Qi He

Qi He is an Associate Professor at the College of Information Technology, Shanghai Ocean University, serving as a master's tutor and member of the Shanghai Branch of the Chinese Computer Society (CCF). Her academic career bridges computer science and marine applications through interdisciplinary research.

Her educational background includes:

• Ph.D. in Computer Software and Theory from Fudan University

Her research focuses on marine big data storage, workflow and business process management, service computing, and cloud computing. She pioneers applications of deep learning in ocean informatics, developing novel frameworks for sea surface temperature forecasting, coastal change detection, and ocean front analysis using multimodal data fusion and transformer architectures.

Recent publications (2024-2025) reveal a consistent trend toward transformer-based models and ensemble networks for oceanographic time series prediction and remote sensing. Key contributions address subseasonal forecasting (10-30 day horizon), multiscale periodic pattern recognition, and multimodal entity extraction, demonstrating strong integration of computer vision with marine science challenges.

As a master's tutor, she mentors graduate students in ocean informatics. Her active publication record in high-impact journals (including IEEE JSTARS and Applied Sciences) indicates sustained research funding in marine big data infrastructure and computational oceanography, though specific grant details aren't provided in source materials.