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Electronics and Electrical Engineering
UAE
2025

D-Index & Metrics

Computer Science

D-Index
54
Citations
11852
World Ranking
4556
National Ranking
24

Electronics and Electrical Engineering

D-Index
57
Citations
12727
World Ranking
1962
National Ranking
11

Research.com Recognitions

  • 2025 - Research.com Electronics and Electrical Engineering in United Arab Emirates Leader Award

Overview

Muhammad Shafique is affiliated with New York University Abu Dhabi, located in the United Arab Emirates. Their research spans several core areas within computer science and engineering, emphasizing both theoretical and applied aspects of advanced computing technologies.

The primary fields of study covered by Muhammad Shafique include:

  • Computer Science
  • Engineering

Within these broader fields, their subfields of study focus on:

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Computer Networks and Communications

The main topics addressed in their work involve:

  • Advanced Memory and Neural Computing
  • Adversarial Robustness in Machine Learning
  • Ferroelectric and Negative Capacitance Devices
  • Advanced Neural Network Applications
  • Quantum Computing Algorithms and Architecture
  • Anomaly Detection Techniques and Applications
  • Physical Unclonable Functions (PUFs) and Hardware Security

They have published extensively in various venues. Among the most frequent publication venues are:

  • arXiv (Cornell University)
  • IEEE Access
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • ACM Transactions on Embedded Computing Systems
  • Microprocessors and Microsystems

Frequent coauthors in Muhammad Shafique's collaborations include:

  • Alberto Marchisio
  • Muhammad Abdullah Hanif
  • Rachmad Vidya Wicaksana Putra
  • Maurizio Martina
  • Nouhaila Innan

Their recent papers highlight a focus on both hardware and software aspects of deep learning acceleration, as well as energy management in smart grids. Representative publications include:

  • "Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead" (2020), IEEE Access
  • "An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks" (2020), Future Internet
  • "A Systematic Review Towards Integrative Energy Management of Smart Grids and Urban Energy Systems" (2023), Renewable and Sustainable Energy Reviews
  • "High-Performance Accurate and Approximate Multipliers for FPGA-Based Hardware Accelerators" (2021), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • "A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends" (2024), IEEE Access

Best Publications

  • Mapping on multi/many-core systems: survey of current and emerging trends

    Amit Kumar Singh;Muhammad Shafique;Akash Kumar;Jorg Henkel

  • A low latency generic accuracy configurable adder

    Muhammad Shafique;Waqas Ahmad;Rehan Hafiz;Jorg Henkel

  • Reliable on-chip systems in the nano-era: lessons learnt and future trends

    Jorg Henkel;Lars Bauer;Nikil Dutt;Puneet Gupta

  • The EDA Challenges in the Dark Silicon Era: Temperature, Reliability, and Variability Perspectives

    Muhammad Shafique;Siddharth Garg;Jörg Henkel;Diana Marculescu

  • Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

    Maurizio Capra;Beatrice Bussolino;Alberto Marchisio;Guido Masera

  • An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks

    Maurizio Capra;Beatrice Bussolino;Alberto Marchisio;Muhammad Shafique

  • Architectural-space exploration of approximate multipliers

    Semeen Rehman;Walaa El-Harouni;Muhammad Shafique;Akash Kumar

  • A Miniaturized Flexible Frequency Selective Surface for X-Band Applications

    Mudassar Nauman;Rashid Saleem;Amir Khurrum Rashid;Muhammad Farhan Shafique

  • Reliable software for unreliable hardware: embedded code generation aiming at reliability

    Semeen Rehman;Muhammad Shafique;Florian Kriebel;Jorg Henkel

  • A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems

    Denise Ratasich;Faiq Khalid;Florian Geissler;Radu Grosu

  • Invited - Cross-layer approximate computing: from logic to architectures

    Muhammad Shafique;Rehan Hafiz;Semeen Rehman;Walaa El-Harouni

  • Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead

    Muhammad Shafique;Mahum Naseer;Theocharis Theocharides;Christos Kyrkou

  • TSP: thermal safe power: efficient power budgeting for many-core systems in dark silicon

    Santiago Pagani;Heba Khdr;Waqaas Munawar;Jian-Jia Chen

  • New trends in dark silicon

    Jorg Henkel;Heba Khdr;Santiago Pagani;Muhammad Shafique

  • Performance evaluation of convolutional neural network for hand gesture recognition using EMG

    Ali Raza Asif;Asim Waris;Syed Omer Gilani;Mohsin Jamil;Mohsin Jamil

  • ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

    Vojtech Mrazek;Zdenek Vasicek;Lukas Sekanina;Muhammad Abdullah Hanif

  • High-Performance Accurate and Approximate Multipliers for FPGA-based Hardware Accelerators

    Salim Ullah;Semeen Rehman;Muhammad Shafique;Akash Kumar

  • Compact ultra-wideband diversity antenna with a floating parasitic digitated decoupling structure

    Muhammad Saeed Khan;Antonio-Daniele Capobianco;Ali Imran Najam;Imran Shoaib

  • Probabilistic Error Modeling for Approximate Adders

    Sana Mazahir;Osman Hasan;Rehan Hafiz;Muhammad Shafique

  • Polarization Insensitive Dual Band Frequency Selective Surface for RF Shielding Through Glass Windows

    Umer Farooq;Muhammad Farhan Shafique;Muhammad Junaid Mughal

  • An adaptive complexity reduction scheme with fast prediction unit decision for HEVC intra encoding

    Muhammad Usman Karim Khan;Muhammad Shafique;Jorg Henkel

  • An overview of next-generation architectures for machine learning: Roadmap, opportunities and challenges in the IoT era

    Muhammad Shafique;Theocharis Theocharides;Christos-Savvas Bouganis;Muhammad Abdullah Hanif

  • FT-ClipAct: resilience analysis of deep neural networks and improving their fault tolerance using clipped activation

    Le-Ha Hoang;Muhammad Abdullah Hanif;Muhammad Shafique

Frequent Co-Authors

Jorg Henkel
Jorg Henkel Karlsruhe Institute of Technology
Jian-Jia Chen
Jian-Jia Chen TU Dortmund University
Sri Parameswaran
Sri Parameswaran University of Sydney
Tulika Mitra
Tulika Mitra National University of Singapore
Akash Kumar
Akash Kumar TU Dresden
Jürgen Teich
Jürgen Teich University of Erlangen-Nuremberg
Norbert Wehn
Norbert Wehn Technical University of Kaiserslautern
Puneet Gupta
Puneet Gupta University of California, Los Angeles
Massoud Pedram
Massoud Pedram University of Southern California

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