Masoud Daneshtalab (http://www.idt.mdh.se/~md/) is currently a Professor at Mälardalen University (MDH) and leads the Heterogeneous System research group (www.es.mdh.se/hero/). He joined KTH as European Marie Curie Fellow in 2014. Before that, he was a university lecturer and group leader at University of Turku in Finland from 2012-2014.
He has represented Sweden in the management committee of the EU COST Actions IC1202: Timing Analysis on Code-Level (TACLe). Since 2016 he is in Euromicro board of Director and a member of the HiPEAC network.
His research interests include interconnection networks, hardware/software co-design, deep learning acceleration and evolutionary optimization. He has published 2 book, 8 book chapters, and over 200 refereed international journals and conference papers within H-index 28. He has served in Technical Program Committees of all major conferences in his area including DAC, NOCS, DATE, ASPDAC, ICCAD, HPCC, ReCoSoC, SBCCI, ESTIMedia, VLSI Design, ICA3PP, SOCC, VDAT, DSD, PDP, ICESS, Norchip, MCSoC, CADS, EUC, DTIS, NESEA, CASEMANS, NoCArc, MES, PACBB, MobileHealth, and JEC-ECC.
He has co-led several research projects including: SafeDeep, AutoDeep, DeepMaker, DESTINE, PROVIDENT, HERO, AGENT, CUBRIC, ERoT, and µBrain with a total estimation of 114 MSEK (11 MEuro).
A Comprehensive Systematic Review of Integration of Time Sensitive Networking and 5G Communication (Jun 2023) Zenepe Satka, Mohammad Ashjaei, Hossein Fotouhi, Masoud Daneshtalab, Mikael Sjödin, Saad Mubeen Journal of Systems Architecture, 2023 (JSA)
Investigating and Analyzing CAN-to-TSN Gateway Forwarding Techniques (May 2023) Aldin Berisa, Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, Saad Mubeen 2023 IEEE 25th International Symposium on Real Time Distributed Computing (ISORC) (ISORC'23)
End-to-end Timing Modeling and Analysis of TSN in Component-Based Vehicular Software (May 2023) Bahar Houtan, Mehmet Onur Aybek , Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, John Lundbäck , Saad Mubeen 2023 IEEE 25th International Symposium on Real Time Distributed Computing (ISORC) (ISORC'23)
NeuroPIM: Flexible Neural Accelerator for Processing-in-Memory Architectures (May 2023) Ali Monavari , Sepideh Fattahi , Mehdi Modarressi , Masoud Daneshtalab International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)
APPRAISER: DNN Fault Resilience Analysis Employing Approximation Errors (May 2023) Mahdi Taheri , Mohammad Ahmadilivani , Maksim Jenihhin , Masoud Daneshtalab, Jaan Raik International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)
RELIANT Industrial graduate school @ MDU (Mar 2023) Kristina Lundqvist, Baran Çürüklü, Elisabeth Uhlemann, Mikael Sjödin, Marjan Sirjani, Cristina Seceleanu, Tiberiu Seceleanu, Malin Rosqvist, Saad Mubeen, Kaj Hänninen, Håkan Forsberg, Mikael Ekström, Masoud Daneshtalab, Federico Ciccozzi
|PROVIDENT: Predictable Software Development in Connected Vehicles Utilising Blended TSN-5G Networks||active|
|AutoDeep: Automatic Design of Safe, High-Performance and Compact Deep Learning Models for Autonomous Vehicles||active|
|AVANS - civilingenjörsprogrammet i tillförlitliga flyg- och rymdsystem||finished|
|DeepMaker: Deep Learning Accelerator on Commercial Programmable Devices||finished|
|Dependable AI in Safe Autonomous Systems||active|
|DESTINE: Developing Predictable Vehicle Software Utilizing Time Sensitive Networking||active|
|DPAC - Dependable Platforms for Autonomous systems and Control||active|
|Energy-Efficient Hardware Accelerator for Embedded Deep Learning||finished|
|FAST-ARTS: Fast and Sustainable Analysis Techniques for Advanced Real-Time Systems||finished|
|FASTER-ΑΙ: Fully Autonomous Safety- and Time-critical Embedded Realization of Artificial Intelligence||active|
|GreenDL: Green Deep Learning for Edge Devices||active|
|HERO: Heterogeneous systems - software-hardware integration||active|
|INTERCONNECT: Integrated Time Sensitive Networking and Legacy Communications in Predictable Vehicle-platforms||active|
|RELIANT Industrial graduate school: Reliable, Safe and Secure Intelligent Autonomous Systems||active|
|SafeDeep: Dependable Deep Learning for Safety-Critical Airborne Embedded Systems||active|
Amin Majd (former)
Mohammad Loni (former)
|OBJECT RECOGNITION THROUGH DEEP CONVOLUTIONAL LEARNING FOR FPGA||finished|