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  • 學術會議

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    【翠屏經管論壇2022年第02期】

    時間:2022-05-19作者: 審核: 來源:經濟管理學院點擊:213

    “鳳回巢”系列學術講座

    榜樣引領,薪火相傳。新加坡、香港、加拿大三地南航校友回校報告


    1)報告題目:Identifying COVID-19 Cases in Singapore During the Early Pandemic Period

    報告人:孫殷霄翯

    報告時間:2022年6月2日 19:00-20:00

    報告地點:騰訊會議 911-7495-8724

    報告簡介:Rapid identification of COVID-19 cases, which is crucial to outbreak containment efforts, is challenging due to the lack of pathognomonic symptoms and in settings with limited capacity for specialized nucleic acid–based reverse transcription polymerase chain reaction (PCR) testing. Thus, we developed models to identify COVID-19 cases via epidemiological and clinical features. Thereafter, a Web Application with improved algorithms was developed for use in outpatient settings. The Web Application assisted physicians decide those patients who need priority PCR testing in early outbreak.

    報告人簡介:孫殷霄翯,南京航空航天大學信息與計算科學專業理學學士、新加坡國立大學統計與應用概率專業碩士?,F為新加坡國立大學公共衛生學院博士生、助理研究員。主要研究方向為傳染病流行病學的傳染病建模和貝葉斯方法。在Clinical Infectious Diseases、Risk Management and Healthcare Policy等刊物發表論文11篇,成功申請1項種子研究基金(S$100,000)。

     

    2)報告題目:Intralogistics Synchronization in Robotic Forward-reserve Warehouses for Last-mile Delivery

    報告人:蔣敏

    報告時間:2022年6月2日 20:00-21:00

    報告地點:騰訊會議 911-7495-8724

    報告簡介:Intralogistics operations (IOs) are defined as the operations inside a warehouse. This talk discusses IOs in a typical robotic forward-reserve e-commerce warehouse involving manual order-picking and robotic order sorting operations. It is critical to synchronize IOs between different areas considering delivery requirements to improve the overall performance. This challenge is formulated as a delivery-driven intralogistics synchronization (DDIS) problem. Our study develops a tailored variable neighborhood search solution method. A series of comprehensive numerical experiments under various scenarios show the superiority and stability of the DDIS as benchmarked with sequential approaches. A substantial reduction can be achieved in both makespan and forward area size, indicating significantly improved intralogistics operational efficiency and space utilization. Managerial insights are also discussed for specific action plans regarding the market size, the labor force, and the trolley configuration.

    報告人簡介:蔣敏,南京航空航天大學工業工程系學士、香港大學工業工程系博士?,F任Barclays Capital(香港)量化研究員。博士期間研究方向為智能倉儲、運籌優化與供應鏈管理。作為第一作者在Transportation Research Part E: Logistics and Transportation Review發表過多篇相關論文,并擔任EJOR、TRE、IJPR等期刊審稿人。

     

    3)報告題目:Exploiting Human Trust to Improve Recommender Systems

    報告人:Jie Zhang

    報告時間:2022年6月9日 16:00-17:00

    報告地點:騰訊會議 911-7495-8724

    報告簡介:Recommender systems based on collaborative filtering suffer from the problems of data sparsity and cold start. Trust-aware recommender systems exploit human trust relationships to improve recommendation performance. In this talk, I will briefly summarize the state-of-the-art methods along this line of research and highlight a few representative works from our group. I will also point out several remaining challenges and interesting future directions.

    報告人簡介:Jie Zhang,南京航空航天大學計算機學院學士、加拿大滑鐵盧大學計算機科學學院博士?,F任新加坡南洋理工大學計算機科學與工程學院副教授。研究領域是人工智能的子領域——用戶建模,主要研究各種新興應用領域的信任建模和偏好建模。論文在頂級人工智能會議(如NeurIPS、AAAI和IJCAI)和頂級期刊(如TKDE和AIJ)上發表。多次在會議上獲得最佳論文獎,以及斯坦福大學頒發的世界頂尖2%科學家獎和AI 2000最具影響力學者榮譽獎。擔任《Electronic Commerce Research and Applications》雜志的高級編輯,并將擔任2023年ACM Recommender Systems會議的總主席。


    學院地址:江蘇省南京市江寧區將軍大道29號

    郵政編碼:211106

    版權所有:南京航空航天大學 ALL RIGHTS RESERVED 蘇ICP備05070685號

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