| Personalized Human Activity Recognition using Wearables: A Manifold Learning-based Knowledge Transfer R Saeedi, K Sasani, S Norgaard, AH Gebremedhin | 10 | 2018 |
| Synthetic Sensor Data Generation for Health Applications: A Supervised Deep Learning Approach S Norgaard, R Saeedi, K Sasani, AH Gebremedhin | 9 | 2018 |
| Co-MEAL: Cost-optimal multi-expert active learning architecture for mobile health monitoring R Saeedi, K Sasani, AH Gebremedhin Proceedings of the 8th ACM International Conference on Bioinformatics …, 2017 | 8 | 2017 |
| Beams: bounded event detection in graph streams MH Namaki, K Sasani, Y Wu, T Ge 2017 IEEE 33rd International Conference on Data Engineering (ICDE), 1387-1388, 2017 | 8 | 2017 |
| Gait speed and survival of older surgical patient with cancer: prediction after machine learning K Sasani, HN Catanese, A Ghods, SA Rokni, H Ghasemzadeh, ... Journal of geriatric oncology 10 (1), 120-125, 2019 | 7 | 2019 |
| Performance Prediction for Graph Queries MH Namaki, K Sasani, Y Wu, AH Gebremedhin Proceedings of the 2nd International Workshop on Network Data Analytics, 9, 2017 | 5 | 2017 |
| Multi-metric graph query performance prediction K Sasani, MH Namaki, Y Wu, AH Gebremedhin International Conference on Database Systems for Advanced Applications, 289-306, 2018 | 2 | 2018 |
| Collaborative Multi-Expert Active Learning for Mobile Health Monitoring: Architecture, Algorithms, and Evaluation R Saeedi, K Sasani, AH Gebremedhin Sensors 20 (7), 1932, 2020 | | 2020 |
| Machine Learning for Predicting Performance of Graph Algorithms in Graph Databases and Network Similarity K Sasani Washington State University, 2018 | | 2018 |
| Network Similarity Prediction in Time-evolving Graphs: A Machine Learning Approach K Sasani, MH Namaki, AH Gebremedhin | | 2018 |
Assefaw GebremedhinWashington State University, School of EECSVahvistettu sähköpostiosoite verkkotunnuksessa eecs.wsu.edu
