Akane Sano

Akane Sano is an Assistant Professor at Rice University, Department of Electrical Computer Engineering and Computer Science.
She directs Computational Wellbeing Group. Her research focuses on human sensing, data analysis and application development for health and wellbeing. She is a member of Scalable Health Labs.

She has been working on developing technologies to measure, forecast, understand and improve health and wellbeing. She has worked on measuring and predicting stress, mental health, sleep and performance and designing systems to help people to reduce their stress and improve their mental health, sleep and performance for student and employee populations including NSF future of work project: embodied cognitive assistant for shift workers, NIH funded SNAPSHOT study project, Eureka project (symptom prediction and digital phenotyping in schizopherenia using phone data) and IARPA mPerf project (Using mobile sensors to support productivity and employee well-being).

She obtained her PhD at MIT Media Lab, and her MEng and BEng at Keio University, Japan. Before she joined Rice University, she was a Research Scientist in Affective Computing Group at MIT Media Lab, and a visiting scientist/lecturer at People-Aware Computing Lab, Cornell University.

Before she came to the US, she was a researcher/engineer at Sony Corporation and worked on wearable computing, intelligent systems and human computer interaction.

Upcoming conferences/events

2019 Sept: ACII 2019 in UK, Cambridge & Ubicomp 2019 in UK, London
2019 Aug: Technology Collaboration Center: Data Analytics Workshop, Rice University
2019 June: 19th Brazilian Symposium on Applied Computing Health in Rio, Brazil
2019 May: Deep Learning in Healthcare Summit in Boston
2019 May: IEEE BHI/BSN in Chicago
2019 Apr: NSF Future of Work PI meeting
2019 Mar: Society of Affective Science in Boston
2019 Feb: Life Sensing Consortium meeting at UT Austin

Recent Talks

2019 March: Rice University ECE Corporate Affiliates Day "Embodied intelligent assistant to enhance wellbeing and cognitive performance".
2018 Dec: Mobile Data 2 Knowledge (MD2K) webinar "Predicting mental health and mesaruing sleep using machine learning and wearable sensors/mobile phones"
2018 Oct: Rice University Data Science Conference "Human Sensing & Data Analysis: Modeling for Health, Well-being & Performance".


[September, 2019] Abstract at The Frontier of AI-Assisted Care Scientific Symposium, 2019 September: V. W. Tseng, A. Sano, T. Choudhury, Developing Clinically Interpretable Machine Learning Models to Predict Fine-Grained Symptom Trajectory of Schizophrenia and Identify Patients At Risk"

[August, 2019] Joining the Technical Program Committee for MobiCom 2020

[July, 2019] New Paper: Toward End-to-end Prediction of Future Wellbeing using Deep Sensor Representation Learning in ACII 2019 ML4AD workshop

[July, 2019] New Paper: Daytime Data and LSTM Can Forecast Tomorrow's Stress, Health, and Happiness in IEEE EMBC 2019

[May, 2019] Best Paper Award at IEEE Biomedical Health Informatics (BHI) 2019 in Chicago. Improving students daily life stress forecasting using lstm neural networks

[May, 2019] Joining a panel session "The Impacts of Machine Learning in Mental Health Care" at Deep Learning in Healthcare Summit in Boston in May, 2019.

[May, 2019] We obtained Creative Ventures Fund: InterDisciplinary Excellence Awards (IDEA) with Profs. King and Denny at Rice Psychology department for our new project "Fostering Positive Emotions and Psycho-Physio Resilience in Job Seekers and Beyond".

[May, 2019] Co-organizing a workshop Mental Health: Sensing & Intervention at Ubicomp 2019 in London, UK. Paper submission deadline: July 1th, 2019

[April, 2019] Co-organizing a workshop Machine Learning for the Diagnosis and Treatment of Affective Disorders (ML4AD) at ACII 2019 in Cambridge, UK. Paper submission deadline: June 21, 2019

[April, 2019] Our team obtained creative venture Faculty Initiative fund to support our new project "CityHealth: Measuring Mental Wellbeing of Houston to Empower City-scale Emotional Resilience and Preparedness for Adverse Weather Events"

[March, 2019] Two papers will be presented at IEEE BHI 2019 conferece in Chicago in May.

[March, 2019] Our computational wellbeing website has launched

[March, 2019] 2019 Society of Affective Science annual conference for Method lunch session "Mobile and ubiquitous emotion sensing"

[Dec, 2018] MD2K webinar on Dec 6 "Human Sensing and Data analysis/modeling for Health, Wellbeing and Performance"

[Nov, 2018] NSF Press Release NSF announces awards to shape the human-technology partnership for the well-being of workers and their productivity
Rice Press Release Enhancing cognitive abilities for healthier work
Nature News Article about our research Happy with a 20% chance of sadness

[Oct, 2018] Rice Data Science Conference

[Sept, 2018] New paper: Multimodal Ambulatory Sleep Detection Using LSTM Recurrent Neural Networks was published in IEEE Journal of Biomedical Health Informatics (IEEE JBHI).

[August, 2018] Teaching "Human sensing, analysis and applications" this semester.

Very excited to receive a NSF grant "Future of Work at the Human-Technology Frontier: Advancing Cognitive and Physycal Capabilities".
We develop "an Embodied Intelligent Cognitive Assistant to Enhance Cognitive Performance of Shift Workers" and people with social jetlag as well as their wellbeing.
This is a 3-year collaborative project with UMass Amherst, Cornell University, Harvard Medical School, Baylor College of Medicine and Microsoft Research.

Co-organizing Workshops: Modeling Cognitive Processes from Multimodal Data at ICMI 2018 in Denver and Mental Health: Sensing & Intervention at Ubicomp 2018 in Singapore

[July, 2018] Presentation at IEEE EMBC 2018 Minisymposia "Sensor-based behavioral informatics: advances in understanding of human behavior"in Hawaii.

[June, 2018] Presentation at Gordon Research Seminar: Advanced Health Informatics, Emerging Perspectives in Health Informatics from Wearable Sensing to Big Data in Hong Kong

[June, 2018] Presentation at NIH 2018 mHealth Technology Showcase

[April, 2018] Our paper about SNAPSHOT study and machine learning models to detect stress and mental health conditions and identify underlying related physiological and modifiable behavioral markers will be published at Journal of Medical Internet Research

[February, 2018] Our paper about N=1 experiment platform was published in Sensors: the Special Issue "QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform"

[January, 2018] Teaching Ubiquitous Computing class this semester at Cornell!

[November, 2017] A paper about a system that enables users to conduct N=1 study (self experimentation) "QuantifyMe: An Automated Single-Case Experimental Design Platform" was presented at MobiHealth 2017.

[October, 2017] Papers about micro-stress intervention delivery timing, stress analysis using toungue images and filling missing data with auto-encoder were presented at ACII 2017.

Prospective Students

Please check admission websites at Rice ECE and CS depending on your background and mention my name and your interest in your research statement!

Prospective Post-docs

Please email me 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 for the 2019 cycle are due on January 3, 2019.

Contact Information


6100 Main Street, Houston, TX, 77098, USA


akane.sano at rice.edu
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