James Morizio

James Morizio serves as an Adjunct Professor in the Department of Electrical and Computer Engineering at Duke University, leveraging 35+ years of expertise in analog CMOS microelectronics for biomedical applications. His research bridges electrical engineering with neuroscience through disruptive sensor interface technologies for neural recording/stimulation and ultrasonic microfluidics.

His educational background includes a

• Ph.D. in Electrical Engineering from Duke University (1995)
• M.S. in Electrical Engineering from University of Colorado, Boulder (1984)
• B.S. in Electrical Engineering from Virginia Polytechnic Institute and State University (1982)

Morizio's research focuses on developing high-performance neural interfaces and acoustofluidic systems. Key areas include wireless neural instrumentation for closed-loop electrophysiology, CMOS-based ultrasonic transducers for microfluidic manipulation, and low-power VLSI design for implantable devices. His work emphasizes translating microelectronics innovations into biomedical solutions for neuroscience and diagnostics.

His publication portfolio demonstrates consistent contributions to neural engineering and microfluidics, with recent trends showing increased focus on acoustofluidic diagnostics (e.g., AIMDx chip) and osseointegrated neural interfaces for prosthetic control. The research spans fundamental circuit design to translational applications in cancer metabolism and neuroprosthetics.

Scientific recognition includes

• 15-year service award from Triangle BioSystems International/Harvard Bioscience Inc. (2016)

Current research is supported by major grants including Neuro-CROWN (ultra-flexible electrode arrays), digital acoustofluidic systems for biomedical automation, and osseointegrated neural interfaces for prosthetic control. His teaching portfolio spans advanced VLSI design and special topics courses, though specific advising roles are not documented.

Collaborative work involves interdisciplinary teams in neuroscience and biomedical engineering, particularly through partnerships with Triangle BioSystems International and translational projects using ovine models for neural interface validation.