Experience

Arctop

• United States
• Software Development
• 1 - 100 Employee

• Algorithm Engineer

  • Aug 2023 - Present



Microsoft

• United States
• Software Development
• 700 & Above Employee

• Research Intern

  • Apr 2023 - Jun 2023

  Developing deep learning models for EEG signal cleaning and reconstruction. Developing deep learning models for EEG signal cleaning and reconstruction.



UC San Diego

• United States
• Higher Education
• 700 & Above Employee

• Graduate Student Researcher

  • Sep 2017 - Mar 2023

  1. Working in Swartz Center of Computational Neuroscience 2. Developing real-time Brain-Computer Interface systems 3. Developing machine learning algorithms on physiological data Virtual Reality Experiment System: Building multi-modal system integrating motion capture, virtual reality, eye-tracking and Electroencephalography (EEG, i.e. brain-waves) recording to study behavioral data. Portable Brain-Computer Interface: Developing portable Brain-Computer Interface (BCI) system, a high-speed speller controlled by brain signals from visual area. Implemented state-of-the-art algorithm with highest information-transfer rate on Android platform. Transfer Learning on Brain-waves Data: Developing transfer learning algorithm on EEG data. Reduced calibration time of BCI system without compromising performance by inter-user transfer learning which makes BCI systems more practical to use. Show less



Meta

• United States
• Software Development
• 700 & Above Employee

• Research Scientist Intern

  • Jul 2022 - Feb 2023



Microsoft

• United States
• Software Development
• 700 & Above Employee

• Research Intern

  • Mar 2022 - Jun 2022

  Working on a Brain-computer Interface (BCI) project mentored by Weiwei Yang in the Living Interfaces Group. Designed and ran the experiment to study physiological signatures of the states of high or low level of cognitive loads. Analyzed EEG, (i.e., brainwaves) and digital sensing (i.e., camera) data to find robust features across different sessions and users. Working on a Brain-computer Interface (BCI) project mentored by Weiwei Yang in the Living Interfaces Group. Designed and ran the experiment to study physiological signatures of the states of high or low level of cognitive loads. Analyzed EEG, (i.e., brainwaves) and digital sensing (i.e., camera) data to find robust features across different sessions and users.



Microsoft

• United States
• Software Development
• 700 & Above Employee

• Research Intern

  • Jun 2020 - Sep 2020

  Built a close-loop BCI framework using adaptive learning methods to enhance the robustness of the system. The framework can generate pseudo-labels for online testing trials by detecting the brain responses to erroneous outputs, and then use the reinforcement signals to fine-tune the CNN-based model used in the BCI. Built a close-loop BCI framework using adaptive learning methods to enhance the robustness of the system. The framework can generate pseudo-labels for online testing trials by detecting the brain responses to erroneous outputs, and then use the reinforcement signals to fine-tune the CNN-based model used in the BCI.



National Taiwan University

• Taiwan
• Higher Education
• 700 & Above Employee

• Research Assistant

  • Feb 2016 - Jun 2017

  1. Worked at High Performance Computing Lab directed by Prof. Sheng-De Wang. 2. Built four programs in C, C++, Python and JavaScript on Raspberry Pi to allow the devices to automatically establish a network and relay Bluetooth packages. Enhanced coverage of the network to six times compared to traditional Bluetooth connections. 3. S. Wang and K. Chiang, "BLE Tree Networks for Sensor Devices in Internet of Things," 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Orlando, FL, 2017, pp. 1304-1309. Show less



GENGEE Sports

• China
• Spectator Sports

• Intern

  • Jul 2015 - Aug 2015

  1.Firmware development and JTag debugging with Texas Instruments SensorTag to transmit IMU data via Bluetooth Low Energy. 2. Analyzed IMU data from SensorTag plugged inside the smart basketball to calculate the locus and rotation of the ball. 3. Designed and wrote IOS app with Objective C to receive data from the basketball. 4.Won 400,000 RMB for the second prize in Xiamen Area China Innovation and Startup Contest. 1.Firmware development and JTag debugging with Texas Instruments SensorTag to transmit IMU data via Bluetooth Low Energy. 2. Analyzed IMU data from SensorTag plugged inside the smart basketball to calculate the locus and rotation of the ball. 3. Designed and wrote IOS app with Objective C to receive data from the basketball. 4.Won 400,000 RMB for the second prize in Xiamen Area China Innovation and Startup Contest.