Systems & Research Engineer focusing on musculoskeletal biomechanics, AI integration, and operational architecture. Expertise in designing "Cognitive Operating Systems" and automated workflows, with a proven track record of bridging technical research with scalable clinical operations. Proficient in Python, C++, TypeScript, and cross-platform systems integration.
Work Experience
- Systems Automation: Engineered internal automation solutions using VBA for Excel, Office Scripts, and cloud webhooks to streamline clinical data processing and reduce manual administrative overhead.
- Infrastructure Management: Managed clinical IT assets and secure data environments, including granular access control and governance of sensitive patient data within cloud environments.
- Technical Operations: Spearheaded the maintenance and full lifecycle management of complex physical therapy machinery, acting as the primary liaison with vendors to troubleshoot, service, and resolve critical equipment hardware issues.
- Documentation & Training: Designed and deployed comprehensive clinical workflow wikis and documentation, utilizing video and workshop-based training to onboard and mentor 12+ staff on technical protocols and documentation best practices.
- Software Development: Developing a secure, custom-built beta application for tracking patient medical cases and exercise programs, focusing on data integrity and high-security standards.
- Collaborated with faculty to instruct 150+ students on dynamic web development (HTML/CSS/JS).
- Monitored 20+ GitHub repositories; supervised project lifecycles and provided technical feedback based on rigorous instructional standards.
Projects
Developed a real-time motion analysis prototype using Python and WebRTC (aiortc/aiohttp) for peer-to-peer media streaming. Implemented dynamic muscle layering and force vector dynamics (joint reaction, tension, and compression) to visualize and analyze movement mechanics. Designing an educational JIT pedagogy engine that utilizes recursive tree traversal of Notion databases to map human knowledge gaps and deliver micro-syllabi.
Built a distributed C/C++ CLI application for real-time system introspection (CPU/Network/Storage) with custom logging for distributed processes. Virtualized networking stacks (Link to Application layer) and implemented complex job scheduling policies using Python and React.
Research Interests
Creating high-fidelity, real-time simulations of musculoskeletal systems for performance and rehabilitation enhancement.
Developing adaptive learning systems that integrate symbolic reasoning with neural networks to bridge human knowledge gaps.
Engineering intuitive AI interfaces that leverage computer vision and biomechanical data to provide real-time, personalized feedback.
Designing resilient, sharded systems for high-performance AI research applications.