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AHSANULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Department of

Computer Science and Engineering




Mr. H M Zabir Haque



Designation: Assistant Professor

Email: zabir.haque.cse@aust.edu

Office Extension: 516

Room No: 7A01 / K



Research Interests

  • Bioinformatics and Computational Biology
  • Machine Learning

Educational Background

  • Master of Science (MSc), (Bioinformatics), University of Saskatchewan (UofS), Canada
  • Bachelor of Science (BSc), (Computer Science and Engineering), Ahsanullah University of Science and Technology (AUST), Bangladesh

Honors and Achievements

  • International Dean's Scholarship, University of Saskatchewan, Canada, 2016

Publications

Book Chapter
Journal Article
  1. Depression Detection Through Smartphone Sensing: A Federated Learning Approach, International Journal of Interactive Mobile Technologies (iJIM), 2023, Kassel University Press GmbH. URL
  2. A Novel Approach for Product Recommendation Using Smartphone Sensor Data, International Journal of Interactive Mobile Technologies, 2022, Kassel University Press GmbH. URL
  3. An Integrated Crowdsourcing Application for Embedded Smartphone Sensor Data Acquisition and Mobility Analysis, Journal of Advances in Information Technology, 2022, Engineering and Technology Publishing. URL
  4. Prediction of Academic Performance Applying NNs: A Focus on Statistical Feature-Shedding and Lifestyle, International Journal of Advanced Computer Science and Applications, 2019, The Science and Information Organization. URL
  5. Balancing Complementary Exploitations and Explorations in Evolutionary Algorithms, International Journal of Information and Communication, 2015.
Conference Proceedings
  1. AutoAct: An Auto Labeling Approach Based on Activities of Daily Living in the Wild Domain, 10th International Conference on Informatics, Electronics & Vision (ICIEV), 2021, IEEE Xplore. URL
Others
  1. Predicting Behavior Trends among Students Based on Personality Traits, ICCA 2020: International Conference on Computing Advancement, 2020, Association for Computing Machinery, New York, United States. URL
  2. Sample Size Evaluation and Comparison of K-Means Clusterings of RNA-Seq Gene Expression Data, 2018. URL