Khan Muhammad
Khan Muhammad is an associate professor at Sungkyunkwan University in Seoul, where he directs the Visual Analytics for Knowledge (VIS2KNOW) Laboratory and studies intelligent video surveillance, medical image analysis and information security. After finishing first in his BS program in 2014, he earned a PhD in digital content from Sejong University in 2019 and served there as an assistant professor until 2022. His AI work includes a 2019 SqueezeNet-inspired CNN for detecting and locating fires in surveillance video, a 2021 survey of deep learning for safe autonomous driving, and the 2024 HazeSpace2M dehazing dataset. Clarivate named him a Highly Cited Researcher every year from 2021 to 2024, and Seoul made him an honorary citizen in 2022.
- Now at
- Sungkyunkwan University
- Works
- 327
- Citations
- 23,424
- h-index
- 80
- Badges
Publication numbers from OpenAlex, as of 22 October 2026.
Timeline
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2010–2015
A gold medal and a fellowship
He completes his 2010–2014 BS program as its first-position holder and gold medalist, and in 2014 he wins a software project competition at City University in Peshawar, Pakistan. In 2015, he receives an MS-leading-to-PhD fellowship award.
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2019
Fire detection and a Sejong PhD
He receives his PhD in digital content from Sejong University in February 2019. In July 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems publishes his first-author paper with Jamil Ahmad, Sung Wook Baik and others on an energy-friendly, SqueezeNet-inspired CNN for detecting and localizing fires in surveillance video.
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March 2019–February 2022
Assistant professor at Sejong
From March 2019 to February 2022, he is a non-tenure-track assistant professor in Sejong University's Department of Software. Sejong University gives him its Outstanding Research Award in 2019.
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July 2021
A survey on safe autonomous driving
In July 2021, he publishes a survey of deep learning for safe autonomous driving in IEEE Transactions on Intelligent Transportation Systems with Amin Ullah, Jaime Lloret, Javier Del Ser and Victor Hugo C. de Albuquerque. It reviews methods across the driving pipeline, from road, lane, vehicle, pedestrian and drowsiness detection to collision avoidance and traffic sign detection.
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2021–2024
A Highly Cited Researcher
Web of Science (Clarivate) recognizes him as a Highly Cited Researcher in 2021, 2022, 2023 and 2024. He becomes an IEEE Senior Member in 2022.
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February 2022–August 2024
Tenure track at Sungkyunkwan
In February 2022, he joins Sungkyunkwan University in Seoul as a tenure-track assistant professor in the Department of Applied AI, School of Convergence, and holds the post until August 2024. Seoul names him one of 18 foreign residents chosen as honorary citizens in 2022, recognizing the researcher from Pakistan for a scientific breakthrough and a patent for public safety technologies.
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2024–2025
The HazeSpace2M dataset
In 2024, he coauthors HazeSpace2M, a dataset of over 2 million images that pairs haze-type classification with specialized dehazers, accepted at ACM Multimedia 2024. His July 2025 keynote at the International Conference on Computational Science and Its Applications covers image enhancement in haze, fog and low light, drawing on HazeSpace2M and the LoLI-Street benchmark.
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As of October 2026
Associate professor at Sungkyunkwan
He is an associate professor in Sungkyunkwan University's School of Convergence and directs the Visual Analytics for Knowledge (VIS2KNOW) Laboratory. His research covers intelligent video surveillance, medical image analysis, information security and multimedia data analysis.
Career
- Since 2022Sungkyunkwan UniversityAssistant professor
- 2019–2022Sejong UniversityAssistant professor
Education
- 2019Sejong UniversityPhD
Most-cited works
- Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial IntelligenceWith Francisco Herrera
- Multi-grade brain tumor classification using deep CNN with extensive data augmentation
- Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features
- Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions
- Early fire detection using convolutional neural networks during surveillance for effective disaster management
Sources and credits
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- Awards and Achievements · Khan Muhammad
- Keynote speakers — The 27th International Conference on Computational Science and Its Applications
- Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications - Sungkyunkwan University
- Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions - Sungkyunkwan University
- From YouTuber to newspaper columnist, 18 foreign residents become honorary Seoul citizens - The Korea Times
- [2409.17432] HazeSpace2M: A Dataset for Haze Aware Single Image Dehazing
- Khan Muhammad - Sungkyunkwan University
