2026 Jinbo Bi: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	43	7947	7720	3423	3294	170	8429

Overview

Jinbo Bi is affiliated with the University of Connecticut in the United States and has a publication record chiefly in the field of Computer Science, with a particular focus on Artificial Intelligence. Their research spans multiple subfields including Experimental and Cognitive Psychology, Computational Mechanics, Molecular Biology, and Computational Theory and Mathematics.

Their recent scholarly output includes work published in recognized venues such as IEEE Transactions on Artificial Intelligence, Polymers, BMC Bioinformatics, Smart Health, and the Proceedings of the ACM/IEEE Design Automation Conference. Some of their recent papers are:

A Survey on Multiview Clustering, 2021, IEEE Transactions on Artificial Intelligence
Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges, 2020, Polymers
Convolutional neural network for automated mass segmentation in mammography, 2020, BMC Bioinformatics
GaitCode: Gait-based continuous authentication using multimodal learning and wearable sensors, 2020, Smart Health
A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining, 2022, Proceedings of the ACM/IEEE Design Automation Conference

Frequent publication venues where Jinbo Bi has contributed multiple papers include:

arXiv (Cornell University)
Smart Health
Proceedings of the AAAI Conference on Artificial Intelligence
IEEE Internet of Things Journal
Neurocomputing

The scientist works collaboratively, with frequent coauthors being Guannan Liang, Chunjiang Zhu, Qianqian Tong, Tan Zhu, and Minghu Song, indicating active research partnerships.

Jinbo Bi's research topics cover diverse areas intersecting computer science and applied sciences. Prominent topics addressed include:

Stochastic Gradient Optimization Techniques
Sparse and Compressive Sensing Techniques
Mental Health Research Topics
Computational Drug Discovery Methods
Privacy-Preserving Technologies in Data
Machine Learning in Materials Science
Digital Mental Health Interventions

This breadth of topics reflects an interdisciplinary approach, incorporating machine learning methods into materials science and health-related applications. The scientist's work involves both theoretical development and practical algorithm design with implications for artificial intelligence, healthcare, and molecular sciences.

Best Publications

MILES: Multiple-Instance Learning via Embedded Instance Selection

Yixin Chen;Jinbo Bi;J.Z. Wang

971
Citations
Dimensionality reduction via sparse support vector machines

Jinbo Bi;Kristin Bennett;Mark Embrechts;Curt Breneman

610
Citations
End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

Chao Shang;Yun Tang;Jing Huang;Jinbo Bi

552
Citations
Active learning via transductive experimental design

Kai Yu;Jinbo Bi;Volker Tresp

421
Citations
A Survey on Multiview Clustering

Guoqing Chao;Shiliang Sun;Jinbo Bi

350
Citations
Regression error characteristic curves

Jinbo Bi;Kristin P. Bennett

303
Citations
Support Vector Classification with Input Data Uncertainty

Jinbo Bi;Tong Zhang

266
Citations
Prediction of protein retention times in anion-exchange chromatography systems using support vector regression.

Minghu Song;Curt M. Breneman;Jinbo Bi;Nagamani Sukumar

223
Citations
Bayesian multiple instance learning: automatic feature selection and inductive transfer

Vikas C. Raykar;Balaji Krishnapuram;Jinbo Bi;Murat Dundar

180
Citations
Machine learning identification of EEG features predicting working memory performance in schizophrenia and healthy adults

Jason K. Johannesen;Jinbo Bi;Ruhua Jiang;Joshua G. Kenney

171
Citations
A Geometric Approach to Support Vector Regression

Jinbo Bi;Kristin P. Bennett

144
Citations
A Survey on Multi-View Clustering

Guoqing Chao;Shiliang Sun;Jinbo Bi

134
Citations
VIGAN: Missing view imputation with generative adversarial networks

Chao Shang;Aaron Palmer;Jiangwen Sun;Ko-Shin Chen

129
Citations
Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data

Asma Ahmad Farhan;Chaoqun Yue;Reynaldo Morillo;Shweta Ware

122
Citations
Column-generation boosting methods for mixture of kernels

Jinbo Bi;Tong Zhang;Kristin P. Bennett

112
Citations
Discrete Graph Structure Learning for Forecasting Multiple Time Series

Chao Shang;Jie Chen;Jinbo Bi

104
Citations
An Improved Multi-task Learning Approach with Applications in Medical Diagnosis

Jinbo Bi;Tao Xiong;Shipeng Yu;Murat Dundar

103
Citations
A sparse support vector machine approach to region-based image categorization

Jinbo Bi;Yixin Chen;J.Z. Wang

92
Citations
Computer aided detection of pulmonary embolism with tobogganing and mutiple instance classification in CT pulmonary angiography

Jianming Liang;Jinbo Bi

91
Citations
Stratified learning of local anatomical context for lung nodules in CT images

Dijia Wu;Le Lu;Jinbo Bi;Yoshihisa Shinagawa

89
Citations
Edge Attention-based Multi-Relational Graph Convolutional Networks

Chao Shang;Qinqing Liu;Ko-Shin Chen;Jiangwen Sun

81
Citations
Prediction of protein retention times in anion-exchange chromatography systems using support vector regression

Curt M. Breneman;Minghu Song;Jinbo Bi;N. Sukumar

0
Citations

Frequent Co-Authors

Glenn Fung American Family Insurance

Shipeng Yu Pinterest

Le Lu Alibaba Group (China)

Alexander Russell University of Connecticut

Jianming Liang Arizona State University

Kristin P. Bennett Rensselaer Polytechnic Institute

Sanguthevar Rajasekaran University of Connecticut

Xiao-Ping Zhou Chongqing University

Arun Krishnan Microsoft (United States)

Joel Gelernter Yale University

External Links

Personal website of Jinbo Bi Google Scholar page

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