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Alumni Roster
Dongjin Seo, Ph.D. 2016

Electrical Engineering
Advisor: Prof. M.M. Maharbiz/E. Alon
Research Interests: My research interests generally lie in the topics that intersects electrical engineering, applied physics, and bioengineering. Particularly, I am currently exploring the relams of low-power integrated circuit design, biosensor/circuit interfaces, and next-generation wireless circuits and systems for communication.
Job Interests: Academic, industry R&D, or start-up

Dongjin (DJ) Seo is currently pursuing his PhD in Electrical Engineering with an emphasis on low-power integrated circuit design and brain-machine interfaces. He received the B.S. degree in Electrical Engineering with honors from the California Institute of Technology in 2011. At Caltech, DJ designed and fabricated microfluidic calorimeters for high-throughput biochemical measurements at the Kavli Nanoscience Institute and for his undergraduate thesis, demonstrated the world’s first all-silicon THz imaging system in CMOS for security imaging and microscopy of biological specimens. DJ has also completed internships at Jet Propulsion Laboratory and Altera Corporations. DJ is the recipient of a NSF Graduate Research Fellowship.

Neural Dust: An Ultrasonic, Low Power Solution for Chronic BrainMachine Interfaces [BPN716]
A major hurdle in brain-machine interfaces (BMI) is the lack of an implantable neural
interface system that remains viable for a substantial fraction of a primate lifetime.
Recently, sub-mm implantable, wireless electromagnetic (EM) neural interfaces have been
demonstrated in an effort to extend system longevity. However, EM systems do not scale down
in size well due to the severe inefficiency of coupling radio waves at mm and sub-mm scales.
We propose an alternative wireless power and data telemetry scheme using distributed,
ultrasonic backscattering systems to record high frequency (~kHz) neural activity. Such
systems will require two fundamental technology innovations: 1) thousands of 10 – 100 um
scale, free-floating, independent sensor nodes, or neural dust, that detect and report local
extracellular electrophysiological data via ultrasonic backscattering, and 2) a sub-cranial
ultrasonic interrogator that establishes power and communication links with the neural dust.
To test the feasibility of this approach, we performed the first in-vivo experiments in the
rat model, where we were able to recover mV-level action potential signals from the
peripheral nerves. Further miniaturization of implantable interface based on ultrasound
would pave the way for both truly chronic BMI and massive scaling in the number of neural
recordings from the nervous system.

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     Last Updated: Sat 2014-Aug-23 11:06:21

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