address: CODA, 756 W Peachtree St NW, Atlanta, GA 30308
We are the Computational Behavior Analysis (CBA) research lab at Georgia Institute of Technology.
Our research agenda focuses on applied machine learning, that is developing systems and innovative sensor data analysis methods for real world applications. Primary application domain for our work is computational behavior analysis where we develop methods for automated and objective behavior assessments in naturalistic environments. Main driving functions for our work are “in the wild” deployments and as such the development of systems and methods that have a real impact on peoples’ lives.
ISWCGenerating Virtual On-Body Accelerometer Data from Virtual Textual Descriptions for Human Activity RecognitionIn Proceedings of the 2023 ACM International Symposium on Wearable Computers 2023
PercomIf only we had more data!: Sensor-Based Human Activity Recognition in Challenging ScenariosIn 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) 2023
IMWUTBootstrapping Human Activity Recognition Systems for Smart Homes from ScratchProc. ACM Interact. Mob. Wearable Ubiquitous Technol. Sep 2022
IMWUTAssessing the State of Self-Supervised Human Activity Recognition Using WearablesProc. ACM Interact. Mob. Wearable Ubiquitous Technol. Sep 2022
ACMApplying machine learning for sensor data analysis in interactive systems: Common pitfalls of pragmatic use and ways to avoid themACM Computing Surveys (CSUR) Sep 2021
ACMIMUTube: Automatic extraction of virtual on-body accelerometry from video for human activity recognitionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Sep 2020