A. Sano

Latest

• Multimodal Autoencoder: A Deep Learning Approach to Filling in Missing Sensor Data and Enabling Better Mood Prediction
• Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health
• Predicting Tomorrow’s Mood, Health, and Stress Level using Personalized Multitask Learning and Domain Adaptation
• Machine Learning of Sleep and Wake Behaviors to Classify Self-Reported Evening Mood
• Automatic identification of artifacts in Electrodermal Activity data
• Multi-task Multi-Kernel Learning for Estimating Individual Wellbeing
• Predicting students' happiness from physiology, phone, mobility, and behavioral data
• Prediction of happy-sad mood from daily behaviors and previous sleep history
• Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors and mobile phones
• Wavelet-based motion artifact removal for Electrodermal Activity