refactor: update points to highlight a specific role title
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2 changed files with 50 additions and 29 deletions
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@ -135,7 +135,7 @@
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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, with expertise in developing high-efficiency AI pipelines. Proven track record of reducing bandwidth demand by \textbf{30$\times$} while maintaining 96\% task accuracy in congested network environments
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AI Systems Engineer with expertise intersecting machine learning optimization, real-time distributed software design, and automated deployment infrastructure. Proven track record designing custom simulation environments, benchmarking edge-hardware bottlenecks, and orchestrating containerized continuous integration pipelines to optimize system constraints
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\vspace{-7pt}
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@ -150,12 +150,20 @@ Versatile Computer Engineer and Researcher specialized in Semantic Communication
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%-----------SKILLS-----------
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\section{\color{blue}SKILLS \& TECHSTACKS}
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\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
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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{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{Skills: } & AI Systems; DevOps; Cloud Infrastructure; IaC; Containerization; CI/CD Pipelines; Telemetry Monitoring; Agile/Scrum \\
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\textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash \\
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\textbf{Tech Stacks: } & PyTorch; Stable-Baselines3; ROS2; Arduino IDE; React; FastAPI; Flask; Jest; PyTest; Docker; Jenkins; Terraform; AWS (EC2, S3); Nginx Proxy Manager; Cloudflare; Prometheus; Grafana; SQLite; PostgreSQL \\
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\end{tabularx}
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\vspace{-10pt}
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% %-----------SKILLS-----------
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% \section{\color{blue}SKILLS \& TECHSTACKS}
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% \begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
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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{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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% \end{tabularx}
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% \vspace{-10pt}
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%----------Experience----------
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\section{\color{blue}WORK EXPERIENCE}
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@ -164,28 +172,29 @@ Versatile Computer Engineer and Researcher specialized in Semantic Communication
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{Researcher - Machine Learning \& Semantic Communications}{Jan 2024 – Dec 2025}
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{University of Guelph}{ Guelph, Ontario}
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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 {Extended models with adaptive deterministic mechanisms to handle bandwidth fluctuations and anomalies, ensuring stable real-time performance}
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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 {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 {Isolated and analyzed system bottlenecks across edge-cloud optical fiber networks, identifying a transition from transmission latency constraints to algorithmic compute bottlenecks during model execution}
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\resumeItem {Optimized end-to-end latency pipelines utilizing Swin Transformer architectures in PyTorch, establishing benchmarking frameworks to compare transmission times across unquantized, quantized (INT8), and baseline non-transformer data states}
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\resumeItem {Programmed an adaptive channel-selection algorithm utilizing logarithmic logic to dynamically scale the number of transmitted image channels based on real-time bandwidth and latency metrics}
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\resumeItem {Authored and published peer-reviewed research in IEEE conference proceedings focusing on task-driven feature extraction to mitigate computational and network overhead in edge-cloud architectures}
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\resumeItemListEnd
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\resumeSubheading
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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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\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 {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 {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 {Developed distributed node architectures for an automated feeding assistant robot within ROS2, writing native C++ and Python nodes to manage core services, topics, and real-time depth-sensor camera data feeds}
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\resumeItem {Designed and programmed firmware for an ESP32-based smart mechatronic door system within the Arduino environment, implementing Bluetooth Low Energy (BLE) for local smartphone authentication and Wi-Fi synchronization for backend logging}
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\resumeItem {Implemented power-management states within microcontroller firmware to alternate between low-power and normal-power operational modes during continuous field deployments}
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\resumeItem {Orchestrated cloud infrastructure provisioning via Terraform, automating the deployment of EC2 instances for application backends/frontends and S3 buckets for media asset management}
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\resumeItemListEnd
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\resumeSubheading
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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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\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 {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 distributed file architectures using a centralized Samba server, increasing secure data access and distribution efficiency by 40\% across multi-department teams}
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\resumeItem {Secured network topography via FortiGate firewall and VPN implementations, supporting 60 active remote users}
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\resumeItem {Deployed Prometheus and Grafana monitoring pipelines across a multi-container Docker environment to track system downtime, monitor SSH traffic, and isolate anomalous network activity}
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\resumeItemListEnd
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\resumeSubHeadingListEnd
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@ -194,28 +203,40 @@ Versatile Computer Engineer and Researcher specialized in Semantic Communication
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\section{\color{blue}PROJECTS}
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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}Real-Time Audio Filtering RL Environment} $|$ \color{blue} \emph{Python, PyTorch, OpenAI Gym, Stable-Baselines3, SciPy, librosa}}{}
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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{Constructed a custom OpenAI Gym audio environment (NoiseReductionEnv) running a frequency-domain control loop via Fast Fourier Transforms (scipy.fft.rfft) to manipulate harmonic scaling coefficients}
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\resumeItem{Trained a PPO agent over 10,000 timesteps using an MlpPolicy, minimizing Mean Squared Error (MSE) against clean baseline signals to synthesize sequential 44.1 kHz time-domain outputs}
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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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% \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{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}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{}
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\resumeProjectHeading{\textbf{\color{black}DevOps Server Infrastructure \& CI/CD Pipeline} $|$ \color{blue} \emph{Docker, Jenkins, Nginx Proxy Manager, Cloudflare, PyTest, Jest}}{}
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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{Self-hosted a containerized Jenkins automation server to manage continuous integration pipelines across 15+ microservices, executing automated validation via PyTest and Jest}
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\resumeItem{Architected a multi-layered proxy topography using Nginx Proxy Manager and Cloudflare to securely route web traffic, isolate runtime endpoints, and automate Let's Encrypt SSL/TLS renewals}
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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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\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{-7pt}
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% %-----------PROJECTS-----------
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% \section{\color{blue}PROJECTS}
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% \resumeSubHeadingListStart
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%
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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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% \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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% \resumeItemListEnd
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%
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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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% \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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%
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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{-7pt}
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\section{\color{blue}PUBLICATIONS}
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\resumeSubHeadingListStart
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