Haris Ahmad Khan

Wageningen University & Research, Centre National de la Recherche Scientifique, Norwegian University of Science and Technology

Papers

Total Citations

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About

Haris Ahmad Khan is a researcher at the forefront of advanced sensing and intelligent robotics, with key contributions spanning multispectral imaging, deep learning for environmental perception, and robotic object manipulation. His most impactful work, “Beyond Tristimulus Color Vision with Perovskite-Based Multispectral Sensors” (2022, 16 citations), introduces a novel class of optical sensors using perovskite semiconductors, achieving high sensitivity and spectral resolution through 3D vertical integration—a breakthrough that could revolutionize machine vision beyond human color perception. In “Discriminative Deep Belief Network for Indoor Environment Classification Using Global Visual Features” (2018, 15 citations), Khan developed a discriminative deep belief network that robustly classifies indoor scenes from global visual cues, advancing autonomous navigation and smart environment systems. His earlier work, “2D/3D Object Recognition and Categorization Approaches for Robotic Grasping” (2017, 5 citations), laid foundational methods for enabling robots to recognize and grasp objects in complex settings. With a growing citation footprint, Khan’s research bridges material science, computer vision, and robotics, offering practical pathways for next-generation sensors and autonomous systems. His interdisciplinary approach continues to inspire students and researchers exploring the intersection of hardware innovation and intelligent algorithms.