Computational Wellbeing Group

@Rice University

We are recruiting participants for the following studies!

Productivity Study: Join our study!

Missions

• Design computational tools, and human centered and/or data driven technologies for measuring and improving health and wellbeing.

• Understand relationships between human behaviors and physiology with health and wellbeing through human data modeling and analytics.

We are a highly interdisciplinary team: data science, machine learning, behavioral science, mobile and ubiquitous computing, physics and human computer interaction. We study non-clinical populations (e.g., college students, office workers) as well as clinical populations (e.g. patients with depression, schizophrenia, substance use disorders, Alzheimer, cancers ) in collaboration with researchers in psychology, psychiatry, sleep and circadian disorders, engineering and behavioral science. We are a part of Rice Scalable Health Labs.

News

[October, 2021] New paper at IEEE EMBC 2021.

Ethan N Lyon , Luis H Victor, Akane Sano, "Health Label and Behavioral Feature Prediction Using Bayesian Hierarchical Vector Autoregression Models", International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBC), 2021. [pdf]

[September, 2021] New paper at International Conference on Affective Computing & Intelligent Interaction (ACII 2021) .

Han Yu, Thomas Vaessen, Inez Myin-Germeys, Akane Sano, "Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the Wild", Accepted to 9th International Conference on Affective Computing & Intelligent Interaction (ACII 2021) [arxiv] [code]

[July, 2021] New Journal paper at ACM Transactions on Computing for Healthcare .

C. Wan, A. W. McHill, E. Klerman, A. Sano. "Sensor-based estimation of dim light melatonin onset (DLMO) using features of two time scales". ACM Transactions on Computing for Healthcare Vol. 2, No. 3. [ACM URL] [arxiv]

[March, 2021] Our clinical trial protol paper at JMIR protocol

A. Ito-Masui, E. Kawamoto, R. Sakamoto, H. Yu, A. Sano, E. Motomura, H. Tanii, S. Sakano, R. Esumi, H. Imai, M. Shimaoka, "Internet-based Individualized Cognitive Behavioral Therapy for Shift Work Sleep Disorder (Empowered by Wellbeing Prediction): A Pilot Study Protocol", JMIR Protocol, Vol 10, No 3 (2021): March, [JMIR URL].

[November, 2020] We presented two papers at MobiHealth 2020.

"Forecasting Health and Wellbeing for Shift Workers Using Job-role Based Deep Neural Network" (Han Yu et al.) [PDF]

"Patient-independent Schizophrenia Relapse Prediction Using Mobile Sensor based Daily Behavioral Rhythm Changes" (Bishal Lamichhane et al.) [PDF]

[October, 2020] We received an NIH grant to measure physical and mental health risks and develop a personalized advice system for dementia spousal caregivers to accomplish everyday tasks and boost their mental health while safely distancing in collaboration with Dr. Chris Fagundes's team at Rice Psychology. [Link]

[September, 2020] New paper "Using Behavioral Rhythms and Multi-task Learning to Predict Fine Grained Symptoms of Schizophrenia" in Scientific Reports, [PDF].

[September, 2020] Our IMWUT paper "Extraction and Interpretation of Deep Autoencoder-based Temporal Features from Wearables for Forecasting Personalized Mood, Health, and Stress" was presented at Ubicomp 2020. [PDF] [video].

[July, 2020] Our team received Microsoft pandemic preparedness award for “Design and Evaluation of Intelligent Agent Prototypes for Assistance with COVID-19 work and lifestyle disruptions.” in collaboration with Drs. Fred Oswald (Rice) and Nidal Moukaddam (Baylor College of Medicine) [link]

[June, 2020] New papers in ACM IMWUT and IEEE EMBC 2020.

B. Li, A. Sano, "Extraction and Interpretation of Deep Autoencoder-based Temporal Features from Wearables for Forecasting Personalized Mood, Health, and Stress", Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, [ACM].

H. Yu, A, Sano, "Passive Sensor Data Based Future Mood, Health and Stress Prediction: User Adaption Using Deep Learning", International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020, [PDF].

L.H. Victor, A. Sano, "Frequency-Dependent Light Stimulation Effects on Performance During Vigilance Tasks on a Laptop", International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020, [PDF].

B. Li, A. Sano, "Early versus Late Modality Fusion of Deep Features from Wearable Sensors for Personalized Prediction of Feature Wellbing", International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020, [PDF].

T. Umematsu, A. Sano, S. Taylor, M. Tsujikawa, R.W. Picard, "Forecasting Stress, Mood, and Health from Daytime Physiology in Office Workers and Students", International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020, [PDF].


[Feb, 2020] Our team received Microsoft Productivity Research Collaboration grant "Unobtrusive Personalized Work Engagement Assistant" in collaboration with Drs. Ashok Veeraraghavan(Rice) and Fred Oswald (Rice) [link]

[Nov, 2019] We received Rice University Institute of Biosciences and Bioengineering: Hamill Innovation Awards: CraveSupport: Measuring and Intervening Craving Moments in Substance Use Disorders (SUD) using Bio-behavioral Sensor (in collaboration with Drs. Ashutosh Sabharwal (Rice), Nidal Moukaddam, Ramiro Salas (Baylor College of Medicine)).


[Nov, 2019] We received AMED funding (Japan agency for medical research and development) "Sleep and wellbeing recommendation system for shift workers" in collaboration with Mie University.

[Sept, 2019] We presented "Toward End-to-end Prediction of Future Wellbeing using Deep Sensor Representation Learning" at International Conference on Affective Computing and Intelligent Interaction (ACII) workshop, Machine Learning for the Diagnosis and Treatment of Affective Disorders (ML4AD).


[June, 2019] Luis got NSF NRT Bioelectronics Fellowship. Congratulations!

[May, 2019] Best Paper Award at IEEE Biomedical Health Informatics 2019 in Chicago.

[May, 2019] Our team received Rice University’s InterDisciplinary Excellence Awards to start a new project Fostering Positive Emotions and Psycho-Physio Resilience in Job Seekers and Beyond with Profs. King and Denny at Department of Psychological Sciences.

[April, 2019] Our team received Rice University’s Faculty Initiatives Fund to start a new project CityHealth: Measuring Mental Wellbeing of Houston to Empower City-scale Emotional Resilience and Preparedness for Adverse Weather Events.

[April, 2019] Han Yu got 2019 IBB Edgar O’Rear and Mary F.D. Morse Travel Award. Congrats!

[March, 2019] Our papers: "Personalized Wellbeing Prediction using Behavioral, Physiological and Weather Data" and "Improving Students' Daily Life Stress Forecasting using LSTM Neural Networks" are accepted to present at IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI’19) in May 2019


[March, 2019] Organize a Method session "Mobile and ubiquitous emotion sensing" at 2019 Society of Affective Science annual conference

[January, 2019] Do Workplace Wellness Programs Really Work?, MIT Sloan Management Review, 1/2019

If you are interested in joining our group,

[Prospective Students] Please check admission websites at Rice ECE or CS depending on your background and include Prof. Sano's name and your interest in your research statement.

[Rice undergrad/grad Students] Please email Prof. Sano with your interest and resume.

[Post-docs] Please email Prof. Sano with your interest and CV.

Rice has a postdoc fellowship program for highly competitive applicants which offer substantial independence.

The Rice Academy of Fellows provides a $60,000 salary for 2 years for a cohort of postdoctoral scholars in departments across campus. Applications are due the beginning of January every year.