Dr Mohammad Haque

Dr Mohammad Haque

Research Associate

School of Electrical Engineering and Computing

Career Summary

Biography

Dr. Mohammad Nazmul Haque achieved his Doctor of Philosophy (Computer Science) degree from the University of Newcastle, Australia on 15-Feb-2017. His PhD research area was on the genetic algorithm-based ensemble of classification methods for biological data classification. Dr. Haque has interdisciplinary research experiences in data analysis, evolutionary computing and machine learning for large-scale datasets. He published several papers in peer-reviewed journals, conferences and book chapters. He possesses the analytic and biomarker discovery experiences from heterogeneous data (gene expression, images, consumer behaviour, disease datasets). 

Dr. Haque achieved his Master and Bachelor of Science in Computer Science & Engineering from Daffodil International University, Bangladesh in 2011 and 2006, respectively. Before he started the RHD candidature in Aug 2012, he was involved in academia as Lecturer at Daffodil International University, Bangladesh from 2009 to 2012. He also served as Lecturer of Computing Information Systems at Daffodil Institute of IT, Bangladesh from 2007 to 2009. Just after completing his Bachelor in 2006, he joined as Junior Software Engineer at KMC e-technology, Bangladesh. 

Dr. Haque's major research interest covers evolutionary computing, data analytics (heterogeneous data classification & knowledge discovery), artificial intelligence, machine learning, image processing and health informatics.


Qualifications

  • Doctor of Philosophy, University of Newcastle
  • Master of Science, Daffodil International University, Bangladesh

Keywords

  • Bioinformatics
  • Computer Algorithms
  • Data Analytics
  • Evolutionary Algorithms
  • Evolutionary Computation
  • Image Processing
  • Machine learning

Languages

  • Bengali (Mother)
  • English (Fluent)

Fields of Research

Code Description Percentage
080108 Neural, Evolutionary and Fuzzy Computation 40
080199 Artificial Intelligence and Image Processing not elsewhere classified 20
080109 Pattern Recognition and Data Mining 40

Professional Experience

UON Appointment

Title Organisation / Department
Research Associate University of Newcastle
School of Electrical Engineering and Computing
Australia
Casual Academic University of Newcastle
School of Electrical Engineering and Computing
Australia

Academic appointment

Dates Title Organisation / Department
29/01/2009 - 14/08/2012 Lecturer in Computer Science & Engineering Daffodil International University
Department of computer Science & Engineering
Bangladesh
1/11/2007 - 26/01/2009 Lecturer in Computing Information System


Daffodil Institute of IT
Bangladesh

Professional appointment

Dates Title Organisation / Department
10/05/2007 - 30/10/2007 Software Engineer KMC e-Technology
Bangladesh
20/06/2006 - 9/05/2007 Junior Software Engineer KMC e-Technology
Bangladesh

Awards

Prize

Year Award
2005 ACM-Solver Coding Championship
Daffodil International University

Scholarship

Year Award
2012 University of Newcastle International Postgraduate Research Scholarship
Faculty of Engineering and Built Environment - The University of Newcastle (Australia)
2012 University of Newcastle Research Scholarship Central
Faculty of Engineering and Built Environment - The University of Newcastle (Australia)

Teaching

Code Course Role Duration
INFO6002 Database Management 2
University of Newcastle - Faculty of Engineering & Built Environment
Lead Web Tutor 22/05/2017 - 31/08/2017
SENG3150 Software Project 1: Requirements Engineering and Design
University of Newcastle - Faculty of Engineering & Built Environment
Teaching Material Development 12/08/2016 - 31/12/2016
COMP2240 Operating Systems
University of Newcastle - Faculty of Engineering & Built Environment
Tutor 25/07/2016 - 31/12/2016
INFO6002 Database Management 2
University of Newcastle - Faculty of Engineering & Built Environment
Lecturer 22/05/2017 - 31/08/2017
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Publications

For publications that are currently unpublished or in-press, details are shown in italics.


Journal article (4 outputs)

Year Citation Altmetrics Link
2016 Haque MN, Noman N, Berretta R, Moscato P, 'Heterogeneous ensemble combination search using genetic algorithm for class imbalanced data classification', PLoS ONE, 11 (2016) [C1]

© 2016 Haque et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and repr... [more]

© 2016 Haque et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble's output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (a, ß) - k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer's disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases.

DOI 10.1371/journal.pone.0146116
Citations Scopus - 2
Co-authors Pablo Moscato, Regina Berretta, Nasimul Noman
2014 Whaiduzzaman M, Haque MN, Rejaul Karim Chowdhury M, Gani A, 'A study on strategic provisioning of cloud computing services.', ScientificWorldJournal, 2014 894362 (2014) [C1]
DOI 10.1155/2014/894362
Citations Scopus - 12Web of Science - 1
2014 Whaiduzzaman M, Gani A, Anuar NB, Shiraz M, Haque MN, Haque IT, 'Cloud Service Selection Using Multicriteria Decision Analysis', SCIENTIFIC WORLD JOURNAL, (2014) [C1]
DOI 10.1155/2014/459375
Citations Scopus - 28Web of Science - 14
2011 Haque MN, Uddin MS, 'Accelerating Fast Fourier Transformation for Image Processing using Graphics Processing Unit', Journal of Emerging Trends in Computing and Information Sciences, 2 367-375 (2011) [C1]
Show 1 more journal article

Conference (2 outputs)

Year Citation Altmetrics Link
2016 Haque MN, Noman N, Berretta R, Moscato P, 'Optimising weights for heterogeneous ensemble of classifiers with differential evolution', 2016 IEEE Congress on Evolutionary Computation (CEC) (2016) [E1]
DOI 10.1109/CEC.2016.7743800
Co-authors Regina Berretta, Nasimul Noman, Pablo Moscato
2011 Haque MN, Uddin MS, Abdullah-Al-Wadud M, Chung Y, 'Fast reconstruction technique for medical images using graphics processing unit', Communications in Computer and Information Science (2011) [E1]
DOI 10.1007/978-3-642-27183-0_32
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Grants and Funding

Summary

Number of grants 1
Total funding $1,500

Click on a grant title below to expand the full details for that specific grant.


20161 grants / $1,500

Research Higher Degree Proof Reading Grant$1,500

Funding body: Faculty of Engineering and Built Environment - The University of Newcastle (Australia)

Funding body Faculty of Engineering and Built Environment - The University of Newcastle (Australia)
Scheme Faculty Research Committee
Role Lead
Funding Start 2016
Funding Finish 2016
GNo
Type Of Funding Internal
Category INTE
UON N
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Research Collaborations

The map is a representation of a researchers co-authorship with collaborators across the globe. The map displays the number of publications against a country, where there is at least one co-author based in that country. Data is sourced from the University of Newcastle research publication management system (NURO) and may not fully represent the authors complete body of work.

Country Count of Publications
Australia 4
Canada 2
Malaysia 2
Bangladesh 1
Korea, Republic of 1
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Dr Mohammad Haque

Positions

Research Associate
School of Electrical Engineering and Computing
Faculty of Engineering and Built Environment

Casual Academic
School of Electrical Engineering and Computing
Faculty of Engineering and Built Environment

Contact Details

Email mohammad.haque@newcastle.edu.au
Phone (02) 4042 0189

Office

Room L3 Pod
Building HMRI Building
Location Hunter Medical Research Institute 1/1 Kookaburra Circuit, New Lambton Heights, NSW 2305 Australia

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