Masoud Daneshtalab, Professor
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).
- Many-core Embedded Systems (resource management, scheduling, dark silicon, etc.)
- Interconnection Networks (multicasting, QoS, learning-based and adaptive routing, etc)
- Deep Learning (network architecture design and optimization of CNN, RNN, MLP, and SNN)
- Reconfigurable Architecture (FPGA, DRRA, CGRA, etc.)
- Multi-objective optimization (Ant colony, genetic, Q-learning, ICA, dynamic programming, etc.
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 ( ETFA2021)
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, 110)
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, 110)
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)
Synthesising Schedules to Improve QoS of Best-effort Traffic in TSN Networks (Apr 2021) Bahar Houtan, Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, Saad Mubeen 29th International Conference on Real-Time Networks and Systems (RTNS'21) (RTNS 2021)
Ali Zoljodi
Johan Hjorth
Mohammad Riazati
Amin Majd (former)
Bahar Houtan
Mahdi Taheri
Mohammad Ahmadilivani
Mohammad Loni
Zenepe Satka
| Thesis Title | Status |
|---|---|
| OBJECT RECOGNITION THROUGH DEEP CONVOLUTIONAL LEARNING FOR FPGA | finished |