Cheng-Te Li (李政德) @ NCKU

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.