Bo Dai

3.7k total citations · 1 hit paper
53 papers, 1.2k citations indexed

About

Bo Dai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Bo Dai has authored 53 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 24 papers in Computer Vision and Pattern Recognition and 5 papers in Computational Mechanics. Recurrent topics in Bo Dai's work include Domain Adaptation and Few-Shot Learning (9 papers), Human Pose and Action Recognition (9 papers) and Advanced Neural Network Applications (7 papers). Bo Dai is often cited by papers focused on Domain Adaptation and Few-Shot Learning (9 papers), Human Pose and Action Recognition (9 papers) and Advanced Neural Network Applications (7 papers). Bo Dai collaborates with scholars based in United States, China and Hong Kong. Bo Dai's co-authors include Dahua Lin, Haodong Duan, Yue Zhao, Kai Chen, Ying Liu, Dongxiang Zhang, Loo Hay Lee, Wang Yuan, Le Song and Hanjun Dai and has published in prestigious journals such as SHILAP Revista de lepidopterología, Analytical Biochemistry and Chemical Engineering Science.

In The Last Decade

Bo Dai

50 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Revisiting Skeleton-based Action Recognition

2022 417 citations Dahua Lin, Bo Dai et al. profile →

Peers

Countries citing papers authored by Bo Dai

Since Specialization

Citations

This map shows the geographic impact of Bo Dai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bo Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Dai more than expected).

Fields of papers citing papers by Bo Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bo Dai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bo Dai. The network helps show where Bo Dai may publish in the future.

Co-authorship network of co-authors of Bo Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Bo Dai. A scholar is included among the top collaborators of Bo Dai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bo Dai. Bo Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Dam early warning model based on structural anomaly identification and dynamic effect variables selection 2025 ·Structures ·(unknown), (unknown), Bo Dai, Junru Li	1
2	A reliability-enhanced Brain–Computer Interface via Mixture-of-Graphs-driven Information Fusion 2025 ·Information Fusion ·Bo Dai, Yijun Wang, (unknown), Xiaorong Gao	1
3	Horizon-Gs: Unified 3D Gaussian Splatting for Large-Scale Aerial-To-Ground Scenes 2025 ·(unknown), (unknown), (unknown), Linning Xu, (unknown), Tao Lu, Feng Zhao, Dahua Lin, Bo Dai	1
4	HireVAE: An Online and Adaptive Factor Model Based on Hierarchical and Regime-Switch VAE 2023 ·(unknown), Anyi Rao, Bo Dai, Dahua Lin	0
5	A Multi-Label Classification Method Based On Textual Data Mining 2023 ·(unknown), Bo Dai, (unknown)	0
6	LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs 2021 ·International Conference on Machine Learning ·Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou	20
7	Analysis of Industrial Internet of Things and Digital Twins 2021 ·ZTE communications ·Jie Tan, (unknown), Bo Dai, (unknown)	5
8	Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach 2020 ·Neural Information Processing Systems ·(unknown), (unknown), Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang	2
9	Differentiable Top-k with Optimal Transport 2020 ·Neural Information Processing Systems ·Yujia Xie, Hanjun Dai, (unknown), Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister	17
10	CoinDICE: Off-Policy Confidence Interval Estimation 2020 ·arXiv (Cornell University) ·Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans	1
11	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections 2019 ·arXiv (Cornell University) ·Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li	10
12	Decoupled Networks 2018 ·arXiv (Cornell University) ·Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, (unknown), Yisen Wang, James M. Rehg, Le Song	7
13	Syntax-Directed Variational Autoencoder for Structured Data 2018 ·International Conference on Learning Representations ·Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song	8
14	Smoothed Dual Embedding Control. 2017 ·arXiv (Cornell University) ·Bo Dai, (unknown), Lihong Li, (unknown), Niao He, Jianshu Chen, Le Song	2
15	Iterative machine teaching 2017 ·International Conference on Machine Learning ·Weiyang Liu, Bo Dai, Ahmad Humayun, (unknown), Yu Chen, Linda B. Smith, James M. Rehg, Le Song	17
16	Recurrent Hidden Semi-Markov Model 2017 ·International Conference on Learning Representations ·Hanjun Dai, Bo Dai, Yan‐Ming Zhang, (unknown), Le Song	12
17	Deep Hyperspherical Learning 2017 ·Neural Information Processing Systems ·Weiyang Liu, Yan‐Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song	21
18	Robust Low Rank Kernel Embeddings of Multivariate Distributions 2013 ·Neural Information Processing Systems ·Le Song, Bo Dai	11
19	Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning 2013 ·International Conference on Machine Learning ·Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama	21
20	Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering 2010 ·Asian Conference on Machine Learning ·Bo Dai, Bao-Gang Hu	6

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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