| 2026 | ICPR | LiteAugNet: A Lightweight Semantic-Guided Augmentation Network for Efficient Edge-Level Image Classification. | Mohammad Shahedur Rahman, Mohammad Tahmid Bari, Md. Nasim Adnan, Arshad Parvez |
| 2023 | ADMA | Exploration of Stochastic Selection of Splitting Attributes as a Source of Inducing Diversity. | Md. Nasim Adnan |
| 2022 | ADMA | On Reducing the Bias of Random Forest. | Md. Nasim Adnan |
| 2018 | ADMA | On Improving the Prediction Accuracy of a Decision Tree Using Genetic Algorithm. | Md. Nasim Adnan, Md Zahidul Islam, Md. Mostofa Akbar |
| 2017 | ADMA | Effects of Dynamic Subspacing in Random Forest. | Md. Nasim Adnan, Md Zahidul Islam |
| 2016 | ADMA | On Improving Random Forest for Hard-to-Classify Records. | Md. Nasim Adnan, Md Zahidul Islam |
| 2016 | PAKDD | Forest CERN: A New Decision Forest Building Technique. | Md. Nasim Adnan, Md Zahidul Islam |
| 2015 | AusDM | Complement Random Forest. | Md. Nasim Adnan, Md Zahidul Islam |
| 2015 | ESANN | One-vs-all binarization technique in the context of random forest. | Md. Nasim Adnan, Md Zahidul Islam |
| 2015 | ESANN | Improving the random forest algorithm by randomly varying the size of the bootstrap samples for low dimensional data sets. | Md. Nasim Adnan, Md Zahidul Islam |
| 2014 | ADMA | On Dynamic Selection of Subspace for Random Forest. | Md. Nasim Adnan |
| 2014 | ICMLC | Extended Space Decision Tree. | Md. Nasim Adnan, Md Zahidul Islam, Paul Wing Hing Kwan |
| 2014 | IRI | Improving the random forest algorithm by randomly varying the size of the bootstrap samples. | Md. Nasim Adnan |