Dr. Yanhui Zhu is an Assistant Professor in the School of Computing at Montclair State University with a concentration on algorithms and trustworthy AI. He earned his Ph.D. in Computer Science from Iowa State University in May 2025, proudly advised by Prof. Pavan Aduri and Prof. Samik Basu. He received an MS in Data Science from the University of West Florida.

Dr. Yanhui Zhu founded the Algorithmic Intelligence Lab (AIL) at Montclair State University. His group develops rigorous and efficient algorithms for constrained submodular optimization problems and investigates their broad applications in AI, machine learning, and network science.

Research

• Theory and Algorithms: approximation algorithms, submodular optimization, etc.

• Application of submodular optimization: feature selection, recommender systems, influence maximization, and data summarization.

• Graph Mining: community detection in complex networks and influence diffusion in social networks.

• Data Science (interdisciplinary research): data modeling in structural/networked datasets, big data analysis.

Publications

• A learning-augmented framework for knapsack-constrained submodular maximization problems. 

Y Zhu. 

LATA Workshop, ACM SIGMETRICS 2026

• Large language models for intelligent healthcare and medicine: A systematic survey. 

C Wu, Y Zhu. 

Advanced IntelliEngineering

• Fairness in monotone k-submodular maximization: algorithms and applications. 

Y Zhu, S Basu, A Pavan. 

IEEE BigData 2024

• Submodular optimization: variants, theory and applications. 

Y Zhu.

CIKM 2024

• Regularized unconstrained weakly submodular maximization. 

Y Zhu, S Basu, A Pavan. 

CIKM 2024

• Improved evolutionary algorithms for submodular maximization with cost constraints. 

Y Zhu, S Basu, A Pavan. 

IJCAI 2024

• SCOREH+: a high-order node proximity spectral clustering on ratios-of-eigenvectors algorithm for community detection. 

Y Zhu, F Hu, LH Kuo, J Liu. 

IEEE Transactions on Big Data 2024

• A framework for adapting offline algorithms to solve combinatorial multi-armed bandit problems with bandit feedback. 

G Nie, YY Nadew, Y Zhu, V Aggarwal, CJ Quinn. 

ICML 2023

• Size-constrained k-submodular maximization in near-linear time. 

G Nie, Y Zhu, YY Nadew, S Basu, A Pavan, CJ Quinn. 

UAI 2023

• Maximizing submodular functions under submodular constraints. 

MR Padmanabhan, Y Zhu, S Basu, A Pavan. 

UAI 2023

• Sedimentary environment prediction of grain-size data based on machine learning approach. 

Q Su, Y Zhu, F Hu, X Xu. 

Interpretation

• An efficient long short-term memory model based on Laplacian eigenmap in artificial neural networks. 

F Hu, Y Zhu, J Liu, L Li. 

Applied Soft Computing

• Prediction and analysis of net ecosystem carbon exchange based on gradient boosting regression and random forest. 

J Cai, K Xu, Y Zhu, F Hu, L Li. 

Applied energy

Highly Cited Paper

• Computing communities in complex networks using the Dirichlet processing Gaussian mixture model with spectral clustering. 

F Hu, Y Zhu, J Liu, Y Jia. 

Physics Letters A

• A time simulated annealing-back propagation algorithm and its application in disease prediction. 

F Hu, M Wang, Y Zhu, J Liu, Y Jia. 

Modern Physics Letters B

• Sedimentary environment analysis by grain‐size data based on mini batch k‐means algorithm. 

Q Su, Y Zhu, Y Jia, P Li, F Hu, X Xu. 

Geofluids

• An algorithm J-SC of detecting communities in complex networks. 

F Hu, M Wang, Y Wang, Z Hong, Y Zhu. 

Physics Letters A

• Symptom distribution regulation of core symptoms in insomnia based on informap-sa algorithm. 

F Hu, Y Qiao, G Xie, Y Zhu, Y Jia, PP Huang. 

2017 16th International Symposium on Distributed Computing and Applications

Students

• Ariel Balcacer (Spring 2026 - )

Teaching

Instructor, Montclair State University

• • CSIT 379 Computer Science Theory, Fa26, Sp26, Fa25.

  • CSIT 170 Discrete Mathematics, Su26

Course Developer, Montclair State University

• • CSIT 571 Computer Algorithms and Analysis (Unbounded)