Mohammad Loni is a Ph.D. student at the School of Innovation, Design, and Engineering at Mälardalen University since October 2017. He received his B.Sc. degree in computer hardware engineering and the M.Sc. degree in computer science from Shiraz University in 2017.
He is a member of the Dependable Platforms for Autonomous Systems and Control (DPAC) and Fast and Sustainable Analysis Techniques for Advanced Real-Time Systems (FAST-ARTS) projects at Mälardalen University.
He had collaboration in domestic industrial projects focusing on FPGA based radar emulators and embedded signal processing.
His research interests are real-time embedded systems, high-throughput FPGA computing, and heterogeneous architectures.
ADONN: Adaptive Design of Optimized Deep Neural Networks for Embedded Systems (Aug 2018) Mohammad Loni, Masoud Daneshtalab, Mikael Sjödin 21st Euromicro Conference on Digital System Design (DSD'18)
A Customized Processing-in-Memory Architecture for Biological Sequence Alignment (Jul 2018) Nasim Akbari , Mehdi Modarressi , Masoud Daneshtalab, Mohammad Loni IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP'18)
Embedded Acceleration of Image Classification Applications for Stereo Vision Systems (Mar 2018) Mohammad Loni, Carl Ahlberg, Masoud Daneshtalab, Mikael Ekström, Mikael Sjödin Design, Automation & Test in Europe Conference & Exhibition (DATE'18)
|DeepMaker: Deep Learning Accelerator on Commercial Programmable Devices||active|
|DPAC - Dependable Platforms for Autonomous systems and Control||active|
|FAST-ARTS: Fast and Sustainable Analysis Techniques for Advanced Real-Time Systems||active|
|A Framework for Testing Redundant Components In Software and Hardware||in progress|