Ibrar Ahmed

Dr. Ibrar Ahmed


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 December 2021 in Sensors
Verified
Journal Article
Open access
PDF file
FAFazal Aman
Fazal Aman
ARAzhar Rauf
Azhar Rauf
RARahman Ali
Rahman Ali
JHJamil Hussain
Jamil Hussain
IAIbrar Ahmed
Ibrar Ahmed
Robust predictive modeling is the process of creating, validating, and testing models to obtain better prediction outcomes. Datasets usually contain outliers whose trend deviates from the most data points. Conventionally, outliers are removed from the training dataset during preprocessing before building predictive models. Such models, however, may have poor predictive performance on the unseen testing data involving outliers. In modern machine learning, outliers are regarded as complex signals because of their significant role and are not suggested for removal from the training dataset. Models trained in modern regimes are interpolated (over trained) by increasing their complexity to treat outliers locally. However, such models become inefficient as they require more training due to the inclusion of outliers, and this also compromises the models’ accuracy. This work proposes a novel complex signal balancing technique that may be used during preprocessing to incorporate the maximum number of complex signals (outliers) in the training dataset. The proposed approach determines the optimal value for maximum possible inclusion of complex signals for training with the highest performance of the model in terms of accuracy, time, and complexity. The experimental results show that models trained after preprocessing with the proposed technique achieve higher predictive accuracy with improved execution time and low complexity as compared to traditional predictive modeling.

26 March 2025 in Photonics
Verified
Journal Article
Open access
PDF file
AKAsad Khan
Asad Khan
JZJnling Zhang
Jnling Zhang
Muhammad IshfaqMuhammad Ishfaq
Muhammad Ishfaq
IAIbrar Ahmed
Ibrar Ahmed
SKShahbaz Khan
Shahbaz Khan
KSKamlesh Kumar Soothar
Kamlesh Kumar Soothar
A low-profile reflectarray has been designed in the Ka-band to efficiently generate wideband orbital angular momentum (OAM) vortex beams. The proposed design employs a reflective phase-shifting patch etched onto a dielectric substrate, featuring a three-square loop structure intersected by two transverse dipoles. This unit cell achieves a 440° phase shift at 30 GHz with a minimal magnitude loss of (−0.25 dB), enabling high-efficiency reflectarray performance. The OAM vortex beam supports high-order phase distributions (l=+1,+2,+3,+4) modes, though fabrication and experimental validation focused on the +1 mode. Measurements confirm that the reflectarray produces a high-purity OAM vortex beam for +1 mode, covering the operational frequency range from 27 to 39 GHz, and achieving a 40% bandwidth with a peak gain of 23.39 dBi at 33 GHz and an aperture efficiency of 17.38%. These results demonstrate the ability of the reflectarray to produce broadband directive OAM beams with robust performance, making it ideal for Ka-band communication systems.