeItemListStart
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\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}
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\resumeItem{Engineered a comprehensive deep learning pipeline integrating a PCA-enhanced MLP, a custom-designed DCNN, and the RegNetY-320 architecture}
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\resumeItemListEnd
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\resumeItem{Applied systematic class rebalancing and extensive data augmentation to achieve 96.9\% accuracy, an optimal F1-score, and a flawless 1.00 AUC}
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\resumeItemListEnd
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\resumeProjectHeading{\textbf{\color{black} Real-Time Noise Cancellation with RL} $|$ \color{blue} \emph{Python, PyTorch, Gymnasium, SciPy, librosa}}{}
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\resumeProjectHeading{\textbf{\color{black}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{}
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\resumeItemListStart
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\resumeItemListStart
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\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}
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\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}
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\resumeItemListEnd
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\resumeItemListEnd
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\resumeSubHeadingListEnd
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\vspace{-7pt}
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\section{\color{blue}PUBLICATIONS}
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\resumeSubHeadingListStart
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\resumeProjectHeading
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{\textbf{Network-Aware Adaptive Semantic Image Transmission in Edge-Cloud Communications}}{MECOM 2025}
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\resumeItemListStart
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\resumeItem{Proposed an adaptive JSCC framework that couples Swin-Transformers with real-time network telemetry to optimize image transmission over dynamic 5G/6G core networks (Accepted, IEEE MECOM25)}
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\resumeItemListEnd
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\resumeProjectHeading
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{\textbf{Boosting Edge-to-Cloud Data Transmission Efficiency with Semantic Transcoding}}{CCECE 2024}
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\resumeItemListStart
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\resumeItem{Utilized transformer-based edge-to-cloud models to achieve a $30\times$ bandwidth reduction and $30\%$ improvement in end-to-end latency for high-speed data systems (Published, IEEE Xplore)}
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\resumeItemListEnd
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\resumeSubHeadingListEnd
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\resumeProjectHeading{\textbf{\color{black} Real-Time Noise Cancellation with RL} $|$ \color{blue} \emph{Python, PyTorch, Gymnasium, SciPy, librosa}}{}
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\resumeItemListStart
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\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}
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\resumeItemListEnd
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\resumeSubHeadingListEnd
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% \vspace{-8pt}
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\end{document}
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\end{document}
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