Chengxing Zhai — accepted AI-conference papers

2026

Efficient Forecasting of Geostationary Infrared Brightness Temperature Sequences: A Benchmark and a Lightweight Model

Kuai Dai, Hui Su, Xutao Li, Chengxing Zhai

AAAI 2026technical

Forecasting geostationary infrared brightness temperature sequences from historical observations is a significant and challenging task. By analyzing these predictions, cloud evolution, convective activity, and atmospheric radiative states can be revealed in advance, offering high potential value in

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2026

SatSolarCast: A Flexible Framework for Multimodal Solar Irradiance Forecasting via Memory-Alignment Learning

Kuai Dai, Hui Su, Chengxing Zhai, Huiwei Lin, Mingliang Bai

AAAI 2026technical

Solar irradiance forecast aims to accurately estimate future solar irradiance based on historical data, playing a vital role in energy production and grid management. While ground-based station measurements provide local accuracy, geostationary satellites offer much broader environmental contexts,

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