Zilverling

dr.ir. S.G.A. Gillani (Ghayoor)

Assistant Professor
EEMCS-CS-CAES
Zilverling 5078
s.ghayoor.gillani@utwente.nl
+31534894635
Business card

G.A. GILLANI received the B.Sc. degree in electrical engineering (with honors) from University of Engineering and Technology (UET), Taxila, Pakistan, the Master of Engineering (M.Eng.) degree in computer science and technology from Northwestern Polytechnical University, Xián, China, and the Ph.D. degree from the faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, The Netherlands.
His research interests include energy-efficient computing, low-power signal processing, deep learning and the non-conventional computing paradigms like near-memory computing, brain-inspired computing, and approximate computing.
Dr. Gillani is currently an Assistant Professor at the University of Twente. He also serves as a guest faculty at the Vrije University, Amsterdam. Moreover, he has industrial experience at different levels like senior design engineer (embedded systems) and Product Lead.

Expertise

  • Computer Science

    • Approximate Computing
    • Computing
    • Error Resilience
    • Algorithms
    • Application
    • Power Efficiency
    • Case Study
    • Survey

Organisations

Publications

2026

AMPEREISH: Approximate Multipliers for Power Efficiency in FPGA Designs Using Internal-Self-Healing (2026)IEEE Access, 14, 60252-60267. Article 11482441 (E-pub ahead of print/First online). Rasheed, Y., Van Der Wijk, R. H., Van Loo, R., Jauregui Morris, R. A., Gillani, G. A., Kokkeler, A. B. J. & Ottavi, M.https://doi.org/10.1109/ACCESS.2026.3684720

2025

Toward Approximate Computing for Deep Learning in Embedded Systems: A Systematic Literature Review (2025)IEEE Access, 13, 210863-210891. Rasheed, Y., Anwar, M. W., Gillani, G. A. & Ottavi, M.https://doi.org/10.1109/ACCESS.2025.3641821Leveraging Error Resilience of Iterative Algorithms for Energy Efficiency: from Concept to Implementation (2025)[Working paper › Preprint]. ArXiv.org. Gillani, G. A., Krapukhin, A. & Kokkeler, A. B. J.https://doi.org/10.48550/arXiv.2502.14729Investigating Approximate Computing to design an energy-efficient deep learning architecture for anomaly detection from ECG signals (2025)[Contribution to conference › Abstract] 10th Dutch Biomedical Engineering Conference, BME 2025. Capitani, D., Gillani, G. & John, A.

2024

Emerging Industrial Internet of Things Open-Source Platforms and Applications in Diverse Sectors (2024)Telecom, 5(2), 369-399. Ayele, E. D., Gavriel, S., Gonzalez, J. F., Teeuw, W. B., Philimis, P. & Gillani, G.https://doi.org/10.3390/telecom5020019Modeling the effects of power efficient approximate multipliers in radio astronomy correlators (2024)Experimental Astronomy, 57(2). Article 11. Kokkeler, A. B. J., Gillani, G. A. & Boonstra, A. J.https://doi.org/10.1007/s10686-024-09921-3

Research profiles

Address

University of Twente

Zilverling (building no. 11), room 5078
Hallenweg 19
7522 NH Enschede
Netherlands

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