Madison, Wisconsin, United States
I'm a biomedical engineering student at UW-Madison passionate about integrating AI, biomaterials, and medical device design to improve patient outcomes. My career path is driven by a desire to create solutions that make a measurable, lasting impact on patient care and improve the efficiency of the teams who deliver it. I put my efforts into the intersection of engineering and AI, building multimodal pipelines, automated systems, and efficient tooling in Python, Java, MATLAB, and RAG/GPT integrations. My projects include OpScribeAI, a multimodal operative-report generator, a bone cyst biomaterial and bioreactor system, and 3D anatomical models now used by 200+ students. Throughout my internships, I've deployed AI tools that cut retrieval times from minutes to seconds, automated reporting and tracking systems, and improved efficiency across organizations. I'm pursuing opportunities in medtech, clinical AI, and biomaterials, and am always open to connecting with anyone working to shape the future of healthcare.
Co-founded OpScribe-AI, a platform that transforms multimodal surgical data (video, audio, and images) into structured operative reports. Lead development of a multimodal AI pipeline focused on reducing surgeon documentation burden while improving report consistency and accuracy. Apply biomedical engineering principles, clinical workflow analysis, and applied machine learning to build a scalable solution for real-world healthcare environments.
- Researched and evaluated AI tools tailored to biomedical engineering, focusing on medical imaging, research simulations, and biomaterial discovery. - Identified high-impact, practical use cases that improve clinical workflows, accelerate R&D, and enhance engineering efficiency in the medical field. - Created educational content, including articles, guides, and technical tutorials, demonstrating how AI can support medical-device development, imaging analysis, and experimental research. - Translated complex AI capabilities into accessible workflows for healthcare and engineering teams. - Collaborated with the editorial team to build a professional brand centered on AI-driven innovation in medicine and the future of biomedical engineering.
- Prototyped and deployed AI tools in Python and Java, cutting file retrieval time from 3–5 minutes to 10 seconds company-wide - Automated competitor monitoring by building an email alert and API-driven article summarization system, saving the marketing team 2–3 hours weekly - Built an automated commission-tracking system that emailed partners, extracted replies, and populated Excel sheets, saving the finance team 5-6 hours each month - Automated tracking of app-enabled screen shipments by populating and sorting building-specific tabs with contact info, streamlining operations across 25–35 buildings - Enabled encrypted access to more than 100 confidential files, queried daily by all employees to improve speed and security of internal operations - Led internal R&D initiatives leveraging large language models, using MATLAB for data visualization to support actionable tools, implementation plans, and cross-team adoption
- Reduced average service time by 25% by creating an improved end-of-day chemical and water loading system, and strengthened client relationships through proactive communication, resulting in a 20% increase in 5-star ratings - Demonstrated reliability and autonomy while managing field operations with minimal supervision - Communicate with customers about treatment plans and answer questions. Maintain accurate service records and contribute to route efficiency and scheduling improvements. Independently apply treatment solutions. Keep track of payments from clients. Train new employees.