Fateme Akbari
PhD Student
ACADEMIC AREA
Information Systems
AREAS OF EXPERTISE
Health Informatics, Machine Learning, Anomaly Detection
SUPERVISOR(S)
Dr. Kamran Sartipi and Dr. Norm Archer
EMAIL
akbarif@mcmaster.ca
Biography
Fateme Akbari is a fourth-year Ph.D. candidate in Information Systems at the DeGroote School of Business, McMaster University. Her current research focus is on the application of machine learning in the field of Health Informatics, with a particular emphasis on mining sensor data streams for detecting behavior abnormalities. Using cutting-edge sequential approaches, she is currently conducting behavior anomaly detection research for older adults living in smart homes equipped with ambient sensors.
Fateme has published papers in peer-reviewed journals and conferences including “ACM Transactions of Computing for Healthcare” (Link to her Google Scholar). She also has presented her research in academic talks at Mayo Clinic, Duke Center for Health Informatics, MIRA (AURA), etc.
Publications
Akbari, F., Sartipi, K., and Archer, N. 2022. “Synthetic Behavior Sequence Generation using Generative Adversarial Networks,” ACM Transactions on Computing for Healthcare. (https://dl.acm.org/doi/10.1145/3563950)
Akbari, F. and Sartipi, K. 2022, “A Transformer-based Model for Older Adult Behavior Change Detection”, The Tenth IEEE International Conference on Healthcare Informatics.
Akbari, F., Saberi, M., and Hussain, O.K., 2020. “Social network structure-based framework for innovation evaluation and propagation for new product development”, Service Oriented Computing and Applications, pp.1-13.
F. Akbari and F. Taghiyareh 2014, “E-SoRS: A Personalized and Social recommender Service for E-learning Environments“, Fifth International Conference on E-Learning and E-Teaching (ICELET).