葛啟陽檢視原始碼討論檢視歷史
葛啟陽
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簡介
從事複雜網絡和深度學習的研究工作，包括計算機視覺、自然語言處理、計算機輔助醫療、數據挖掘分析、因果推斷分析等方向。
工作經歷
2015.09-2022.06 復旦大學數學科學學院 應用數學專業 博士學位 導師：林偉教授
教育經歷
2015.09-2022.06 復旦大學數學科學學院 應用數學專業 博士學位 導師：林偉教授
2011.09-2015.07 復旦大學數學科學學院 數學與應用數學專業 學士學位
代表成果
Preprints
1. Hu Z, Ge Q, Luo L, and et al. Population vaccine effectiveness and its implication for control of the spread of COVID-19 in the US. medRxiv, 2021.
2. Ge Q, Hu Z, Zhang K, Li S, Wei L, and et al. Recurrent neural reinforcement learning for counterfactual evaluation of public health interventions on the spread of Covid-19 in the world. medRxiv, 2020: 2020.07.
3. Hu Z, Ge Q, and et al. Artificial intelligence forecasting of Covid-19 in China. arXiv preprint arXiv: 2002.07112, 2020.
4. Hu Z, Ge Q, and et al. Spread of Covid-19 in the United States is controlled. medRxiv, 2020.
Papers in Refereed Journals
1. Ge Q, Hu Z, Li S, Lin W, and et al. A novel intervention recurrent autoencoder for real time forecasting and non-pharmaceutical intervention selection to curb the spread of Covid-19 in the world. Statistics and Its Interface, 2021, 14(1):37-47.
2. Ge Q, Huang X, Fang S, Guo S, Liu Y, Lin W, and et al. Conditional generative adversarial networks for individualized treatment effect estimation and treatment selection. Frontiers in Genetics, 2020, 11.
3. Hu Z, Ge Q, and et al. Evaluating the effect of wearing face masks by the general population on mitigating the spread of COVID-19. Epidemiology International Journal. 2020, 4I2.
4. Hu Z, Ge Q, Li S, and et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide. Frontiers in Artificial Intelligence, 2020, 3:41.