About Me
Hello there! I’m a Postdoctoral Researcher in the Department of Computer Science and Engineering at the University of California, Riverside, where I’m mentored by Prof. Vagelis Papalexakis. My current work focuses on developing machine learning methods to address challenges in precision agriculture.
Prior to UCR, I completed my PhD in Computer Science and Computational Mathematics at the University of São Paulo, under Prof. Alneu de Andrade Lopes where I developed graph reduction methods aimed at improving the efficiency and scalability of graph-based learning systems.
Research Interests:
- Graph Machine Learning
- Data-Centric AI and Representation Learning
- Large-Scale Data and Model Compression
- Efficient and Scalable AI Systems
- AI for Precision Agriculture
Selected Publications
Multi-view Graph Condensation via Tensor Decomposition
One-mode Projection of Bipartite Graphs for Text Classification using Graph Neural Networks
Semi-Supervised Coarsening of Bipartite Graphs for Text Classification via Graph Neural Network
Spectral Regularization for Diffusion Models
FairDIF: Debiasing Classifiers with Item Response Theory and Differential Item Functioning
Unfairness in Machine Learning for Web Systems Applications
News
- [Mar 2026] Paper accepted at WSDM 2026: Multi-view Graph Condensation via Tensor Decomposition
- [Feb 2026] Preprint out: Spectral Regularization for Diffusion Models
- [Jan 2026] Paper accepted at AI and Ethics: FairDIF: Debiasing Classifiers with Item Response Theory and Differential Item Functioning
- [Jan 2025] Started as a Postdoctoral Researcher at the University of California, Riverside
- [Dec 2025] Paper accepted at BRACIS 2025: Graph Condensation for Text Classification