Dr. Caitlin Stamatis

Head of Clinical Research, Slingshot AI

Dr. Caitlin Stamatis is a clinical psychologist and researcher specializing in digital mental health, behavioral health technology, and AI-enabled care. As Head of Clinical Research at Slingshot AI, she leads research on the safety, efficacy, and responsible development of Ash and other purpose-built AI systems for mental health.

Over the past decade, Dr. Stamatis has held research and leadership roles across healthcare and technology, including at Google, Otsuka Pharmaceutical, and Akili Interactive. At Akili, she helped develop and validate novel digital measures of cognitive functioning derived from passively collected behavioral data, contributing to peer-reviewed research and the commercialization of Akili's Focus Score cognitive biomarker. Her work has supported the development and evaluation of pioneering digital therapeutics for conditions including ADHD and major depressive disorder.

Dr. Stamatis has authored research spanning digital phenotyping, passive sensing, machine learning, depression risk prediction, and technology-enabled mental healthcare. Her publications have examined topics including smartphone-based mental health monitoring, algorithmic bias in AI systems, and digital biomarkers for depression and anxiety.

She has served as adjunct faculty at Northwestern University Feinberg School of Medicine and holds leadership positions within organizations advancing the field of digital medicine, including the Society for Digital Mental Health.

Dr. Stamatis earned her B.A. in Psychology from Columbia University, where she was awarded a Fulbright Fellowship. She received her Ph.D. in Clinical Psychology with a quantitative specialization and completed her clinical residency at Weill Cornell Medicine.

Explore their work

Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction

npj Mental Health Research, 2024.

Explores how passively collected smartphone behavioral data can predict depression and anxiety symptoms over time in a large longitudinal cohort.

PubMed record

Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data

npj Mental Health Research, 2024.

Examines fairness, bias, and generalizability challenges in AI systems that predict depression risk from smartphone behavioral signals.

Full text on PubMed Central

Prospective Associations of Text-Message-Based Sentiment with Symptoms of Depression, Generalized Anxiety, and Social Anxiety

Depression & Anxiety (Wiley), 2022.

Demonstrates how language patterns in text messages can be associated with future symptoms of depression, anxiety, and social anxiety.

PubMed record

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ACKNOWLEDGMENT

Ash is not designed to be used in crisis. If you are in crisis, please seek out professional help, or a crisis line. You can find resources at www.findahelpline.com.

Begin your journey

Take the first step today

GET IN TOUCH

support@talktoash.com

press@slingshotai.com

ACKNOWLEDGMENT

Ash is not designed to be used in crisis. If you are in crisis, please seek out professional help, or a crisis line. You can find resources at www.findahelpline.com.

Begin your journey

Take the first step today

GET IN TOUCH

support@talktoash.com

press@slingshotai.com

ACKNOWLEDGMENT

Ash is not designed to be used in crisis. If you are in crisis, please seek out professional help, or a crisis line. You can find resources at www.findahelpline.com.