The University of Nottingham · School of Computer Science
Dr Chao Chen
Member of the Laboratory for Uncertainty in Data and Decision Making (LUCID) and the Intelligent Modelling and Analysis (IMA) Research Group. His research mainly addresses a central tension in AI: how to improve predictive performance without sacrificing interpretability. His work advances optimisation methods for inherently interpretable models, especially fuzzy inference systems, combining gradient-based, differentiable, and hybrid approaches to narrow the performance gap with modern deep learning while preserving transparent reasoning and principled uncertainty handling.
Latest News
View all →Selected Publications
View all →C Chen, JM Mendel, JM Garibaldi · IEEE Transactions on Fuzzy Systems 2025
F Abbasov, C Chen, JM Garibaldi · IEEE International Conference on Fuzzy Systems 2025
Q Lin, X Chen, C Chen, JM Garibaldi · Information Sciences 2024
Open-Source Software
An open-source Fuzzy Logic Toolkit for the R programming language. Supports design, simulation, and optimisation of type-1 and interval type-2 fuzzy inference systems — used internationally for research and teaching.
Related Publications
library(FuzzyR)# Build a Type-1 Fuzzy Inference Systemfis <- newfis("temperature")fis <- addvar(fis, "input", "temp", c(0, 40))fis <- addvar(fis, "output", "fan", c(0, 100))# Define membership functionsfis <- addmf(fis, "input", 1, "cold", "trimf", c(-10, 0, 15))fis <- addmf(fis, "input", 1, "warm", "trimf", c( 10, 22, 30))fis <- addmf(fis, "input", 1, "hot", "trimf", c( 25, 40, 50))# Add rules and evaluatefis <- addrule(fis, c(1,1,1,1))evalfis(25, fis) # → 65.0