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Mental health is a major societal challenge. In the US, approximately 1 in 5 adults (46.6 million) experiences mental illness in a given year; 1 in 5 youth aged 13–18 (21.4%) and 13% of children aged 8-15 experiences a severe mental disorder; over 30% of adolescents and 18.1% of adults experience an anxiety disorder. Engineering technologies have the potential to improve diagnosis, intervention, and treatment of mental illness. In the Viterbi School of Engineering, a growing number of faculty are exploring research relevant to mental health.



Heather Culbertson

Wearable haptic devices for emotion regulation through virtual touch


Gale Lucas

Virtual reality and computerized assessments for depression and anxiety; web resources for prevention around depression and anxiety


Maja Mataric

Socially assistive robotics for anxiety and depression coping and companionship and machine learning for personalized anxiety-management wearable devices


Shri Narayanan1

Shri Narayanan

Bio-behavioral machine intelligence to support human and autonomous decision making; novel diagnostics, personalized interventions, and tracking treatment in mental and behavioral health

Maryam Shnechi1

Maryam Shanechi

Neurotechnology development; Closed-loop neuromodulation in depression, anxiety, chronic pain; Direct electrical brain stimulation; Neural decoding of mood; Brain network modeling; System identification for brain networks.


Mohammad Soleymani

Computational mental health assessment from verbal and nonverbal behavior (depression, PTSD, alcohol abuse); conversational virtual agents for therapeutic interviewing.


Jennifer Treweek

Whole-organ molecular phenotyping and circuit-mapping to inform novel treatment modalities for stress-related disorders; non-invasive approaches for modulating depression-associated neural networks.

Phebe Vayanos 1

Phebe Vayanos

Robust and fair suicide prevention interventions for vulnerable populations.


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