Masoud Daneshtalab

Masoud Daneshtalab

Mälardalens högskola

H-index: 35

Europe-Sweden

About Masoud Daneshtalab

Masoud Daneshtalab, With an exceptional h-index of 35 and a recent h-index of 22 (since 2020), a distinguished researcher at Mälardalens högskola, specializes in the field of Deep Learning, Heterogeneous Computing, Interconnection Networks.

His recent articles reflect a diverse array of research interests and contributions to the field:

Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators

SAFFIRA: a Framework for Assessing the Reliability of Systolic-Array-Based DNN Accelerators

TrajectoryNAS: A Neural Architecture Search for Trajectory Prediction

AdAM: Adaptive Fault-Tolerant Approximate Multiplier for Edge DNN Accelerators

A systematic literature review on hardware reliability assessment methods for deep neural networks

Supporting end-to-end data propagation delay analysis for TSN-based distributed vehicular embedded systems

DASS: Differentiable Architecture Search for Sparse Neural Networks

Deepaxe: A framework for exploration of approximation and reliability trade-offs in dnn accelerators

Masoud Daneshtalab Information

University

Position

Full Professor Sweden

Citations(all)

4493

Citations(since 2020)

2264

Cited By

2943

hIndex(all)

35

hIndex(since 2020)

22

i10Index(all)

118

i10Index(since 2020)

66

Email

University Profile Page

Mälardalens högskola

Google Scholar

View Google Scholar Profile

Masoud Daneshtalab Skills & Research Interests

Deep Learning

Heterogeneous Computing

Interconnection Networks

Top articles of Masoud Daneshtalab

Title

Journal

Author(s)

Publication Date

Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators

arXiv preprint arXiv:2401.09509

Mahdi Taheri

Natalia Cherezova

Mohammad Saeed Ansari

Maksim Jenihhin

Ali Mahani

...

2024/1/17

SAFFIRA: a Framework for Assessing the Reliability of Systolic-Array-Based DNN Accelerators

Mahdi Taheri

Masoud Daneshtalab

Jaan Raik

Maksim Jenihhin

Salvatore Pappalardo

...

2024/4/3

TrajectoryNAS: A Neural Architecture Search for Trajectory Prediction

arXiv preprint arXiv:2403.11695

Ali Asghar Sharifi

Ali Zoljodi

Masoud Daneshtalab

2024/3/18

AdAM: Adaptive Fault-Tolerant Approximate Multiplier for Edge DNN Accelerators

arXiv preprint arXiv:2403.02936

Mahdi Taheri

Natalia Cherezova

Samira Nazari

Ahsan Rafiq

Ali Azarpeyvand

...

2024/3/5

A systematic literature review on hardware reliability assessment methods for deep neural networks

Mohammad Hasan Ahmadilivani

Mahdi Taheri

Jaan Raik

Masoud Daneshtalab

Maksim Jenihhin

2024/1/22

Supporting end-to-end data propagation delay analysis for TSN-based distributed vehicular embedded systems

Journal of Systems Architecture

Bahar Houtan

Mohammad Ashjaei

Masoud Daneshtalab

Mikael Sjödin

Saad Mubeen

2023/8/1

DASS: Differentiable Architecture Search for Sparse Neural Networks

ACM Transactions on Embedded Computing Systems

Hamid Mousavi

Mohammad Loni

Mina Alibeigi

Masoud Daneshtalab

2023/9/9

Deepaxe: A framework for exploration of approximation and reliability trade-offs in dnn accelerators

Mahdi Taheri

Mohammad Riazati

Mohammad Hasan Ahmadilivani

Maksim Jenihhin

Masoud Daneshtalab

...

2023/4/5

NeuroPIM: Felxible Neural Accelerator for Processing-in-Memory Architectures

Ali Monavari Bidgoli

Sepideh Fattahi

Seyyed Hossein Seyyedaghaei Rezaei

Mehdi Modarressi

Masoud Daneshtalab

2023/5/3

Accurate detection of paroxysmal atrial fibrillation with certified-GAN and neural architecture search

Scientific Reports

Mehdi Asadi

Fatemeh Poursalim

Mohammad Loni

Masoud Daneshtalab

Mikael Sjödin

...

2023/7/14

Evaluating the robustness of ml models to out-of-distribution data through similarity analysis

Joakim Lindén

Håkan Forsberg

Masoud Daneshtalab

Ingemar Söderquist

2023/8/31

Efficient On-device Transfer Learning using Activation Memory Reduction

Amin Yoosefi

Hamid Mousavi

Masoud Daneshtalab

Mehdi Kargahi

2023/9/18

Auto-spmv: Automated optimizing spmv kernels on gpu

arXiv preprint arXiv:2302.05662

Mina Ashoury

Mohammad Loni

Farshad Khunjush

Masoud Daneshtalab

2023/2/11

Appraiser: Dnn fault resilience analysis employing approximation errors

Mahdi Taheri

Mohammad Hasan Ahmadilivani

Maksim Jenihhin

Masoud Daneshtalab

Jaan Raik

2023/5/3

Enhancing Fault Resilience of QNNs by Selective Neuron Splitting

arXiv e-prints

Mohammad Hasan Ahmadilivani

Mahdi Taheri

Jaan Raik

Masoud Daneshtalab

Maksim Jenihhin

2023/6

Analysing Robustness of Tiny Deep Neural Networks

Hamid Mousavi

Ali Zoljodi

Masoud Daneshtalab

2023/8/31

Enabling Energy-Efficient and Low-Latency of Sparse Matrix-Vector Multiplication on GPUs

Mina Ashoury

Mohammad Loni

Farshad Khunjush

Masoud Daneshtalab

2023/11/6

A comprehensive systematic review of integration of time sensitive networking and 5G communication

Zenepe Satka

Mohammad Ashjaei

Hossein Fotouhi

Masoud Daneshtalab

Mikael Sjödin

...

2023/5/1

End-to-end Timing Modeling and Analysis of TSN in Component-Based Vehicular Software

Bahar Houtan

Mehmet Onur Aybek

Mohammad Ashjaei

Masoud Daneshtalab

Mikael Sjödin

...

2023/5/23

FARMUR: Fair Adversarial Retraining to Mitigate Unfairness in Robustness

Seyed Ali Mousavi

Hamid Mousavi

Masoud Daneshtalab

2023/8/28

See List of Professors in Masoud Daneshtalab University(Mälardalens högskola)

Co-Authors

H-index: 51
Axel Jantsch

Axel Jantsch

Technische Universität Wien

H-index: 48
Nader Bagherzadeh

Nader Bagherzadeh

University of California, Irvine

H-index: 42
Juha Plosila

Juha Plosila

Turun yliopisto

H-index: 40
Tapio Pahikkala

Tapio Pahikkala

Turun yliopisto

H-index: 38
Hamid Sarbazi-Azad

Hamid Sarbazi-Azad

Sharif University of Technology

H-index: 37
Hai Zhou

Hai Zhou

Northwestern University

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