About Me
I'm an AI Developer Advocate at Red Hat with a background in Computer Science and Mathematics from UMass Boston. I'm passionate about building elegant solutions to complex problems, with experience spanning web development, systems programming, computer vision, and AI/ML technologies.
I enjoy solving complex problems and writing clean, scalable code. My work involves bridging the gap between developers and cutting-edge AI technologies, helping others leverage open source tools to build innovative solutions. Through both academic projects and professional experience, I focus on encouraging creativity, collaboration, and continuous learning in the developer community.
I'm always looking for opportunities to grow as a developer, explore emerging technologies, and take on challenges that push my creativity while making a meaningful impact through technology and developer education.
Experience
AI Developer Advocate
Red Hat
- Build and deploy containerized AI applications and inference pipelines using vLLM, RHOAI, and Kubernetes, creating reusable templates and automation for model deployment.
- Develop technical demonstrations and proof-of-concept systems showcasing LLM integration, fine-tuning workflows, and GPU-accelerated inference on Red Hat infrastructure.
- Create educational resources through code repositories, technical blog posts with implementation details, and hands-on workshops teaching AI/ML development on open-source platforms.
STEMPOWER Research Fellow
Alfred P. Sloan Foundation (UMass Boston)
- Spearheaded migration of legacy MATLAB jamming algorithms to Python for improved computer vision and Machine Learning integration utilizing Nividia's SionnaRT.
- Collaborated with graduate team to modernize signal processing codebase and enable CV framework compatibility.
Undergraduate Research Fellow
UMass Boston
- Developed automated computer vision pipeline for real-time detection and tracking of extracellular vesicles in microscopy video data.
- Project available on GitHub demonstrating advanced CV techniques and real-time processing capabilities.
Software Engineering Intern - Data Systems
Exelon – PECO
- Automated extraction and classification of 1,000,000+ equipment maintenance records from Cascade databases using Python, SQL, NLP, improving workflow efficiency and system resiliency in an Agile environment.
- Developed automated weekly reporting pipelines (Python, SQL) to filter and flag 30,000+ transmission/substation assets missing maintenance triggers, reducing manual effort and increasing reporting accuracy to 96%.
IoT & Embedded Systems Engineer
CRK Properties
- Engineered a WAN-enabled IoT leak detection system (embedded sensors, microcontrollers, network protocols) that detected 94% of leaks in a test environment, enabling automated monitoring and early alerts to minimize commercial building water damage.
Teaching Fellow & Grading Assistant
UMass Boston - Introduction to Computing
- Taught classes and facilitated test prep for 200+ students in Introduction to Computing coursework.
- Provided comprehensive grading and feedback to support student learning and development.
Data Engineer
Vote Jobs Maryland
- Built an automated legislative web scraping system (Python) to process 100,000+ voter records with 99.8% accuracy, reducing manual data entry time by ~80 hours.
- Ensured 100% data integrity for electoral information through automated multi-check workflows (Python, Pandas, SQL).
Process Automation Engineer
Barcoding Inc.
- Developed automated pipelines (Python, SQL) for RFID product tracking and operational metrics extraction, achieving 100% accuracy and reducing manual reporting by 40%.
Selected Work
Signal Jamming Simulation Sionna Ray Tracing
Migrated MATLAB jamming algorithms to Python for GPU-accelerated signal processing and machine learning integration using Nvidia's SionnaRT framework. Part of STEMPOWER Fellowship.
Real-Time Microscopy Video Analysis
Automated computer vision pipeline for detecting and tracking extracellular vesicles in microscopy video data. Enables high-throughput analysis of biological samples for research applications.
Haste RL - Autonomous Speedrunning Agent
Built a reinforcement learning system that plays the Steam game "Haste" by processing live screen capture data and executing keyboard inputs. The agent learns parkour mechanics and optimal routing through trial-and-error, progressively improving completion times to match human speedrunner performance. [Currently Training!]
What's on your mind?
I'd love to hear from you!