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Department of

Computer Science and Engineering

Dr. Md. Shahriar Mahbub

Designation: Professor


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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


  • 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
  • Bengali Fake Review Detection using Semi-supervised Generative Adversarial Networks, 5th International Conference on Natural Language Processing (ICNLP), 2023
  • A multi-objective optimization approach in defining the decarbonization strategy of a refinery, Smart Energy, 2022
  • 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
  • Soft Constraints Handling for Multi-objective Optimization, 2021
  • 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
  • A Multi-Objective Optimization Approach for Solving AUST Classtimetable Problem Considering Hard and Soft Constraints, International Journal of Mathematical Sciences and Computing(IJMSC), 2020
  • Development of innovative tools for multi-objective optimization of energy systems, 2017
  • An innovative multi-objective optimization approach for long-term energy planning, Applied Energy, 2017
  • Multi-objective optimisation with multiple preferred regions, 2017
  • Energy efficiency and sustainability assessment of about 500 small and medium-sized enterprises in Central Europe region, Energy Policy, 2017
  • 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
  • Incorporating domain knowledge into the optimization of energy systems, Applied Soft Computing, 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