Name: Ali Haider
Email: alihaider681@hotmail.com
Gender: Male
Native Country: Pakistan
Research Area: Artificial Intelligence, Computer Vision, Deep Learning, Remote Sensing Image Analysis, Object Detection, Change Detection, and Vision-Language Models
Master's Thesis Topic: A Lightweight YOLO-Driven Framework with Adaptive Multi-Scale Fusion for Robust Typical Object Detection in Remote Sensing Imagery
Supervisor: Prof. Zhenming Peng
PhD: September 2026 – Present
Supervisor: Prof. Zhenming Peng
Research Projects
• Training-Driven Multi-Scale Optimization for Lightweight Remote Sensing Object Detection.
• Structured Prompt-Guided Vision-Language Models for Remote Sensing Change Captioning.
• Lightweight YOLO-Driven Framework with Adaptive Multi-Scale Fusion for Robust Typical Object Detection in Remote Sensing Imagery.
Publications
[1] Ali Haider, Aysha Ashraf, Han Guo, Zhenming Peng. Training-Driven Multi-Scale Optimization for Lightweight Remote Sensing Object Detection [C]. Proceedings of the 9th International Conference on Artificial Intelligence and Big Data (ICAIBD 2026), Chengdu, China, May 29–31, 2026. (First Author, indexed by EI and Scopus).
[2] Aysha Ashraf, Shaina Ashraf, Wafaa I. M. Hussin, Ali Haider, Zhenming Peng. Structured Prompt-Guided Vision-Language Models for Remote Sensing Change Captioning [C]. Proceedings of the 9th International Conference on Artificial Intelligence and Big Data (ICAIBD 2026), Chengdu, China, May 29–31, 2026. (Fourth Author, indexed by EI and Scopus).
Awards and Honors
Best Presentation Award, 9th International Conference on Artificial Intelligence and Big Data (ICAIBD 2026).
Self-Evaluation: Highly motivated PhD researcher with research interests in artificial intelligence, lightweight deep learning, computer vision, and remote sensing image analysis. Dedicated to developing efficient and deployable object detection algorithms for real-world applications, with a focus on balancing model accuracy and computational efficiency. Passionate about conducting impactful research and contributing innovative solutions to intelligent remote sensing systems.