Narges (Ness) Afsham received her B.Sc. in Telecommunications Engineering and M.Sc. in Biomedical Engineering, in 2007 and 2009 from University of Tehran, Iran. She received her Ph.D. in Electrical and Computer Engineering and Diploma in Engineering Management in 2013 and 2014 from University of British Columbia, Vancouver, Canada. She has performed at various industrial roles focusing on image/signal processing, embedded computer vision, and AI; as a result, she has contributed to three US patent publications since 2015. She has also received the Women In Tech Fellowship from Founder Institute in 2017, Vancouver, Canada. She is currently the Senior AI/Embedded Vision Engineer at Aupera Technologies, Vancouver, Canada and her current R&D interests are edge computing, accelerated AI and embedded video and computer vision applications.
Real time streaming and video-based services require high quality and high speed video transcoding capability. Recently, AI powered applications are booming both in academia and industry to further enhance user experience. Integrating the software-based AI applications within the hardware-based framework of video encoders is a nontrivial task and developing an optimized and efficient solution makes it more challenging. Aupera offers a solution to address this need by building an integrated FPGA-based hardware and development video stack for AI-powered real-time applications.