Computer Science and Engineering

Dr. Mohammad Shafiul Alam

Research Interests

• Machine Learning
• Swarm Intelligence
• Evolutionary Algorithm
• Adaptive System

Educational Background

• Ph.D, (Computer Science and Engineering), Bangladesh University of Engineering and Technology
• Master of Science (MSc), (Computer Science and Engineering), Bangladesh University of Engineering and Technology
• Bachelor of Science (BSc), (Computer Science and Engineering), Bangladesh University of Engineering and Technology

Honors and Achievements

Publications

1. Transformer-based deep learning model for stock price prediction: A case study on Bangladesh stock market, International Journal of Computational Intelligence and Applications, 2023, World Scientific Publishing Company.
2. Depression Detection From Social Networks Data Based on Machine Learning and Deep Learning Techniques: An Interrogative Survey, IEEE Transactions on Computational Social Systems, 2023, IEEE.
3. Convolutional auto-encoder and independent component analysis based automatic place recognition for moving robot in invariant season condition, Human-Centric Intelligent Systems, 2023, Springer Netherlands Dordrecht.
4. An Approach of Adjusting the Switch Probability based on Dimension Size: A Case Study for Performance Improvement of the Flower Pollination Algorithm, arXiv preprint arXiv:2208.09699, 2022.
5. Adaptive Flower Pollination Algorithm: A Novel Approach for Function Optimization Problem, Communications on Applied Electronics, 2019, Foundation of Computer Science, NY, USA. URL
6. Tuning Exploitation and Exploration for Flower Pollination Algorithm: A Case Study on Function Optimization Problem, International Journal of Applied Information Systems, 2019, Foundation of Computer Science, NY, USA.
7. Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem, Communications on Applied Electronics, 2018, Foundation of Computer Science (FCS), NY, USA.
8. Flower Pollination Algorithm with Linearly Varying Exploration: A Novel Approach for Continuous Function Optimization Problem, Communications on Applied Electronics, 2018, Foundation of Computer Science (FCS), NY, USA.
9. Comparison between fast evolutionary programming and artificial bee colony algorithm on numeric function optimization problems, 2015, International Journal of Science and Research (IJSR).
10. Explorative artificial bee colony algorithm: A novel swarm intelligence based algorithm for continuous function optimization, International Journal of Science and Research (IJSR), 2015.
11. On the Performance of Explorative Artificial Bee Colony Algorithm for Numeric Function Optimization, International Journal of Applied Information Systems (IJAIS)--ISSN, 2015.
12. A comparative study of flower pollination algorithm and bat algorithm on continuous optimization problems, International Journal of Soft Computing and Engineering, 2014.
13. Bat algorithm with self-adaptive mutation: a comparative study on numerical optimization problems, International Journal of Computer Applications, 2014, Foundation of Computer Science.
14. A novel adaptive bat algorithm to control explorations and exploitations for continuous optimization problems, International Journal of Computer Applications, 2014, Citeseer.
15. Diversity Guided Evolutionary Programming: A novel approach for continuous optimization, Applied soft computing, 2012, Elsevier.
16. Recurring two-stage evolutionary programming: A novel approach for numeric optimization, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2011, IEEE.

1. Credit Card Fraud Detection using Data Pre-processing on Imbalanced Data — both Oversampling and Undersampling, International Conference on Computing Advancements (ICCA), 2020, Association for Computing Machinery (ACM), Inc. URL
2. Hybridization of Evolutionary and Swarm Intelligence Algorithms for Improved Performance: A Case Study with TSP Problem, International Conference on Computing Advancements (ICCA), 2020.
3. A Novel Hybrid Swarm Intelligence Algorithm Combining Modified Artificial Bee Colony and Firefly Algorithms: Performance Evaluation on Continuous Function Optimization Problems, International Joint Conference on Computational Intelligence (IJCCI), 2019.
4. Employing Machine Learning Techniques on Sentiment Analysis of Google Play Store Bangla Reviews, International Conference on Computer and Information Technology (ICCIT), 2019.
5. Self Adaptive Hybrid Model Between Artificial Bee Colony and Differential Evolution Algorithms for Function Optimization Problem, International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017.

1. Classification of Potato Disease with Digital Image Processing Technique: A Hybrid Deep Learning Framework, 2023.
2. An Overview of Bengali Speech Recognition: Methods, Challenges, and Future Direction, 2023.
3. A Multi-modal Deep Learning Approach for Predicting Dhaka Stock Exchange, 2023.
4. A hybrid method based on machine learning to predict the stock prices in bangladesh, 2022.
5. Covid-19 prediction based on infected cases and deaths of bangladesh using deep transfer learning, 2022.
6. Apriori-backed fuzzy unification and statistical inference in feature reduction: An application in prognosis of autism in toddlers, 2021.
7. A data-driven hybrid optimization based deep network model for short-term residential load forecasting, 2021.
8. A Novel Hybrid Swarm Intelligence Algorithm Combining Modified Artificial, 2020.
9. A novel comparative study between dual population genetic algorithm and artificial bee colony algorithm for function optimization, 2016.
10. Ensemble approach for improving generalization ability of neural networks, 2013.
11. Artificial bee colony algorithm with improved explorations for numerical function optimization, 2012.
12. Artificial Bee Colony algorithm with Self-Adaptive Mutation: A novel approach for numeric optimization, 2011.
13. Self-adaptation of mutation step size in artificial bee colony algorithm for continuous function optimization, 2010.
14. A two-layer hierarchical permission based mutual exclusion algorithm, 2009.
15. A scheme for the solutions of the h-out of-k mutual exclusion problems using k-arbiters, 2007.