Leveraging Artificial Intelligence for Mental Health Support

Research project description

PhD will investigate and to develop AI-based solutions to enhance mental health care, addressing the need for accessible and effective resources. 

Key focus areas include: 

1. Supportive AI Chatbots & Early Detection Algorithms: Developing AI chatbots for initial mental health support and guidance, complementing professional care. Also, creating algorithms to identify early mental health concerns, aiding specialists in early intervention. 

2. AI-Assisted Personalized Care Recommendations: Creating AI systems to analyze health records and user inputs, helping healthcare professionals craft personalized treatment plans, thereby improving care effectiveness. 

3. Data Security in Mental Health Tech: Ensuring high data privacy and security standards in digital health tools used by professionals and patients, contributing to the ethical application of technology in sensitive health areas. 

4. AI Tools for Therapeutic and Community Support: Developing AI-driven assistants and community analysis tools to support therapists and counselors. These tools aim to provide tailored therapy and maintain constructive online support environments. 

5. Designing Intuitive Interfaces for Health Tech Tools: Creating user-friendly interfaces for digital health applications to assist mental health professionals, making these tools more accessible and effective in therapeutic settings. 

6. Understanding human cognition and affective experience in health and disease: we will use the lens of predictive processing, particularly in the field of emotion, social perception, and creativity, which are heavily related to mental health, in combination with AI to better understand human experience. 

Participating in this research offers valuable opportunities in academia and industry, building skills and experiences in AI for mental health, a field of growing importance in tech companies, healthcare organizations, and research institutions.

Academic background / Skills

Candidates must hold a degree that allows admission to the official doctoral programme at UAB.  

Additional requirements for a stronger application are: 

• Master’s degree in Computer Science, Mathematics, Data Science, AI, or a related field. 
• Notions in Psychology/Psychiatry may be beneficial. 
• Prior experience in conducting research is essential (Master’s thesis, participation in research projects, etc). 

Preferred Skills and Learning Opportunities: 

• Programming languages such as Python or R are needed. 
• Knowledge of machine learning algorithms and libraries (like TensorFlow or PyTorch). 
• Experience with Natural Language Processing (NLP) is highly desirable. Experience in fine-tuning and applying Large Language Models, such as ChatGPT or LLAMA, is highly valued. 
• Skills in data preprocessing, analysis, and visualization are important. 
• Ability to teamwork 
• An understanding of ethical considerations in AI and data privacy is essential. 

Research group/s description

The present PhD project is a truly transdisciplinary proposal involving two groups of research: 

1) The AI and Data Science Research Group is a multidisciplinary team of experts at the Computer Vision Center (UAB) and the University of Barcelona united to harness tech for societal benefit. The team includes specialists in artificial intelligence, machine learning, data analysis, and mental health. They specialize in creating AI solutions for predictive tasks, text analysis, and tailored treatment approaches, seeking to enhance mental health care using AI- driven methods. 

2) The Cognitive and Affective Science Laboratory, led by Lorena Chanes, is a research group at the Department of Clinical and Health Psychology-Institute of Neurosciences. Their research focuses on cognitive and affective processes that ultimately lead to conscious experience and how they relate to mental health. They have a multidisciplinary approach including behavior, non-invasive brain stimulation and neuroimaging.