Mohamad Sadegh Monfared received his B.Sc. in Electrical Engineering - Electronics Technology at the Sadjad University of Technology in 2013 and his M.Sc. in Electrical Engineering - Electronics at the Ferdowsi University of Mashhad (FUM), Iran, in 2017. He worked in the Advanced Computer Architecture Laboratory (ACAL) at FUM on communication protocols as well as digital system designs. In 2019, he started his PhD work in the Biomedical Microsystems Lab at Laval University. His main research focused on wireless implantable micro systems, VLSI design, FPGAs, artificial intelligence/machine learning. After his Master research, he presented a paper in IEEE ICCKE conference in 2019.
Project : Efficient Implementation of Neural Network built on FPGAs for biological systems applications
Entire our environment, Machine Learning applications are growing extremely and becoming one of the important subjects. There are many applications such as brain–machine interfaces, computer vision, financial market analysis, handwriting and face recognition, machine translation, neural networks, speech recognition, and etc. which are going to revolutionise our society. This project aims to develop and optimise machine-learning application for neural networks on FPGAs in biological systems. FPGAs have been chosen for implementing the neural networks for the project since they can control different algorithms in parallel in one device.