Kyun Kyu (Richard) Kim
Apple, Cupertino. Sensing Design Engineer
Email: enthusiakk@gmail.com / rikim@stanford.edu
Github: https://github.com/richkim92
I specialize in the co-development of integrated hardware and artificial intelligence for wearable human-machine interfaces, with a focus on VR/AR and healthcare applications.
- AI algorithms for time-series signal processing, enabling motion prediction and language translation from physiological signals
- Generative AI models that extrapolate sensory data to enhance and enrich wearable experiences in augmented environments
- Wearable system design for capturing high-precision motion, health, and language signals, including EMG, ECG, and strain sensors
Research Experience
Postdoctoral Research Fellow (2021.09-2023.11)
Bao Research Group, Stanford University
• AI-augmented wearables for human-machine interface. Keyboard-less typing and gesture prediction through few-shot learning
• AI-augmented wearable EMG array for gesture/health/language prediction
Postdoctoral Fellow (2021.03-2021.09)
Soft Robotics Research Center (SRRC, srrc.snu.ac.kr), Seoul National University, Seoul, Korea
Project: Skin-sensors combined with machine intelligence
Ph.D. Researcher (2014-2021)
Seoul National University
• AI-based patch that decode human gestures.
• Ultra-thin wearables for human physiology/gesture.
• Transparent wearable 3D touch sensor.
Degree & Education
Ph.D. in Mechanical Engineering (2016 – March 2021)
Seoul National University, Seoul, Korea
(Thesis title: Augmented skin electronics for human-machine interaction based on laser nano structuring and machine intelligence)
M.S. in Mechanical Engineering (2014 – 2016)
Seoul National University, Seoul, Korea
(Thesis : Highly Sensitive and Stretchable Multidimensional Strain Sensor)
B.S. in Mechanical Engineering (2010 – 2014)
Korea University, Seoul, Korea, Graduation with Great Honor
Daejeon Science High School, Daejeon, Korea (2008-2009)
One-year early graduation
Honor & Awards
- MIT Innovators Under 35, 2022, Korea (Link)
- Post-Doctoral Overseas Training Fellowship granted by National Foundation of Korea (Strategic Field: Intelligent Semiconductor/Advanced Materials)
- 2020 Outstanding Doctoral Dissertation Award, Seoul National University
- 2020 Seoul National University Youlchon AI Honorable Mention (top 10 entry)
- Naver AI gitHackerthon Competition 2019, Entered the top 40 entry
- OSA (The Optical Society) Best Student Paper Prize (3rd)
- Global PhD Fellowship 2017 granted by the National Research Foundation of Korea
- Scholarship for academic excellence, Mechanical Engineering, Korea University, 2010-2012
- 55th National Science Exhibition (participated by 1,720 teams Awarded the 1st Prize by the
President of South Korea, Lee M.B, 2009)
- V-th Asian Pacific Astronomy Olympiad, 2nd Prize medal, 2009
President of South Korea, Lee M.B, 2009)
Invited Talks
- Innovations in AI-Enhanced Soft Sensors for Gesture Recognition, System X Alliance, Stanford University, June 2023 (Link)
- Soft Electronics for Biosignal & Human Machine interface, Korea University Medical Center (KUMC), Department of Physiology, May 2023
- AI-enhanced electronic skin that rapidly reads hand tasks with limited data, Stanford University, Wearable Electronics Initiative (eWear), Jan 2023 (Link)
- Electronic skin with AI for Augmented Human-Machine Interface, POSTECH, Mechanical Engineering, December 2022
- Electronic skin with AI for Augmented Human-Machine Interface, KAIST, Bio and Brain Engineering, December 2022
- Electronic skin with AI for Augmented Human-Machine Interface, Yonsei University, Mechanical Engineering, December 2022
- Electronic skin with AI for Augmented Human-Machine Interface, Seoul National University, Mechanical Engineering, December 2022
- Augmented skin electronics for human-machine interaction based on laser nano structuring and machine intelligence, Korea Institute of Industrial Technology (KITECH), February 2021
Skills & Certificate
- Software development
• Generative AI focused on VAE
• Time-series signal prediction model based on Transformer and few-shot training model
- Hardware development
• Embedded circuitry design for multi-modal signal measurement device
• Sensor design for human motion & physiology (Wearable EMG/ECG, touch, strain)
- Development tools & Other Languages : CSS Studio, Cadence, COMSOL, C/C++ code composer studio, LabVIEW
• Generative AI focused on VAE
• Time-series signal prediction model based on Transformer and few-shot training model
• Embedded circuitry design for multi-modal signal measurement device
• Sensor design for human motion & physiology (Wearable EMG/ECG, touch, strain)