Research Scientist, Human Sleep Research Program, Center for Health Sciences
Massimiliano de Zambotti, Ph.D., joined SRI International in 2012 and is currently leading the Translational Sleep Technology Unit of the Human Sleep Research Program. His work focuses on the interactions between the autonomic and central nervous systems in different psychophysiological states (e.g., sleep and wake state, menstrual cycle phases and reproductive hormonal environments), in clinical and non-clinical populations (e.g., insomnia disorder, alcohol use disorder). De Zambotti is devoted to the mission of advancing science, discovering and developing novel approaches and technologies to improve people’s health and well-being.
His expertise is in the areas of normal and pathologic sleep, sleep technology development and testing, autonomic nervous system regulation during sleep and interactions between sleep, autonomic and endocrine systems, menopause, hot flashes and wearable technology. de Zambotti leads validation studies of wearable technologies in the sleep space and the development of novel technologies such as non-pharmacological wearable devices to monitor sleep and bio-signals and improve sleep quality.
de Zambotti is also co-founder and chief scientific officer of digital health platform and SRI spin-out Lisa Health, which utilizes AI and wearable technology to transform the menopause and healthy aging journey. He has investigated and developed novel technology for menopause, including automatic detection and prediction of hot flashes in menopausal women, sleep disturbance associated with hot flashes, and immersive meditation as a novel evidence-based intervention for various menopause symptoms.
He is currently PI on two NIH-funded projects, one about sleep and cardiovascular health in adolescents (R01 HL139652), and the other about alcohol, sleep, and autonomic nervous system function in adults (R21 AA024841).
de Zambotti has published more than 40 international peer-reviewed papers. He obtained a MSc in experimental psychology and cognitive-behavioral neurosciences in 2007 and a Ph.D. in psychological sciences (biological psychology) in 2011, from the University of Padua, Italy.
Recent publicationsmore +
Evaluation of a device-agnostic approach to predict sleep from raw accelerometry data collected by Apple Watch Series 7, Garmin Vivoactive 4, and ActiGraph GT9X Link in children with sleep disruptions
This study demonstrates that raw acceleration data from consumer wearable devices has the potential to be harnessed to predict sleep in children.
Effects of emerging alcohol use on developmental trajectories of functional sleep measures in adolescents
We tracked developmental changes in polysomnographic (PSG) and electroencephalographic (EEG) sleep measures and their relationship with emergent alcohol use in adolescents considering confounding effects (e.g., cannabis use).
Association of Demographic and Socioeconomic Indicators With the Use of Wearable Devices Among Children
We examined whether demographic and socioeconomic indicators are associated with willingness to join a wearable device study and adherence to wearable data collection in children.
This study examined changes in sleep habits and recreational screen time (social media, video gaming), and their relationship, before and across the first year of the pandemic in adolescents in the Adolescent Brain Cognitive Development (ABCD) Study.
We sought to elucidate the interaction between sleep and mood considering menstrual cycle phase in 72 healthy young women with natural, regular menstrual cycles and without menstrual-associated disorders.
Morning perception of sleep, stress, and mood, and its relationship with overnight physiological sleep: findings from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study
This cross-sectional study investigated objective–subjective sleep discrepancies and the physiological basis for morning perceptions of sleep, mood, and readiness, in adolescents.