Paula Lago

Current Research

Dr. Lago is an assistant professor in the Department of Electrical and Computer Engineering at Concordia University in Canada. Her research is focused on Pervasive Computing for Health and Healthy Aging. She is a member of the PERFORM Center and engAGE, where she studies ways of understanding and measuring health status and outcomes in ecological and cost-effectives ways by using wearables, sensors at home and machine learning. 

Education

Paula Lago has a Doctorate of Engineering from Universidad de Los Andes, Colombia. She received her Bachelor’s and Master Degree in Software Engineering from the same university.

During her PhD. Dr. Lago studied activity recognition and routine learning at homes from non-invasive sensors embedded in objects like doors, light switches, or electric appliances, at home. The routines are described by their context to account for the fact that people usually change their routines based on context changes like day of the week, weather, presence of visitors, etc. As an invited researcher in the Informatics Laboratory of Grenoble, Paula had the opportunity to live in Amiqual4Home Smart Home to evaluate these ideas.

Dr. Lago was also a postdoctoral researcher at Kyushu Institute of Technology from 2018 to 2020 under the supervision of Prof. Sozo Inoue. There, she worked on a project focused on how to use wearable-sensor-based activity recognition to optimize nurses work at nursing homes, specifically by reducing the time spent in documentation tasks. Her research looked at ways to better use data collected in laboratory settings for activity recognition models used in real-life.

Sensors and Data Streams

Using sensors embedded in objects of smart environments or sensors embedded in wearable devices to understand people's needs or to enable personal awareness and reflection of behavior.

Pattern mining and machine learning for sensor data

Making sense of sensor data by recognizing activities, learning frequent patterns and understanding routines

Healthcare applications

Sensing and analysis brought together to monitor and predict health outcomes

For a full and updated list of publications, see Google Scholar

• N Oishi, D Roggen, P Birch, P Lago (2025) Variability-Aware Data Augmentation for Wearable IMU Using Physics Simulation Activity, Behavior, and Healthcare Computing
• Khaked, A. A., Oishi, N., Roggen, D., & Lago, P. (2025). In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability. Sensors, 25(2), 430.
• S. S. Alia and P. Lago, "Daily Routine Recognition from Longitudinal, Real-Life Wearable Sensor Data for the Elderly," 2024 International Conference on Activity and Behavior Computing (ABC), Oita / Kitakyushu, Japan, 2024, pp. 1-9, doi: 10.1109/ABC61795.2024.10651644.
• Khaked, A. A., Oishi, N., Roggen, D., & Lago, P. (2023, October). Investigating the Effect of Orientation Variability in Deep Learning-based Human Activity Recognition. In Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing (pp. 480-485).
• Cortes‐Cornax, M., Lago, P., & Roncancio, C. (2023). A case study of environmental considerations and opportunities in cyber physical systems. IET Software, 17(4), 424-434.
• Paula Lago, Moe Matsuki, Kohei Adachi, and Sozo Inoue. 2021. Using additional training sensors to improve single-sensor complex activity recognition. 2021 International Symposium on Wearable Computers. Association for Computing Machinery, New York, NY, USA, 18–22.
• Inoue, S., Lago, P., Hossain, T., Mairittha, T., & Mairittha, N. (2019). Integrating Activity Recognition and Nursing Care Records: The System, Deployment, and a Verification Study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3(3), 1-24.
• Paula Lago, Claudia Roncancio, Claudia Jiménez-Guarín. Learning and managing context enriched behavior patterns in smart homes. Future Generation Computer Systems, Volume 91, 2019, Pages 191-205.
• The ContextAct@A4H Real-Life Dataset of Daily-Living Activities

Winter Terms

COEN 6311 - Software Engineering (Graduate Course)
COEN 691 - Pervasive Computing for Healthcare (Graduate course)

Fall Terms

COEN 346 - Operating Systems (Undergraduate)