| 2022 | ACSSC | Topological Knowledge Distillation for Wearable Sensor Data. | Eun Som Jeon, Hongjun Choi, Ankita Shukla, Yuan Wang, Matthew P. Buman, Pavan K. Turaga |
| 2022 | BSN | Multimodal Time-Series Activity Forecasting for Adaptive Lifestyle Intervention Design. | Abdullah Mamun, Krista S. Leonard, Matthew P. Buman, Hassan Ghasemzadeh |
| 2020 | CVPR | PI-Net: A Deep Learning Approach to Extract Topological Persistence Images. | Anirudh Som, Hongjun Choi, Karthikeyan Natesan Ramamurthy, Matthew P. Buman, Pavan K. Turaga |
| 2018 | CVPR | Temporal Alignment Improves Feature Quality: An Experiment on Activity Recognition With Accelerometer Data. | Hongjun Choi, Qiao Wang, Meynard John Toledo, Pavan K. Turaga, Matthew P. Buman, Anuj Srivastava |
| 2017 | CHI | Self-Experimentation for Behavior Change: Design and Formative Evaluation of Two Approaches. | Jisoo Lee, Erin Walker, Winslow Burleson, Matthew Kay, Matthew P. Buman, Eric B. Hekler |
| 2016 | BSN | Learning approach for classification of GENEActiv accelerometer data for unique activity identification. | Arindam Dutta, Owen Ma, Matthew P. Buman, Daniel W. Bliss |
| 2016 | ICMLA | Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data. | Arindam Dutta, Owen Ma, Meynard John Toledo, Matthew P. Buman, Daniel W. Bliss |
| 2016 | ICMLA | A Hierarchical Meta-Classifier for Human Activity Recognition. | Anzah H. Niazi, Delaram Yazdansepas, Jennifer L. Gay, Frederick W. Maier, Lakshmish Ramaswamy, Khaled Rasheed, Matthew P. Buman |
| 2013 | CHI | Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research. | Eric B. Hekler, Predrag V. Klasnja, Jon Froehlich, Matthew P. Buman |