Cheng-Te Li (李政德) @ NCKU
Short Bio. I am Professor at Department of Computer Science and Information Engineering (資訊工程學系) also jointly appointed at Institute of Data Science (數據科學研究所) and Department of Statistics, National Cheng Kung University (NCKU, 成功大學), Tainan, Taiwan. I received my Ph.D. degree (2013) from Graduate Institute of Networking and Multimedia, National Taiwan University. Before joining NCKU, I was an Assistant Research Fellow (2014-2016) at Research Center for IT Innovation (CITI, 資創中心), Academia Sinica (中央研究院). Our research targets at Machine Learning, Deep Learning, and Data Science with their applications to Social Networks, Recommender Systems, Trustworthy AI, Combating Fake News, Fraud Detection, Smart Cities, and Computational Health. Problems we tackle are inspired by real-world applications with massive datasets, and methods we present tend to be graph-based. I lead Networked Artificial Intelligence Laboratory (NetAI Lab) at NCKU.
Contact Information
Email: chengte[at]ncku.edu.tw
Tel: +886-6-2757575 ext. 62560
Office: Old Building 1F Room 4205A, Dept. of CSIE, No.1, University Road, Tainan 701, Taiwan
[徵才] Recruiting!! We are seeking for Postdoc Researcher (博士後研究員), research assistants (專任研究助理), and potential students (兼任研究助理). If you are passionate in learning the skills of Data Science / Machine Learning / Deep Learning, or interested in the applications of Trustworthy AI, Social Network, Social Media, Privacy/Security, Disinformation, Fraud Detection, Recommender Systems, Internet of Things, Smart City, and Computational Health, feel free to email me about the possibility to join us. For more details about our research, please visit my Research Topics.
What's New
Two papers on AI Food Safety and FinTech are accepted to The Web Conferece (WWW) 2024.
One paper on GNN-based Recommender Systems is accepted to IEEE Computational Intelligence Magazine (CIM) 2024.
Featured interview by News Media (FTV) for 圖機器學習之對抗式個資隱私攻防.
Our survey paper entitled "Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions" is available at arXiv. We also create an awesome page on Github. Both will be kept updated.
Join the CSIE department of National Cheng Kung University, and start a new lab at August 2023.
Give a tutorial on "Defending against Misinformation in the Wild" at APSIPA ASC 2023.
Give a tutorial on "Demystifying Graph Neural Networks: Essentials, Applications, and Trends" at ROCLING 2023.
Delivered a lecture-style tutorial on "Graph Neural Networks for Tabular Data Learning (GNN4TDL)" at TheWebConf (WWW) 2023, IEEE ICDE 2023, and IEEE DSAA 2022.
Two papers on Graph Neural Networks with Hierarchy-awareness and Reinforcement Learning get accepted to DMKD (ECML PKDD Journal Track).
One paper on Graph Neural Networks with Adaptive Structural Granularity gets accepted to IEEE TKDE.
Gave a keynote speech on "Graph Machine Learning and Its Applications" at PyCon APAC 2022.
Received the 2022 Y. Z. Hsu Scientific Paper Award (有庠科技論文獎) in the category of Artificial Intelligence!
Honored by the 2021 Young Scholars’ Creativity Award (年輕學者創新獎) from Foundation for the Advancement of Outstanding Scholarship (傑出人才發展基金會).
One paper on Adversarial Attack and Defense on Graphs gets accepted to IEEE TKDE.
Two papers on Graph Representation Learning are accepted to IEEE TKDE.
One paper on zero-shot learning for relation extraction gets accepted as a long paper to NAACL 2021.
One paper on graph neural network-based sequential recommendation gets accepted as a regular paper to The Web Conference (WWW) 2021.
One paper on explainable cyberbullying detection gets accepted as a long paper to EMNLP 2020.
One paper on urban computing (air quality forecasting, traffic flow prediction, and bike demand prediction) gets accepted as a short paper to IEEE ICDM 2020.
Two papers on self-supervised learning and actor recommendation are accepted by IEEE BigData 2020 and IEEE/ACM ASONAM 2020 as full papers, respectively.
The presentation of my research highlights, titled 連結萬物的網路人工智慧 – 瘟疫、反恐、空汙、走私與假訊息 is available on YouTube by MOST YSF.
Our research outcomes on AI privacy and ethics on social media are interviewed and reported by mass media: AI攻防社群媒體的隱私與道德 (工商時報, 2020.05.11)
One paper on deep learning-based customs fraud detection gets accepted as a full paper by ACM KDD 2020. This work is an joint collaboration with World Customs Organization (WCO). Here is the press release by World Customs Organization (WCO) official website.
Received the K. T. Li Young Researcher Award (李國鼎青年研究獎) 2019.
One paper on explainable fake news detection gets accepted as a long paper by ACL 2020.
Invited as the Keynote Speaker at the 4th International Workshop on Mining Actionable Insights from Social Networks (MAISoN) at TheWebConf 2020. The online presentation can be accessed below.
One paper on network embedding gets accepted as a regular paper by The Web Conference (WWW) 2019.
受科學人雜誌邀稿，撰寫「從社群網路看資訊流動」一文，為本實驗室研究主題之一。
關於本實驗室的研究介紹，亦可參考我接受臺大科學教育發展中心針對「社群網路與人工智慧」之專訪。
共同策劃 2018人工智慧探索講座「智慧新世界：圖靈所沒料想到的人工智慧」 與 2018人工智慧AI嘉年華 之科普活動，歡迎踴躍報名參加。
Co-orgranize SocialNLP workshop in ACL 2018 at Melbourne, Australia. Welcome to your submission! (Past: SocialNLP in TheWebConf (WWW) 2018 at Lyon, France.
Serve as Program Chair in TAAI 2017 Domestic Track (The 2017 Conference on Technologies and Applications of Artifical Intelligence), was held at NTU CSIE, Taipei, Taiwan.