News & Updates
- [Sep 2025] Joined as Postdoctoral Researcher at the Vision & Learning Laboratory, UNIST.
- [Jun 2025] "Traffic Sign Recognition Under Visual Perturbations: Shadows, Light Patches, and Simulated Obstructions." In Proceedings of Computer Vision and Pattern Recognition (CVPR). [LINK]
- [Feb 2025] "M-GAID: A Real-World Dataset for Ghosting Artifact Detection and Removal in Mobile Imaging." In Proceedings of Winter Conference on Applications of Computer Vision (WACV). [LINK]
- [Nov 2024] As part of Pi-lab, we generated a Real-World Ghosting Artifact Dataset specifically for mobile imaging.
- [Jun 2023] Received Best Paper Award for FireXplainer at KCC'23.
About Me
I am a postdoctoral researcher at the Vision & Learning Lab, UNIST, focusing on efficient and interpretable deep learning frameworks for computer vision applications. I recently completed my Ph.D. in the Pervasive Intelligence Lab at Sangmyung University under Professor Heemin Park. My research focuses on developing efficient and interpretable deep learning frameworks, particularly for computer vision applications such as medical imaging analysis, mobile imaging artifact removal, object detection, and traffic sign recognition under challenging conditions. I am particularly interested in creating robust vision systems that can handle real-world visual perturbations and artifacts. Through my work, I aim to bridge the gap between theoretical advances in machine learning and practical solutions for real-world computer vision challenges, contributing to both academic research and industry applications.
Education
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Ph.D. in Software (Machine Learning & Computer Vision)
Sangmyung University, Korea 2025)
Dissertation: Efficient and Interpretable Deep Learning Frameworks for Resource-Constrained and Time-sensitive Vision Applications -
M.S. in Information Technology
National University of Science and Technology (NUST), Islamabad, Pakistan (2019)
Thesis: Prediction based Target Tracking in Wireless Sensor Network -
B.Sc. in Computer Engineering
COMSATS Institute of Information Technology (CIIT), Lahore, Pakistan (2014)
Research Interests
- Computer Vision & Image Processing: Low-light enhancement, Feature extraction and visualization.
- Medical Imaging: MRI analysis, Tumor segmentation, Multi-class classification, Resolution enhancement.
- Efficient Model Design: Lightweight Deep Learning Architectures, Model Optimization and Quantization.
- Image/Video Enhancement & Artifact Removal: Noise Removal, Ghosting Artifact Compression.
- Interpretable AI: Explainable Deep Learning models, Gradient-based Attribution Methods.
Research Funding & Honors
- Google Korea Research Grant (2024-2025): "Post-Processing Methods for Artifact Removal"
- Google Korea Research Grant (2023-2024): "Objective Quality Metrics for Ghosting Artifacts"
- Best Paper Award (2023): "FireXplainer: An Interpretable Approach for Detection of Wildfires"
- Professor Scholarship for Ph.D. (2021-2025): Pi-Lab, Sangmyung University
- DURE Scholarship (2022-2023): For international collaboration with Mongolia
- Teaching Assistant Scholarship (2021-2022): Department of Software, Sangmyung University