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Privatdoz.in Dr.-Ing.in Semeen Rehman ,
Privatdoz.in Dr.-Ing.in Semeen Rehman

Contact Information

Telephon:
E-Mail:
semeen.rehman@tuwien.ac.at
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TISS:
TISS
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All publications

  • M. Hanif, A. Marchisio, T. Arif, R. Hafiz, S. Rehman, M. Shafique, X-DNNs: Systematic Cross-Layer Approximations for Energy-Efficient Deep Neural Networks. ASP Journal of Low Power Electronics (JOLPE), vol. 14, no. 4, 2018, pp. 520 - 534.
  • B. Prabakaran, M. Dave, F. Kriebel, S. Rehman, M. Shafique, Architectural-Space Exploration of Heterogeneous Reliability and Checkpointing Modes for Out-of-Order Superscalar Processors. IEEE Access, vol. 7, 2019, pp. 145324 - 145339.
  • A. Hassan, F. Khalid, H. Tariq, M. Hanif, R. Ahmed, S. Rehman, SSCNets: Robustifying DNNs using Secure Selective Convolutional Filters.. Ieee Design & Test, vol. 37, 2020, pp. 1 - 8.
  • S. Ullah, H. Schmidl, S. Satyendra Sahoo, S. Rehman, A. Kumar, Area-optimized Accurate and Approximate Softcore Signed Multiplier Architectures. IEEE Transactions on Computers, vol. PP, 2020, pp. 1 - 8.
  • F. Khalid, I. H. Abbassi, S. Rehman, A. Mehmood Kamboh, O. Hassan, ForASec: Formal Analysis of Hardware Trojan-based Security Vulnerabilities in Sequential Circuits. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. "", no. "", 2021, pp. ##.
  • B. Prabakaran, A. Akhtar, S. Rehman, O. Hasan, M. Shafique, BioNetExplorer: Architecture-Space Exploration of Biosignal Processing Deep Neural Networks for Wearables. IEEE Internet of Things Journal, vol. 8, no. 17, 2021, pp. 13251 - 13265.
  • S. Rehman, S. Ullah, M. Shafique, A. Kumar, High-Performance Accurate and Approximate Multipliers for FPGA-based Hardware Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. "", 2021, pp. ##.
  • N. Taimoor, S. Rehman, Reliable and Resilient AI and IoT-based Personalised Healthcare Services: A Survey. IEEE Access, vol. "", no. "", 2021, pp. 535 - 563.
  • M. Hanif, R. Hafiz, M. Javed, S. Rehman, M. Shafique, Energy-Efficient Design of Advanced Machine Learning Hardware, in Machine Learning in VLSI Computer-Aided Design, Springer International Publishing, 2019, pp. 647 - 678.
  • M. Hanif, M. Javed, R. Hafiz, S. Rehman, M. Shafique, Hardware-Software Approximations for Deep Neural Networks, in Approximate Circuits: Methodologies and CAD, Springer International Publishing, 2019, pp. 269 - 288.
  • B. Prabakaran, W. El-Harouni, S. Rehman, M. Shafique, Approximate Multi-Accelerator Tiled Architecture for Energy-Efficient Motion Estimation, in Approximate Circuits: Methodologies and CAD, Springer International Publishing, 2019, pp. 249 - 268.
  • S. Rehman, B. Prabakaran, W. El-Harouni, M. Shafique, J. Henkel, Heterogeneous Approximate Multipliers: Architectures and Design Methodologies, in Approximate Circuits: Methodologies and CAD, Springer International Publishing, 2019, pp. 45 - 66.
  • M. Shafique, O. Hasan, R. Hafiz, S. Mazahir, M. Hanif, S. Rehman, Approximate Computing across the Hardware and Software Stacks, in Many-Core Computing: Hardware and Software, IET, 2019, pp. 497 - 522.
  • M. Hanif, F. Khalid, R. Putra, M. T. Teimoori, F. Kriebel, J. Zhang, K. Liu, S. Rehman, T. Theocharides, A. Artusi, S. Garg, M. Shafique, Robust Computing for Machine Learning-Based Systems, in Dependable Embedded Systems, Springer Nature Switzerland AG, 2020, pp. 479 - 503.
  • A. Herkersdorf, M. Engel, M. Glaß, J. Henkel, V. Kleeberger, J. Kühn, P. Marwedel, D. Mueller-Gritschneder, S. Nassif, S. Rehman, W. Rosenstiel, U. Schlichtmann, M. Shafique, J. Teich, N. Wehn, C. Weis, RAP Model-Enabling Cross-Layer Analysis and Optimization for System-on-Chip Resilience, in Dependable Embedded Systems, Springer Nature Switzerland AG, 2020, pp. 1 - 27.
  • F. Kriebel, K. Chen, S. Rehman, J. Henkel, J. Chen, M. Shafique, Dependable Software Generation and Execution on Embedded Systems, in Dependable Embedded Systems, Springer Nature Switzerland AG, 2020, pp. 139 - 160.
  • F. Kriebel, F. Khalid, B. Prabakaran, S. Rehman, M. Shafique, Fault-Tolerant Computing with Heterogeneous Hardening Modes, in Dependable Embedded Systems, Springer Nature Switzerland AG, 2020, pp. 161 - 180.
  • M. Salehi, F. Kriebel, S. Rehman, M. Shafique, Power-Aware Fault-Tolerance for Embedded Systems, in Dependable Embedded Systems, Springer Nature Switzerland AG, 2020, pp. 565 - 588.
  • F. Khalid, A. Hassan, M. Hanif, S. Rehman, R. Ahmed, M. Shafique, FaDec: A Fast Decision-based Attack for Adversarial Machine Learning, IEEE International Joint Conference on Neural Networks (IJCNN), IJCNN, 2020, pp. 1 - 8.
