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.
Supporting End-to-end Data-propagation Delay Analysis for TSN Networks (Nov 2021) Bahar Houtan, Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, Saad Mubeen MRTC Report, Mälardalen Real-Time Research Centre (MRTC 2021)
FastStereoNet: A Fast Neural Architecture Search for Improving the Inference of Disparity Estimation on Resource-Limited Platforms (Oct 2021) Mohammad Loni, Ali Zoljodi, Amin Majd , Byung Hoon Ahn , Masoud Daneshtalab, Mikael Sjödin, Hadi Esmaeilzadeh IEEE Transactions on Systems, Man, and Cybernetics: Systems (SMCS)
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)
Ali Zoljodi
Johan Hjorth
Mohammad Riazati
Aldin Berisa
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 |