Jeehwan Kim, associate professor of mechanical engineering at MIT, is using his background in materials science to build a physical neural network and produce cheap semiconductor wafers – technologies that could help bring the artificial intelligence power of super computers to handheld devices.
A team of researchers led by Associate Professor Jeehwan Kim have designed a “brain-on-a-chip” smaller than a piece of confetti that could advance the development of small portable AI devices.
Associate Professor Jeehwan Kim has developed a new process that may be the key to manufacturing flexible electronics with multiple functionalities in a cost-effective way.
UNIVERSITY OF CALIFORNIA-LOS ANGELESPh.D.
SEOUL NATIONAL UNIVERSITYM.S.
‐ 1R-based ANN arrays for online training/inference
- Artificial synapses based on single-crystalline ReRAM
Remote epitaxy, Graphene-based layer transfer
‐ III-V/III-N MicroLEDs
- Freestanding InGaAs-based IR Photodectors
- Freestanding Multifunctional complex oxides for magnetoelectric coupling
- SiC/IIII-N power electronics
Renewable energy, Energy storage
- Wafer recycling technique for GaAs solar cells based on remote epitaxy
- High efficiency III-V multi-junction solar cells based on remote epitaxy
- Single-crystalline all solid-state battery
Heterointegration, Flexible electronics
- Skin strain sensor arrays
- Flexible/transparent microLEDs
- Self-powered IoT system
- Monolayer-by-monolayer splitting of wafer‐scale 2D materials
- Wafer-scale single-crystalline 2D materials
- Wafer-scale 2D heterostructures
2.001 Mechanics and Materials
2.674 Micro/Nano Engineering Laboratory
2.671 Instrument and Measurement