Masoud Daneshtalab

Publications

Journal / Periodical: IEEE Access
Authors: Rahbari, Dadmehr; Daneshtalab, Masoud; Jenihhin, Maksim
Year: 2025

Projects

Year: 2024 - 2027
Building on TalTech’s expertise in the field of computer engineering and its high-level capacity in the domain of diagnostics and testing of nanoelectronic systems, this project aims at establishing in TalTech, with the strong support of the Advanced Partners, the capacity to R&D&I a complete customised AI-chip design flow. The research ambition of the TAICHIP (TalTech AI-chip) action is a leading-edge forward-thinking R&D framework for reliable and resource-efficient custom AI-chips based on open HW architectures (e.g., RISC-V, NVDLA), open EDA (Electronic Design Automation) tools, methodologies and implementation technologies satisfying the requirements of AI applications of tomorrow. TAICHIP project also allows building at TalTech the necessary scientific knowledge, research skills, administrative and management skills, as well as strengthening its advanced training and education capacity. Evenly related to the central goal are the additional measures that focus on building the supporting capacities, as well as dissemination, exploitation and communication, and public policy focused activities.

Recognitions

Best Paper Award for the paper “Multi-objective Optimization of Real-Time Task Scheduling Problem for Distributed Environments” IEEE 6th Conference on the Engineering of Computer Based Systems (ECBS).
2019
Best Paper Award for the paper “Designing Compact Convolutional Neural Network for Embedded Stereo Vision Systems” IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 2018.
2018
HiPEAC Paper Award for “EbDa: A New Theory on Design and Verification of Deadlock-free Interconnection Networks,” IEEE/ACM International Symposium on Computer Architecture (ISCA),
2017