Resume

Professional Summary

Biomedical Engineer with hands-on experience designing and integrating electromechanical systems for implantable, wearable, and handheld medical devices, from SolidWorks CAD and DFM-driven enclosure design through analog signal acquisition, embedded firmware, and formal V&V testing. Comfortable moving between mechanical, electrical, and system-level work, translating user needs into design requirements, and communicating technical findings clearly to cross-functional teams.

Education

• BME Design Fellows, Society of Biomedical Engineers, Pratt Dean's List
• Relevant Coursework: Medical Device Design, Embedded Systems, Bioelectricity, Biomechanics, Medical Instrumentation, Signals & Systems, Product Engineering

Work Experience

• Analyze and structure large-scale commercial and clinical datasets, build data pipelines (Python, SQL), and translate technical analysis into clear reporting for pharmaceutical and biotech clients.
• Self-taught a clinical trial operating system used by a ~15-person team; synthesized scattered documentation into pipeline diagrams and data-structure spreadsheets to eliminate knowledge bottlenecks concentrated in 2–3 individuals.

• Led design reviews and troubleshooting sessions for 20+ students' medical device prototypes, identifying mechanical and system-level integration issues during hardware bring-up.
• Mentored students in circuit assembly, ECAD/CAD (KiCAD, Onshape), SPICE simulation, and firmware development (C++, Python).

• Defined performance requirements and executed verification testing for implantable LCP sEEG electrode systems; optimized heat-press encapsulation parameters to eliminate voids seen on CT imaging, and helped establish saline soak testing that later showed <0.006% mass loss over 30 days.
• Designed and built a gravity-tensioned electrode-coiling fixture targeting sub-1 mm mandrels, reaching 5.55 ± 0.28 mm pitch on 1 mm tubing; conducted impedance testing and signal characterization.

• Designed a production-intent, DFM-optimized enclosure for an at-home dry eye treatment device, from foam ergonomics mockups through 3D-printed prototypes; stacked tolerances between the CNC-machined tip and injection-molded housing to set mating dimensions.
• Built and automated a Python-based GUI application coordinating four USB-connected instruments (Modbus-controlled temperature chamber/reservoir, DAQ-driven pump/compressor, device data streaming) for unattended multi-day calibration trials; implemented multithreading and automatic outlier handling, reducing test time by 40%.

Projects

• Defined system-level requirements and led verification testing across EEG acquisition, embedded processing, and BLE telemetry, integrating hardware, firmware, and cloud-based ML into one wearable; authored the project's Design History File, including test protocols, FMEA, and V&V documentation.
• Designed the rebiasing and power circuitry, custom PCB, battery-monitoring circuit, and drop-resistant back-mounted enclosure; validated EEG acquisition (eyes-open/closed alpha power, p < 0.001) and end-to-end classification on non-epileptic subjects (76.5% average interictal accuracy across four subjects and three movement conditions). Finalist, People's Choice Award.

• Designed, built, and verified a VVI demand pacemaker (ECG acquisition, R-wave detection, pacing firmware, MOSFET stimulation stage) with BLE telemetry; validated stimulus width within 1.4% of a physiologically derived target and ~13 ms average wireless reporting latency.

Technical Skills