Yonis Gulzar
International Islamic University Malaysia, King Faisal University, Bangalore University, University of Kashmir
0000-0002-6515-1569
About
Dr. Yonis Gulzar is a dedicated Computer Science professional with a Ph.D. from the International Islamic University Malaysia (2018), complemented by a Master's in Computer Applications from Bangalore University (2013) and a Bachelor's in Computer Applications from the University of Kashmir (2010).
Since 2019, Dr. Gulzar has been a part of King Faisal University, where he initially joined as an Assistant Professor and was promoted to Associate Professor in February 2024. His academic journey also includes significant roles as a lecturer and a teaching and research assistant at the International Islamic University, where he contributed from 2014 to 2018.
Dr. Gulzar's research interests and expertise lie in the dynamic fields of Database Systems, Computer Vision, Artificial Intelligence, Deep Learning, and Image Processing. He is passionate about leveraging these technologies to drive innovation and solve complex problems in healthcare and agriculture.
Contact: [email protected] / [email protected]
Employment
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International Islamic University Malaysia2026 - Present
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King Faisal University Associate Professor2024 - Present
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King Faisal University Assistant Processor2019 - 2024
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International Islamic University Malaysia Lecturer/ Teaching Assistant2015 - 2018
Education
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International Islamic University Malaysia PhD Computer Science2014 - 2018
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Bangalore University Master of Computer Applications2010 - 2013
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University of Kashmir Bachelor of Computer Applications2007 - 2010
Projects & Funding
Projects & funding information is unavailable.
Publications (185)
- DADFENet: A dual-branch adaptive and dynamic feature enhancement network for hyperspectral change detection Save
- Computational Frameworks for Video Segmentation and Holistic Scene Understanding Save
- Large Vision Models (LVMs) for Video Intelligence Save
- Comparative analysis of automatic mask generation methods for agricultural seed instance segmentation Save
- Explainable AI for Detecting Harassment and Extremism in Voice Chat Save
- Gene Editing in Agriculture Save
- Interpretable Machine Learning Models for Cyber Threat Detection Save
- Determination of Carbon Sequestration Potential of Fruit Trees in Urban and Agricultural Areas Save
- Intent-Based Multi-Agent Allocation With Nature-Inspired Online Algorithm Save
- Earth Observation-Driven Mangrove Management With Global Species Mapping and Blue Carbon Assessment Save