| 2026 | GECCO | Teaching the Teacher: The Role of Teacher-Student Smoothness Alignment in Genetic Programming-based Symbolic Distillation. | Soumyadeep Dhar, Kei Sen Fong, Mehul Motani |
| 2026 | GECCO | Generalization Analysis of Symbolic Regression Algorithms via Stability Theory. | Kei Sen Fong, Mehul Motani |
| 2026 | GECCO | Hot off the Press: FEAT-KD: Learning Concise Representations for Single and Multi-Target Regression via TabNet Knowledge Distillation. | Kei Sen Fong, Mehul Motani |
| 2026 | GECCO | Hot off the Press: Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms. | Kei Sen Fong, Mehul Motani |
| 2026 | GECCO | Evolutionary Identification of Scientific Equations Using Language-Model-Guided Symbolic Regression. | Juncheng Zhao, Kei Sen Fong, Mehul Motani |
| 2025 | GECCO | Discovering Shared Function Structures with Adaptable Parameters for Multi-Level Modeling via Symbolic Regression. | Kei Sen Fong, Mehul Motani |
| 2025 | GECCO | SLIME: Supralocal Interpretable Model-Agnostic Explanations via Evolved Equation-Based Surrogates. | Kei Sen Fong, Mehul Motani |
| 2025 | GECCO | Mutual Information-Based Evolutionary Feature Construction via Minimizing Redundancy and Maximizing Relevance. | Yunze Leng, Kei Sen Fong, Mehul Motani |
| 2025 | GECCO | Analysis of Memory-Runtime Trade-offs in Caching Strategies for Genetic Programming Symbolic Regression. | Jiaming Shi, Kei Sen Fong, Mehul Motani |
| 2025 | ICML | Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms. | Kei Sen Fong, Mehul Motani |
| 2025 | ICML | FEAT-KD: Learning Concise Representations for Single and Multi-Target Regression via TabNet Knowledge Distillation. | Kei Sen Fong, Mehul Motani |
| 2025 | KDD | POVE: A Preoptimized Vault of Expressions for Symbolic Regression Research and Benchmarking. | Kei Sen Fong, Mehul Motani |
| 2024 | AAAI | Symbolic Regression Enhanced Decision Trees for Classification Tasks. | Kei Sen Fong, Mehul Motani |
| 2024 | AISTATS | Multi-Level Symbolic Regression: Function Structure Learning for Multi-Level Data. | Kei Sen Fong, Mehul Motani |
| 2024 | GECCO | MetaSR: A Meta-Learning Approach to Fitness Formulation for Frequency-Aware Symbolic Regression. | Kei Sen Fong, Mehul Motani |
| 2024 | GECCO | Enhancing Prediction, Explainability, Inference and Robustness of Decision Trees via Symbolic Regression-Discovered Splits. | Kei Sen Fong, Mehul Motani |
| 2024 | ICTAI | SyREC: A Symbolic-Regression-Based Ensemble Combiner. | Kei Sen Fong, Mehul Motani |
| 2023 | GECCO | DistilSR: A Distilled Version of Gene Expression Programming Symbolic Regression. | Kei Sen Fong, Mehul Motani |
| 2023 | GECCO | Evolutionary Symbolic Regression: Mechanisms from the Perspectives of Morphology and Adaptability. | Kei Sen Fong, Shelvia Wongso, Mehul Motani |
| 2023 | ICLR | Rethinking Symbolic Regression: Morphology and Adaptability in the Context of Evolutionary Algorithms. | Kei Sen Fong, Shelvia Wongso, Mehul Motani |