Welcome to Caleb's Homepage

Short Biography

Caleb Cao (曹琛) is now a senior manager of research and development in Big Data Institute, HKUST. He is affiliated with HKGAI(Hong Kong Generative AI Research Center) and HKUST(GZ) as well.

Before joining HKUST, he was an AI Data specialist in Huawei Hong Kong Research Center, where he honourably founded the AI Framework and Data Technology Lab as the tech lead. In this lab, he initiated research works in Data-driven and Knowledge-aware eXplainable AI and translated a set of frontier research into Huawei's all-scenario deep learning framework MindSpore.

Caleb graduated in 2014 with a Ph.D degree in computer science from The Hong Kong University of Science and Technology. He was supervised by Prof. Lei Chen and worked on Stochastic Combinatorial Optimization and its application in Data-driven Crowdsourced Human Computation(PhD Thesis). Before that, in 2010, Caleb received his bachelor's degree in telecommunication engineering from Beijing University of Posts and Telecommunications. He finished his undergraduate thesis in Daedalus S.A.(acquired by MeaningCloud) & Universidad Politécnica de Madrid under Prof. José C. González's supervision.

For more information, please drop me an email to cao AT ust.hk

Ps 119 :130 The opening of Your words gives light, / Imparting understanding to the simple.

Recruiting

I'm looking for postdoctoral researchers, research assistants and PhD/MPhil students in topics of LLM-related applications

Research Interests & Services

Human-centered AI, data-centric approaches, foundation model applications
PC/reviewers for ICLR, ICML, NeurIPS, IJCAI, AAAI, ICDE, etc.

Selected Publications [DBLP, Google Scholar]

R Qi, Y Zheng, Y Yang, Caleb Chen Cao, JH Hsiao, "Explanation strategies in humans versus current explainable artificial intelligence: Insights from image classification", British Journal of Psychology'24
J Zhang, L Wang, D Su, Y Huang, Caleb Chen Cao, L Chen, "Model Debiasing via Gradient-based Explanation on Representation", AIES'23
W Xie, XH Li, Z Lin, LKM Poon, Caleb Chen Cao, NL Zhang, "Two-stage holistic and contrastive explanation of image classification", UAI'23
Tong Li, Jialei Deng, Yanyan Shen, Luyu Qiu, Yongxiang Huang, Caleb Chen Cao, "Towards fine-grained explainability for heterogeneous graph neural network", AAAI'23
Yating Wei,..., Caleb Chen Cao, et al., "Visual Diagnostics of Parallel Performance in Training Large-Scale DNN Models", TVCG'23
Rusheng Pan,..., Caleb Chen Cao, et al., "Towards Efficient Visual Simplification of Computational Graphs in Deep Neural Networks", TVCG'22
Runjin Chen, Tong Li, Yanyan Shen, Luyu Qiu, Kaidi Li, Caleb Chen Cao, "GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases", CIKM'22
Yi Yang, Yueyuan Zheng, Didan Deng, Jindi Zhang, Yongxiang Huang, Yumeng Yang, Janet H Hsiao, Caleb Chen Cao, "HSI: Human Saliency Imitator for Benchmarking Saliency-Based Model Explanations", HCOMP'22
Shendi Wang, Haoyang Li, Caleb Chen Cao, et al., "Tower Bridge Net (TB-Net): Bidirectional Knowledge Graph Aware Embedding Propagation for Explainable Recommender Systems", ICDE'22
Luyu Qiu, Yi Yang, Caleb Chen Cao, et al., "Generating perturbation-based explanations with robustness to out-of-distribution data", WWW'22
Ge Lv, Lei Chen, Caleb Chen Cao, "On Glocal Explainability of Graph Neural Networks", DASFAA'22
Xiao-Hui Li, Yuhan Shi, Haoyang Li, Wei Bai, Caleb Chen Cao, Lei Chen, "An experimental study of quantitative evaluations on saliency methods", KDD'21
Cong Wang, Xiao-Hui Li, Haocheng Han, Shendi Wang, Luning Wang, Caleb Chen Cao, Lei Chen, "Counterfactual explanations in explainable AI: a tutorial", KDD'21 Tutorial
Janet Hui-wen Hsiao, Hilary Hei Ting Ngai, Luyu Qiu, Yi Yang, Caleb Chen Cao, "Roadmap of designing cognitive metrics for explainable artificial intelligence (XAI)", arXiv'21
Xiao-hui Li, Caleb Chen Cao, et al., "A Survey of Data-driven and Knowledge-aware eXplainable AI", TKDE'20
Caleb Chen Cao, Jiayang Tu, Zheng Liu, Lei Chen, H. V. Jagadish, “Tuning Crowd- sourced Human Computation”, ICDE’17, San Diego, California
Jieying She, Yongxin Tong, Lei Chen, Caleb Chen Cao, “Conflict-Aware Event- Participant Arrangement and Its Variant for Online Setting”, TKDE’16
Rui Meng, Yongxin Tong, Caleb Chen Cao, Lei Chen, “CrowdTC:Crowdsourced Taxonomy Construction”, ICDM’15, Atlantic City, U.S.
Jieying She, Yongxin Tong, Lei Chen, Caleb Chen Cao, “Conflict-aware event- participant arrangement”, ICDE’15, Seoul, Korea
Zhao Chen et al., Caleb Chen Cao, Yongxin Tong, Chen Zhang, “gMission: A General Spatial Crowdsourcing Platform”, VLDB’14, Hangzhou, China
Caleb Chen Cao, Lei Chen, H.V. Jagadish, “From labor to trader: opinion elicitation via online crowds as a market”, KDD’14, New York, U.S.
Yongxin Tong, Caleb Chen Cao, Chen Jason Zhang, Yatao Li, Lei Chen, "CrowdCleaner: Data Cleaning For Multi-Version Data on the Web via Crowdsourcing", ICDE 2014(demo), Chicago, USA
Leihao Xia, Caleb Chen Cao, Lei Chen, Zhao Chen, "C-DMr: Crowd-powered Decision Maker for Real Knapsack Problems", ICDE 2014(demo), Chicago, USA
Yongxin Tong, Caleb Chen Cao, Lei Chen, “TCS: efficient topic discovery over crowd-oriented service data”, KDD’14, New York, U.S.
Chen Zhang, Ziyuan Zhao, Lei Chen, H.V. Jagadish, Caleb Chen Cao, “Crowd- Matcher: crowd-assisted schema matching.”, SIGMOD’14, Salt Lake City, U.S.
Caleb Chen Cao, Yongxin Tong, Lei Chen, H.V. Jagadish, "WiseMarket: A New Paradigm for Managing Wisdom of Online Social Users", KDD 2013, Chicago, USA[pdf] [slides] [bibtex]
Chen Jason Zhang, Lei Chen, H. V. Jagadish, Caleb Chen Cao, "Reducing Uncertainty of Schema Matching via Crowdsourcing", VLDB 2013, Trento, Italy
Caleb Chen Cao, Jieying She, Yongxin Tong, Lei Chen, "Whom to Ask? Jury Selection for Decision Making Tasks on Microblog Services", VLDB 2012, Istanbul, Turkey[pdf] [slides] [bibtex]