Researching the intersection of neuroscience, cognitive science, medical technology, and AI (including human-machine and brain-computer interfaces) to optimize the financial decision-making process, enhance real-time crisis management, and design systems that augment human capabilities by accounting for emotional and cognitive biases.
- Enhanced Decision-Making: Leveraging brain-computer interfaces (BCI) to monitor neural responses in real time, thereby optimizing financial decision-making processes under high-risk or volatile market conditions.
- Behavioral and Emotional Analysis: Using neuroimaging techniques (such as EEG or fMRI) to detect and analyze the emotional and cognitive factors that influence investor behavior, ultimately improving the prediction of market trends and investment outcomes.
- Investor Training and Development: Implementing neurofeedback and virtual reality-based training programs that help investors identify and mitigate cognitive biases and stress responses during trading, leading to more rational decision-making.
- Adaptive Algorithm Development: Combining insights from neuroscience with AI to develop algorithms that adjust to the cognitive and emotional states of users, creating more personalized and effective investment strategies.
- Crisis Management and Risk Mitigation: Utilizing neurotechnology to monitor cognitive reactions during financial crises, enabling the design of systems that can preemptively detect stress signals and mitigate potential losses.