Chawla, Nitesh V.

SMOTE synthetic minority over-sampling technique

Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002) · Journal of Artificial Intelligence Research

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 32,865

Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Guo, T., Chen, X., Wang, Y., Chang, R., Pei, S., Chawla, N. V., Wiest, O., & Zhang, X. (2024) · arXiv

Multi-Agent Systems and NegotiationAI-based Problem Solving and Planning

Cited by 1,713

Heterogeneous Graph Neural Network

Zhang, C., Song, D., Huang, C., Swami, A., & Chawla, N. V. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Advanced Graph Neural NetworksRecommender Systems and Techniques

Cited by 1,591

A unifying view on dataset shift in classification

Moreno-Torres, J. G., Raeder, T., Alaiz-Rodríguez, R., Chawla, N. V., & Herrera, F. (2012) · Pattern Recognition

Domain Adaptation and Few-Shot LearningData Stream Mining Techniques

Cited by 1,029

Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework

Chawla, N. V., & Davis, D. A. (2013) · Journal of General Internal Medicine

Artificial Intelligence in HealthcareElectronic Health Records Systems

Cited by 440

G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

He, X., Tian, Y., Sun, Y., Chawla, N. V., Laurent, T., LeCun, Y., Bresson, X., & Hooi, B. (2024) · arXiv

Topic ModelingAdvanced Graph Neural Networks

Cited by 122

“Engagement vs. performance: using electronic portfolios to predict first semester engineering student retention,”

Aguiar, E., Chawla, N. V., Brockman, J., Ambrose, G. A., & Goodrich, V. (2014) · Proceedings of the Fourth International Conference on Learning Analytics And Knowledge

Online Learning and AnalyticsEvasion and Academic Success Factors

Cited by 69

Social network structure is predictive of health and wellness

Lin, S., Faust, L., Robles-Granda, P., Kajdanowicz, T., & Chawla, N. V. (2019) · PLOS ONE

Mental Health Research TopicsHealth and Lifestyle Studies

Cited by 41

MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation

Zhang, Z., Wang, Z., Ma, T., Taneja, V. S., Nelson, S., Le, N. H. L., Murugesan, K., Ju, M., Chawla, N. V., Zhang, C., et al. (2025) · Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1

Recommender Systems and TechniquesInnovation in Digital Healthcare Systems

Cited by 16

Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge

Ye, J., Wang, Y., Huang, Y., Chen, D., Zhang, Q., Moniz, N., Gao, T., Geyer, W., Huang, C., Chen, P.-Y., et al. (2024) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence in Law

Cited by 11

LLMs4All: A Review of Large Language Models Across Academic Disciplines

Ye, Y., Zhang, Z., Ma, T., Wang, Z., Li, Y., Hou, S., Sun, W., Shi, K., Ma, Y., Song, W., et al. (2025) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 8

NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning

Zhang, Z., Li, Y., Le, N. H. L., Wang, Z., Ma, T., Galassi, V., Murugesan, K., Moniz, N., Geyer, W., Chawla, N. V., et al. (2024) · arXiv

Advanced Graph Neural NetworksTopic Modeling

Cited by 2

Do the Young Live in a "Smaller World" Than the Old? Age-Specific Degrees of Separation in Human Communication

Dong, Y., Lizardo, O., & Chawla, N. V. (2016) · arXiv

Complex Network Analysis TechniquesContemporary Social and Educational Issues

Cited by 1