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).
Curating Datasets for Visual Runway Detection (Oct 2021) Joakim Lindén , Håkan Forsberg, Josef Haddad , Emil Tagebrand , Erasmus Cedernaes , Emil Gustafsson Ek , Masoud Daneshtalab The 40th Digital Avionics Systems Conference (DASC'2021)
Schedulability Analysis of Best-Effort Traffic in TSN Networks (Sep 2021) Bahar Houtan, Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, Sara Afshar, Saad Mubeen 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021)
Time-Sensitive Networking in Automotive Embedded Systems: State of the Art and Research Opportunities (Sep 2021) Mohammad Ashjaei, Lucia Lo Bello , Masoud Daneshtalab, Gaetano Patti , Sergio Saponara , Saad Mubeen Journal of Systems Architecture, 2021 (JSA)
Guest Editorial: Special Issue on Parallel, Distributed, and Network-Based Processing in Next-generation Embedded Systems (Aug 2021) Saad Mubeen, Lucia Lo Bello , Masoud Daneshtalab, Sergio Saponara Journal of Systems Architecture, 2021 (JSA)
RoCo-NAS: Robust and Compact Neural Architecture Search (Jul 2021) Vahid Geraeinejad , Sima Sinaei, Mehdi Modarressi , Masoud Daneshtalab the international joint conference on neural networks (IJCNN)
ELC-ECG: Efficient LSTM Cell for ECG Classification based on Quantized Architecture (May 2021) Seyed Ahmad Mirsalari , Najmeh Nazari , Sima Sinaei, Mostafa Salehi , Masoud Daneshtalab IEEE International Symposium on Circuits & Systems (ISCAS)
|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|
|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||active|
|HERO: Heterogeneous systems - software-hardware integration||active|
|INTERCONNECT: Integrated Time Sensitive Networking and Legacy Communications in Predictable Vehicle-platforms||active|
|SafeDeep: Dependable Deep Learning for Safety-Critical Airborne Embedded Systems||active|
|OBJECT RECOGNITION THROUGH DEEP CONVOLUTIONAL LEARNING FOR FPGA||finished|