As an MRes student in Neurotechnology with a foundation in Biotech and Life Sciences, I am dedicated to advancing innovation at the intersection of neuroscience and technology. My research focuses on developing a closed-loop brain-computer interface to enhance cognitive functions using a novel EEG headset for real-world applications. This work integrates device engineering, algorithm development, and neurostimulation, with the potential to transform mental health interventions. Additionally, I have worked on stem cell research for Parkinson’s therapy and fear response studies in animal models, reinforcing my commitment to impactful science.

The Hong Kong Laureate Forum offers a unique opportunity to connect with global leaders and peers across disciplines. I believe interdisciplinary collaboration is essential for transformative advancements. Engaging with distinguished Shaw Laureates and fellow young scientists will broaden my perspective and inspire innovative research approaches. The forum aligns with my goal of bridging academia and industry to develop neurotechnology products that enhance accessibility and address societal needs.

Alongside my technical skills, I aim to leverage my leadership experience—as a scholar, educator, and co-founder of entrepreneurship establishments and a neuroscience education platform—to contribute to the scientific community. Attending the forum will empower me to foster meaningful change through science and innovation.

My current research focuses on developing a wearable, extended ear-based EEG device designed to detect and modulate anxiety through real-time neural stimulation, which can serve as a model that allow real-world simultaneous application. By utilizing advanced dry conductive elastomer electrodes, this device aims to accurately capture neural markers of anxiety, such as frontal alpha asymmetry and variations in beta and alpha power. The integration of machine learning algorithms—like Support Vector Machines, Random Forests, and Convolutional Neural Networks—will enable effective classification of anxiety levels by analyzing EEG data alongside physiological and psychological metrics.

A key innovation of this project is the establishment of a closed-loop system that not only monitors anxiety but also delivers targeted stimulation techniques, such as transcranial direct current stimulation and cranial electrotherapy stimulation, to alleviate symptoms. Evaluating this system’s usability and effectiveness in real-world settings is essential for ensuring practicality and user acceptance. Ultimately, this research seeks to pave the way for the development of non-invasive, accessible solutions for anxiety management, contributing valuable knowledge to the field of neurotechnology and mental health interventions. In the future, serving as an anchor, the device can not only target anxiety modulation but various modulation of cognitive functions and beyond.