Dr. Michael Jo’s expertise includes Semiconductor Material/Device Physics and Simulation, and Computer Vision. He is interested in Computer Vision, Machine Learning, Integrated Media Systems, Semiconductor Material/Device Physics, and integration of Nanotechnology and Machine Learning. He is also interested in patent/market analysis and planning on including these topics in his courses.

Dr. Jo is currently pursuing multiple student-faculty involved projects including COVID-19 bionanosensor modeling/simulation and accelerated machine learning. Dr. Jo is seeking for highly motivated undergraduate and graduate students who can continue making positive impact to our community through these projects. Check out Dr. Jo’s recent webpage for more information.

Academic Degrees

Ph.D. in Electrical and Computer Engineering - University of Illinois at Urbana-Champaign, 2018
M.S. in Electrical and Computer Engineering - University of Illinois at Urbana-Champaign, 2013
B.E. Electrical Engineering - Korea University, Seoul, Republic of Korea, 2010

Awards & Honors

Harriett and Robert Perry Fellowship Award, ECE, UIUC 2015 - 2016
Ernest A. Reid Fellowship Award, ECE, UIUC 2014 - 2015
Olesen Award for Excellence in Undergraduate Teaching, ECE, UIUC Fall 2012
National Scholarship for Science and Engineering: awarded full 4-year scholarship for tuitions and school expenses, KOSAF, 2003-2010

Publications & Presentations

Jo, M., Kirkor, E., Sinha, S., Scheeline, A., Martin, P. and Ravaioli, U., “Dynamic Thermal Interface Material (D-TIM) Simulation and Parameter Optimization Using Genetic Algorithm,” IWCN 2019, Chicago, 2019

Jo, M. and Ravaioli, U., “Geometric Property Estimation Based on Raman Spectra Measurement Using Machine Learning,” IEEE 13th Nanotechnology Materials and Devices Conference (NMDC), Portland, 2019

“Smarter Simulation for Dynamic Thermal Interface Material: linking Machine learning and Computer vision to micro-nanotechnology," Invited Talk, University of New Haven, 2017

Chen, Y., Jo, M., Mohamed, M. and Xu, R., “Monte Carlo analysis of dynamic characteristics and high-frequency noise performances of nanoscale double-gate MOS-FETs,” International Journal of Numerical Modelling, 2013, DOI: 10.1002/jnm.1886.

Chen, Y., Mohamed, M., Jo, M., Xu, R. and Ravaioli, U., “Junction-less MOSFETs with laterally graded-doping channel for analog/RF applications,” Journal of Computational Electronics, 2013. DOI: 10.1007/s10825-013-0478-3

Research Experiences

Computer Vision and Machine Learning
Computational Nanotechnology
GPU accelerated ion beam therapy simulation
Multigate FinFET Current Noise Analysis
Energy Constrained System on Chips

Teaching Interests

Embedded Systems and Digital Systems
Image Processing and Computer Vision
Machine Learning and Artificial Intelligence
Semiconductor Material and Device Physics
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