Dr. Akram Bayat is a postdoctoral associate at The MIT Media lab advised by Dr. Pratik Shah. Akram received her PhD in Computer Science from University of Massachusetts Boston in 2018. During her Ph.D. research, she worked on developing machine learning algorithms for solving real-world problems and conducted experimental studies for modeling of human physical and behavioral characteristics using data from sensors, wearables and mobile phones. Akram has significant expertise in applying deep learning for computer vision applications such as improving performance of deep object and scene recognition networks using mechanisms of human visual perceptions. Her research has been published in leading computer science conferences and journals and won numerous awards. In 2017, she won best student paper award out of 600 papers at AHFE2017 for her novel algorithm for building a robust identification method based on human eye-movement data during reading activity. Her publication on human activity recognition from mobile phone sensory data is one of the most cited papers in Procedia Computer Science. Akram was invited speaker at MIT Center for Brains, Minds & Machines (2017) and Deep Learning summit in Boston (2019) and was winner of Randall Malbone Scholarship award at the University of Massachusetts Boston (2018). She has also received several fellowships and travel grants from Woman in Computer Vision at CVPR 2018 and CRA-W Grad Cohort Workshop 2017, as well as two GSA grants from UMass Boston.