diff --git a/resumes/Murtadha.pdf b/resumes/Murtadha.pdf index 87261fc..fef976e 100644 Binary files a/resumes/Murtadha.pdf and b/resumes/Murtadha.pdf differ diff --git a/resumes/Murtadha.tex b/resumes/Murtadha.tex index 5de08ab..cd09f68 100644 --- a/resumes/Murtadha.tex +++ b/resumes/Murtadha.tex @@ -117,22 +117,25 @@ \section{\color{blue}Relevant Work Experience} \resumeSubHeadingListStart \resumeSubheading - {ML Engineer - Researcher}{Jan 2024 -- Dec 2024} - {University of Guelph}{Guelph, Ontario} + {MLOps Engineer - Researcher}{Jan 2024 -- Dec 2024} + {University of Guelph}{Guelph, Ontario} \resumeItemListStart - \resumeItem {Pioneered transformer-based models for semantic data transmission, reducing latencies in E2E communications by 29\%, and reducing network bandwidth utilization by 30x} - \resumeItem {Authored deployable implementations in C on Kira SoCs with Vitis AI™, utilizing hardware acceleration achieving 15\% computional time reduction} - \resumeItem {Published findings in CCECE 2024, showcasing improved data transmission latencies} - \resumeItemListEnd + \resumeItem {Collected latency data from diverse hardware setups and performed feature engineering to identify optimal correlations, enhancing model performance in varying network 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\% accuracy} + \resumeItem {Pioneered deployable transformer-based models for semantic data transmission, achieving 29\% lower latencies in end-to-end communications specifically 30x reduction in network bandwidth utilization} + \resumeItem {Deployed existing PyTorch-based implementations onto Kira SoCs using Vitis AI™, leveraging hardware acceleration to achieve a 15\% reduction in computational time} + % \resumeItem {Published findings in CCECE 2024, showcasing improved data transmission latencies} + \resumeItemListEnd \resumeSubheading {Software Developer}{Oct 2022 -- Oct 2023} {University of Guelph - Robotics Institute}{Guelph, Ontario} \resumeItemListStart - \resumeItem {Developed ROS2 modules in C++ and Python in the process of migrating from a standalone Python implementation for an Assistive Robotic Feeding System for Elderly Individuals, accounting for multithreaded operations' integrity} - \resumeItem {Co-authored a feedback loop in the React Native mobile app to provide analytics from 50+ users reporting users' interactions to enhance user experience and app performance} - \resumeItem {Deployed a Node.js backend system in an EC2 instance, coupled with a PostgresDB to monitor and analyze users' activity as part of a research survey} - \resumeItemListEnd + \resumeItem {Developed ROS2 modules in C++ and Python to migrate an Assistive Robotic Feeding System for Elderly Individuals, ensuring multithreaded operations' integrity} + \resumeItem {Managed and maintained the codebase of a smart door application suite with a Node.js backend, React Native app, and Vue dashboard, enabling smartphone control of motorized doors and providing user analytics from over 50 users} + \resumeItem {Built a Jenkins CI/CD pipeline for automated building, testing, and deployment of Node.js backend, Vue frontend, and React Native app, with Dockerized PostgresDB for data handling} + \resumeItem {Implemented Terraform for IaC to automate AWS resource provisioning, enhancing the scalability and reliability of the smart door system} + \resumeItemListEnd \resumeSubheading {Information Technology Analyst}{Jul 2020 -- Oct 2020} @@ -148,9 +151,9 @@ %-----------SKILLS----------- \section{\color{blue}Skills} \begin{tabular}{ @{} >{\bfseries}l @{\hspace{3ex}}l } - \small\textbf{\color{black}Languages:} &\small C/C++/C\#, Python, JavaScript, SQL, R, Java, HTML, MATLAB, CSS\\ + \small\textbf{\color{black}Languages:} &\small C/C++/C\#, Python, JavaScript, SQL, Java, HTML, MATLAB, CSS\\ \small\textbf{\color{black}Frameworks:} &\small PyTorch, Node.JS, React, Express JS, .NET, TensorFlow, ROS, Django \\ - \small\textbf{\color{black}Cloud \& DB:} &\small Docker, AWS, Kubernetes, WoodPecker CI, PostgresSQL, MongoDB, MySQL, SQLite \\ + \small\textbf{\color{black}Cloud \& DB:} &\small Docker, AWS, Kubernetes, PostgresSQL, MongoDB, MySQL, SQLite \\ \small\textbf{\color{black}Tools \& Protocols:} &\small Git, Jenkins, Postman, Flask, Swagger, HTTP, TCP, Jira, CMake \\ \end{tabular} \vspace{-8pt} @@ -158,17 +161,11 @@ %-----------PROJECTS----------- \section{\color{blue}Projects} \resumeSubHeadingListStart - \resumeSubItem{\textbf{\color{black}Transformer-based Semantic Transcoding:}} - {Developed PyTorch models for E2E semantic transcoding, deployed on Xilinx SoC boards using Vitis AI™} + \resumeSubItem{\textbf{\color{black}Full-stack application}} + {Developed and Dockerized a full-stack portfolio using React and Java (adhering to microservices architecture) and deployed it on a home server using a Jenkins CI/CD pipeline and Minio S3 bucket} - \resumeSubItem{\textbf{\color{black}CI/CD React Portfolio Website}} - {Designed and developed a personal portfolio website using React. Implemented a CI/CD pipeline to automate the building, testing, and deployment process} - - \resumeSubItem{\textbf{\color{black}Clean Architecture C\# Backend:}} - {Engineered a scalable portfolio website backend using C\#, adhering to Clean Architecture and REST API principles and implementing CI/CD pipeline for efficient deployment} - - \resumeSubItem{\textbf{\color{black}DevOps Homelab Maestro:}} - {Orchestrating a robust homelab environment with Docker containers, Kubernetes clusters, Ceph distributed storage, and CI/CD pipelines for seamless application deployment} + \resumeSubItem{\textbf{\color{black}DevOps Homelab}} + {Orchestrating a robust homelab environment with dockerized apps, virtual machines, Kubernetes clusters for load distribution, Ceph distributed storage and CI/CD pipelines for seamless deployment of personal applications} \resumeSubItem{\textbf{\color{black}RL Dynamic Noise Cancelling:}} {Implemented real-time Automatic Noise Filtering using Reinforcement Learning and Dynamic Sparse Training in PyTorch} @@ -195,7 +192,7 @@ {Boosting Edge-to-Cloud Data Transmission Efficiency with Semantic Transcoding}{} {Published @ IEEE CCECE (Aug 2024)}{} \resumeItemListStart - \resumeItem {Explored a novel approach to incorporate semantic transcoding in edge-cloud system to reduce data transmission rates} + \resumeItem {Explored a novel approach to incorporate semantic transcoding in edge-cloud system to reduce data latency rates} \resumeItemListEnd \resumeSubHeadingListEnd \end{document}