Vertically Integrated Projects
Goals
Mental health is critical for our overall well-being, and emotional health challenges are rising globally, especially during and after the pandemic. The emergence of artificial intelligence (AI) can assist community residents and providers with some elements of support in decision-making that can ease the pressure on the behavioral health care system.
This research aims to understand the feasibility, gain insights, and employ cutting-edge AI in the emotional well-being domain to form an AI-human team to bolster the personalized care that a trained clinician provides. With the shortage of clinicians in the field, we need to turn to AI for specific emotional well-being tasks and supports that AI can do effectively. Therefore, in this research, we plan to develop and deploy natural language and wearable sensing-based multimodal techniques to form an AI-human system as a personalized emotional well-being companion for a large-scale student population. This teaming system will enhance the ability of clinicians to assist with delegating certain elements of emotional support provision to AI while the clinician completes the more complex and sophisticated elements.
Experience Gained
We plan to conduct the following high-level research activities to achieve the above project goal, and it will help students gain desired skills in the respective fields as well.
- Explore and understand multimodal data, e.g., texts and wearable sensor signals.
- Participate and assist in relevant data collection process.
- Use existing software tools, e.g., prodigy, and Weka, mobile Apps to collect, annotate, analyze data, and identify inherent characteristics of the data.
- Analyze data to showcase inherent characteristics and convey messages from the data.
- Read relevant state-of-the-art literature and be capable of summarizing the findings.
- Programming knowledge is not required, but good to have it for analysis and AI tools development.
- Designing, developing, and deploying AI algorithms -- machine learning, deep learning, reinforcement learning algorithm, and natural language processing pipeline (not mandatory).
- Interact and provide feedback to the AI-based system and observe the changed behavior of the human-AI system to monitor overall performance.
- Conducting and disseminating research findings into writing and publishing internal and external venues (symposium, conference, workshop).
