Muhammad Shafique

Muhammad Shafique
Univ.Prof. Dr.-Ing.
E-Mail
Phone +43 (1) 58801-18252
Fax +43 1 5880118297
Address



Vienna University of Technology
Institute of Computer Engineering
Embedded Computing Systems
Treitlstraße 3, 1040 Wien, Österreich

Post-Doc Researchers

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PhD Students

Co-Supervised PhD Students

  • Beatrice Bussolino (co-supervising together with Prof. Maurizio Martina at Politech. Di Torino)

Student Research Assistants

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On-Going MS/BS Theses and Internships

Different theses are under joint co-supervision with my collaboration partners in Politecnico di Torino, Italy (Prof. M. Martina and Prof. G. Masera), Sapienza university of Rome, Italy (Prof. A. Rizzi), NUST, Pakistan (Prof. O. Hasan and Prof. R. Ahmed), and ITU, Pakistan (Prof. R. Hafiz)
  • Federico Teodonio: "Inexact Genome Sequence in FPGA"
  • Riccardo Massa: "Efficient Implementation of Spiking Neural Networks on the Loihi Neuromorphic Processor"
  • Antonio De Marco: "Capsule Networks Robustness against Adversarial Attacks and Affine Transformations"
  • Giuseppe Sarda: "Approximating Deep Convolutional Neural Networks through Bit-level Masking of Network Parameters"
  • Valerio Venceslai: "Fault-Injection and Neural Trojan Attacks on Spiking Neural Networks"
  • Andrea Massa: "Hardware-Aware Capsule Networks Architecture Search"
  • Dino Santoro: "Efficient Spiking Neural Networks Accelerator on FPGA"
  • Farzad Nikfam: "Fast Adversarial Training for Deep Neural Networks"
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Completed MS/BS Theses and Internships

Different theses are jointly co-supervised with my collaboration partners in Politecnico di Torino, Italy (Prof. M. Martina and Prof. G. Masera), Sapienza university of Rome, Italy (Prof. A. Rizzi), NUST, Pakistan (Prof. O. Hasan and Prof. R. Ahmed), and ITU, Pakistan (Prof. R. Hafiz)
  • Beatrice Bussolino: "Capsule Networks: Training and Quantized Inference"
  • Alessio Colucci: "Software- and Hardware-Level Optimizations for Fast Training of Capsule Networks"
  • Angelo Fusillo: "Advanced SDRAM controller architecture for Approximate Computing"
  • Clemens Pircher: "Efficient Machine Learning Architectures for FPGAs"
  • Giorgio Nanfa: "Black-Box Adversarial Attacks for Deep Neural Networks and Spiking Neural Networks"
  • Mohammad Omer Naeem: "Energy and Performance Efficient Inference for Neural Networks"
  • Hassan Ali: "Analyzing the Security Vulnerabilities of Deep Neural Networks: Attacks and Defenses"
  • Muhammad Zuhaib Akbar: "Efficient Hardware for Generative Adversarial Networks (GANs)"
  • Nouman Naseer: "Efficient Sparse Matrix-Vector Multiplication Accelerator for Compressed Deep Neural Network Inference"
  • Alberto Marchisio: "Optimizing Deep Neural Networks on GPUs"
  • Ayesha Siddique: "On-Sensor Approximate Computing for Compressed Sensing in IoT-Edge Systems"
  • Kamran Ayub: "Statistical Error Analysis for Low Power Approximate Adders"
  • Paolo Selvo: "Approximate Computing for Energy-Efficient Motion Estimation in High Efficiency Video Coding"
  • Aditya Manglik: "ReRAM based DNN Architectures"
  • Himanshu Kumar: "Energy Efficiency in IoT Healthcare"
  • Radha Vaidya: "Hardware Security for FPGAs"
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Administration Team

Alumni: Post-Doc Researchers

  • Vojtěch Mrázek
  • Marcelo Brandalero
  • Muhammad Taghi Teimoori

Alumni: PhD Researchers

  • Paniti Achararit (Tokyo Institute of Technology, Japan): Hardware-Aware Neural Architecture Search
  • Omid Akbari (University of Tehran, Iran): Approximate Coarse-Grained Reconfigurable Processors
  • Muhammad Taghi Teimoori (Sharif University, Iran): Approximate Memories
  • Marcelo Brandalero (UFRGS, Brazil): Approximate Reconfigurable Computing
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