  • B. Prabakaran, S. Rehman, M. Hanif, S. Ullah, G. Mazaheri, A. Kumar, M. Shafique, DeMAS: An Efficient Design Methodology for Building Approximate Adders for FPGA-Based Systems, in IEEE/ACM 21st Design, Automation and Test in Europe Conference & Exhibition (DATE), 2018, pp. 917 - 920.
  • M. Shafique, T. Theocharides, C.-S. Bouganis, M. Hanif, F. Khalid, R. Hafiz, S. Rehman, An Overview of Next-Generation Architectures for Machine Learning: Roadmap, Opportunities and Challenges in the IoT Era, in IEEE/ACM 21st Design, Automation and Test in Europe Conference (DATE), 2018, pp. 827 - 832.
  • S. Ullah, S. Rehman, B. Prabakaran, F. Kriebel, M. Hanif, M. Shafique, A. Kumar, Area-Optimized Low-Latency Approximate Multipliers for FPGA-based Hardware Accelerators, in 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC), 2018, pp. 1 - 6.
  • M. Hanif, F. Khalid, R. Putra, S. Rehman, M. Shafique, Robust Machine Learning Systems: Reliability and Security for Deep Neural Networks, in 2018 IEEE 24th International Symposium on On-Line Testing and Robust System Design (IOLTS), 2018, pp. 257 - 260.
  • S. Rehman, F. Kriebel, B. Prabakaran, F. Khalid, M. Shafique, Hardware and Software Techniques for Heterogeneous Fault-Tolerance, in 2018 IEEE 24th International Symposium on On-Line Testing and Robust System Design (IOLTS), 2018, pp. 115 - 118.
  • F. Kriebel, S. Rehman, M. Hanif, F. Khalid, M. Shafique, Robustness for Smart Cyber Physical Systems and Internet-of-Things: From Adaptive Robustness Methods to Reliability and Security for Machine Learning, in 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2018, pp. 581 - 586.
  • M. Shafique, F. Khalid, S. Rehman, Intelligent Security Measures for Smart Cyber Physical Systems, in 2018 21st Euromicro Conference on Digital System Design (DSD), 2018, pp. 280 - 287.
  • F. Khalid, M. Hanif, S. Rehman, M. Shafique, Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference, in 16th International Conference on Frontiers of Information Technology (FIT), 2018, pp. 1 - 6.
  • I. H. Abbassi, F. Khalid, S. Rehman, A. M. Kamboh, A. Jantsch, S. Garg, M. Shafique, TrojanZero: Switching Activity-Aware Design of Undetectable Hardware Trojans with Zero Power and Area Footprint, in Proceedings of 2019 IEEE/ACM Design, Automation and Test in Europe Conference (DATE), 2019, pp. 914 - 919.
  • F. Khalid, M. Hanif, S. Rehman, J. Qadir, M. Shafique, FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning, in Proceedings of 2019 IEEE/ACM Design, Automation and Test in Europe Conference (DATE), 2019, pp. 902 - 907.
  • B. Prabakaran, S. Rehman, M. Shafique, XBioSiP: A Methodology for Approximate Bio-Signal Processing at the Edge, in Proceedings of 2019 56th ACM/IEEE Design Automation Conference (DAC), 2019, pp. 1 - 6.
  • J. Zang, K. Liu, F. Khalid, M. Hanif, S. Rehman, T. Theocharides, A. Artussi, M. Shafique, S. Garg, INVITED: Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities, in Proceeding of 2019 56th ACM/IEEE Design Automation Conference (DAC'19), 2019, pp. 1 - 4.
  • F. Khalid, H. Ali, H. Tariq, M. Hanif, S. Rehman, R. Ahmed, M. Shafique, QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks, in Proceeding of 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design (IOLTS'19), 2019, pp. 182 - 187.
  • F. Khalid, M. Hanif, S. Rehman, R. Ahmed, M. Shafique, TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks, in Proceeding of 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design (IOLTS'19), 2019, pp. 188 - 193.
  • F. Kriebel, S. Rehman, M. Shafique, Studying Aging and Soft Error Mitigation Jointly under Constrained Scenarios in Multi-Cores, in Proceeding of 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design (IOLTS'19), 2019, pp. 139 - 142.
  • M. Hanif, M. Akbar, R. Ahmed, S. Rehman, A. Jantsch, M. Shafique, MemGANs: Memory Management for Energy-Efficient Acceleration of Complex Computations in Hardware Architectures for Generative Adversarial Networks, in Proceeding of 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED'19), 2019, pp. 1 - 6.
  • F. Khalid, H. Ali, M. Hanif, S. Rehman, R. Ahmed, M. Shafique, FaDec: A Fast Decision-based Attack for Adversarial Machine Learning, in Proceedings of 2020 International Joint Conference on Neural Networks (IJCNN), 2020, pp. 1 - 8.
  • A. Colucci, D. Juhasz, M. Mosbeck, A. Marchisio, S. Rehman, M. Kreutzer, G. Nadbath, A. Jantsch, M. Shafique, MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences, in Proceedings of the 2021 Design, Automation & Test in Europe, 2021, pp. 108 - 113.