Computer Science and Engineering

Prof. Dr. Md. Shahriar Mahbub

Research Interests

Educational Background

• Ph.D, (Information and Communication Technology), University of Trento, Italy
• Master of Science (MSc), (Advanced Computing Systems), Lucian Blaga university of Sibiu, Romania
• Bachelor of Science (BSc), (Computer Science and Engineering), Ahsanullah university of science and Technology

Honors and Achievements

Publications

• Bengali Fake Review Detection using Semi-supervised Generative Adversarial Networks, 5th International Conference on Natural Language Processing (ICNLP), 2023
• Multi-objective optimization of an energy community: an integrated and dynamic approach for full decarbonisation in the European Alps, International Journal of Sustainable Energy Planning and Management, 2023
• Cricketer’s tournament-wise performance prediction and squad selection using machine learning and multi-objective optimization, Applied Soft Computing, 2022
• Decentralizing and Optimizing Nation-Wide Employee Allocation While Simultaneously Maximizing Employee Satisfaction, International Conference on Optimization and Learning, 2022
• A multi-objective optimization approach in defining the decarbonization strategy of a refinery, Smart Energy, 2022
• Soft Constraints Handling for Multi-objective Optimization, 2021
• A Multi-Objective Optimization Approach for Solving AUST Classtimetable Problem Considering Hard and Soft Constraints, International Journal of Mathematical Sciences and Computing(IJMSC), 2020
• A comparative study on constraint handling techniques of NSGAII, 2020
• Integrated and dynamic energy modelling of a regional system: A cost-optimized approach in the deep decarbonisation of the Province of Trento (Italy), Energy, 2020
• Energy efficiency and sustainability assessment of about 500 small and medium-sized enterprises in Central Europe region, Energy Policy, 2017
• An innovative multi-objective optimization approach for long-term energy planning, Applied Energy, 2017
• Development of innovative tools for multi-objective optimization of energy systems, 2017
• Multi-objective optimisation with multiple preferred regions, 2017
• Incorporating domain knowledge into the optimization of energy systems, Applied Soft Computing, 2016
• Combining multi-objective evolutionary algorithms and descriptive analytical modelling in energy scenario design, Applied Energy, 2016
• Designing optimized energy scenarios for an Italian Alpine valley: the case of Giudicarie Esteriori, Energy, 2016
• Improving robustness of stopping multi-objective evolutionary algorithms by simultaneously monitoring objective and decision space, 2015
• Developing domain-knowledge evolutionary algorithms for network-on-chip application mapping, Microprocessors and Microsystems, 2013
• Isolating significant phrases in common natural language queries to databases, 2008