Current Research Position

Postdoctoral Research Associate, UCI Brain Computer Interface Lab of Dr. An Do, in active collaboration with Dr. Zoran Nenadic and Dr. Payam Heydari of Dept. of Neurology & Biomedical and Electrical Engineering, University of California, Irvine, CA. Mar. 2019 – Present.
  • Designing and implementing Bi-directional Brain-Computer Interface (BD-BCI) which both reads from and writes to the sensorimotor brain to facilitate re-walking of persons with spinal cord injury (SCI).

Education

Postdoctoral Research Fellow, Action Lab, Department of Biology, Northeastern University, May 2017-Feb. 2019.
Postdoctoral Research Fellow, INSPIRE Lab, Rehabilitation Medicine, Emory School of Medicine / Georgia Tech Bioengineering. Sept. 2015- April. 2017.
​
Ph.D. Biomedical Engineering. University of Southern California. Expected graduation: 2015. 
  • Advisor: Terence D. Sanger. MD, PhD.  Link
M.S.  Electrical Engineering, University of Southern California, 2014.
B.S.   Electrical Engineering and Computer Science, University of California, Berkeley, 2007.  
          Han Young Foreign Language High School, Seoul, Korea.  

Research history



Breadth of Knowledge 
(courses taken in Engineering & Science) 

Biomedical Eng. |   Electrical Eng.  |  Computer Science  |  Medicine | Philosophy of Science 
Biomedical Engineering
  • BME501 - Advanced Topics in Biomedical Systems, USC
  • BME502 - Advance Studies of the Nervous System, USC
  • BME504 - Neuromuskular Systems, USC (Audit)
  • BME 505A/B - Laboratory Projects in Biomedical Engineering, USC
  • BME511 -  Physiological Control Systems, USC
  • BME513 - Signal and Systems Analysis, USC
  • BME566A/B - Topics in Health, Technology and Engineering, USC
  • BME599  - Nonlinear filtering theory, USC 
  • BIOE C265 - Principle of  Magnetic Resonance Imaging, UC Berkeley

Biological Science
  • BIO1A - General Biology, Berkeley College
  • CHEM1A-  General Chemistry, Foothill College
  • OCHEM3AL - Organic Chemistry AL, UC Berkeley
  • BISC325 - Genetics (audit), USC
  • Bioinformatics Algorithm, UC San Diego (Coursera)
  • BIOL5601 -Multidisciplinary Approaches to Motor Control, Northeastern University. 

Statistics
  • PM 510 - Principle of Biostatistics, USC

Engineering etc.
  • NE 107 - Introduction to Medical Imaging, UC Berkeley

Teaching Courses
  • EE142 - Integrated Circuit for Communications, UC Berkeley
  • BME101 - Introduction to Biomedical Engineering, USC
  • BME302L - Medical Electronics, USC
  • BME511 - Physiological Control Systems, USC

College-level Math & Natural Science
  • Calculus
  • Multivariable Calculus
  • Linear Algebra
  • General Physics
  • Modern Physics

Philosophy of Science 
  • Understanding Philosophy of Science (by James Ladyman)
  • The Modern Intellectual Tradition: From Descartes to Derrida (Lawrence Cahoone, Stony Brook University)
  • Philosophy of Science (Jeffrey L. Kasser, ​University of Michigan Ann Arbor)
Electrical Engineering
  • EE 577B - VLSI System Design, USC
  • EE/CS 545 -  Robotics, USC
  • EE 529 - Optics, USC
  • EE 482 -  Linear Control Systems, USC
  • EE 464  - Probability Theory for Engineers, USC
  • EE 441 -  Applied Linear Algebra for Engineers, USC
  • EE20 - Structure and Interpretation of Signal and Systems, UC Berkeley
  • EE40 -Introduction to Microelectronic Circuits, UC Berkeley
  • EE105 - Microelectronic Devices and Circuits, UC Berkeley
  • EE145C - Introduction to Electronic Tranducers Laboratory, UC Berkeley
  • EE120 - Signal and Systems, UC Berkeley
  • EE130 - Integrated Circuit Devices  , UC Berkeley
  • EE140 -Linear Integrated Circuits, UC Berkeley 
  • EE141 - Introduction to Digital Integrated Circuits, UC Berkeley
  • EE142 - Integrated Circuits for Communications, UC Berkeley

Computer Science
  • MIT 18.06 Linear Algebra 
  • MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
  • CS 567 - Machine Learning, USC
  • EE/CS 545 - Robotics, USC
  • CS / EE 450  - Introduction to Computer Networks,  USC
  • CS 61A - The Structure and Interpretation Computer Programs - UC Berkeley
  • CS 61B - Data Sturctures, UC Berkeley
  • CS 61C - Machine Structures, UC Berkeley
  • CIS 27A  - Introduction to JAVA, Foothill College
  • CIS 27B/C - JAVA, GUI design, Data Structures, Foothill College
  • KAGGLE Machine Learning courses 
    • ​Introduction to Machine Learning 
    • Intermediate Machine Learning
    • Deep Learning
    • Feature Engineering

Skills & Tools

SOFTWARE ENGINEERING
  • Proficient in R programming: ggplot, data analysis with statistical tests. (5+ years)
  • Proficient in python: dataframe, pandas, scikit-learn, opencv, etc.   (8+ years)
  • Strong traditional programming: C++, C, Java, MIPS.  (15+ years)
  • Expert in Matlab (10+ years)
  • Proficient in Android programming (2+ year)

HARDWARE ENGINEERING
  • Embedded programming: ARM Cortex-M0+, arduino.  (3+ years)
  • Hardware programming / HDL programming: Verilog, VHDL.  (5+ years)

STATISTICAL ANALYSIS
  • Trained statistician:  lead authors in peer-reviewed multiple clinical studies 
  • R statistical packages for advanced analyses

MACHINE LEARNING 
  • Neural signal analysis with brain signal decoding 
  • Regression, classification, deep learning experience

Last update:  August 2020