Email: drashishdutt@gmail.com

Education

2014-2020

  • PhD

    Department of Information Systems, Faculty of Computer Science and Information Systems (FCSIT), University of Malaya, Kuala Lumpur, Malaysia

    Field of Research- Computer Science (Mixed Data Clustering)

    Thesis- A Partition based Feature Selection Approach for Mixed Data Clustering

2010-2012

  • M.Sc

    University of Staffordshire, UK

    Field of Research: Computer Science (Clustering)

    Dissertation Title: A Framework for mining the top call drivers as experienced in technical contact centers Published paper

1996-1999

  • B.Sc

    Panjab University, Chandigarh, India

    Major: Life Science

RESEARCH PUBLICATIONS

Published articles

  1. Dutt, A., Ismail, MA. (2020), A partition based feature selection approach for mixed data clustering. journal paper

  2. Dutt, A., Ismail, MA. (2019), Can we predict student learning performance from LMS data? A classification approach. conference paper

  3. Dutt, A., Ismail, MA., Herawan, T. (2017), A systematic review on educational data mining. journal paper

  4. Sardareh, S. A., Aghabozorgi, S., & Dutt, A. (2015). Applying clustering approach to analyze reflective dialogues and students’ problem solving ability. journal paper

  5. Dutt, A., Aghabozrgi, S., Maizatul, A.B.I., Mahroeian, H. (2014). Clustering algorithms applied in educational data mining journal paper

  6. Dutt, A., Aghabozrgi. (2014). A framework for mining top call drivers as experienced in technical contact centres to facilitate self help portals conference paper

  7. Aghabozrgi, S., Mahroeian, H., Dutt, A., Wah, T.Y., Herawan, T. (2014). An approachable analytical study on big educational data mining conference paper

  8. Sardareh, S. A., Aghabozrgi, S., & Dutt, A. (2014). Reflective Dialogues and Students’ Problem Solving Ability Analysis Using Clustering conference paper

Under review articles

  • Year 2024

    • Dutt, A, Ismail, MA., Targio, I.A.H, A systematic review on mixed data clustering in educational data mining

Reviewer

I serve as a reviewer to several international journals. Peer-review is a voluntary service and one is not paid for it.

Active reviewer for the following journals
  • IEEE Transactions on Knowledge and Data Engineering Journal (ISSN: 1041-4347) - ISI indexed

IEEE Trans on Knowledge and Data Engineering, is a Q1 (JCR year 2018) journal in Computer Science, Artificial Intelligence & Information Systems, with an impact factor of 3.85. It is published by IEEE, USA. It publishes 12 issues/year.

  • IEEE Access Journal (ISSN: 2169-3536) - ISI indexed

IEEE Access is an Open Access journal. It is a Q1 (JCR year 2016) journal in Computer Science with an impact factor of 2.95. It is published by IEEE, USA.

  • IEEE Transactions on Learning Technologies Journal (ISSN: 1939-1382) - ISI indexed

IEEE Transactions on Learning Technologies is a Q2 (JCR year 2016) journal in Computer Science and Interdisciplinary Applications with an impact factor of 2.083. It is published by IEEE Computer Society from California, USA. It publishes 4 issues/year

  • Kybernetes Journal (ISSN: 0368-492X) - ISI indexed

Kybernetes is a Q4 (JCR year 2016) journal in Computer Science and Cybernetics with an impact factor of 0.811. It is published by Emerald group at Yorkshire, England and publishes 10 issues/year. Review speed (1st Decision): 6 weeks

  • International Journal of Electrical and Computer Engineering (IJECE) Journal (ISSN: 2088-8708) - Scopus indexed

IJECE is published by the Institute of Advanced Engineering and Science (IAES) with an impact factor of 0.99 and Q2 in Computer Science. Review speed (1st Decision): 8 weeks

  • International Journal of Educational Technology in Higher Education Journal (ISSN: 2365-9440) - Scopus indexed

ETHE is associated with Universitat Oberta de Catalunya and published by Springer Nature. It has an impact factor of 1.33 in Scopus. Subject area: Education, Computer Science Applications. Review speed (1st Decision): 21 days, Acceptance to Publication: 28 days

  • Research in Learning Technology Journal (ISSN: 2156-7069) - Scopus Indexed

Published by the Association for Learning Technology. There is no publication fees. Link

  • Soft Computing Journal (ISSN: 1432-7643) - ISI indexed is dedicated to system solutions based on soft computing techniques. It is published by Springer Berlin Heidelberg. Subject area: Computer Science Applications. Review speed (1st Decision): 45 days

Programming Skills

  • R
  • Python
  • SQL

Ongoing Project(‘s)

Independent projects on text mining, applied machine learning and web-data scraping

Completed Projects

  1. Project: To develop a partition based feature selection algorithm for mixed data clustering

    Project commissioned by: Department of Information System, University of Malaya

    SDLC process methodology: Scrum

    Technologies stack: R

  2. Project: A predictive analytic model to determine the run time, and, end of life of electric grids deployed in Bangladesh

    Project commissioned by: Edotoco Sdn Bhd

    SDLC process methodology: Scrum

    Technologies stack: R, PowerBI

  3. Project: A classification approach to model the employee flight risk behaviour

    Project duration: March-May 2019

    Objective: Determine the factors which contribute to accurately predicting flight risk behaviour proclivities in employees.

    Deliverable: Used the labor force data and performed exploratory, inferential and predictive data analysis. The findings are listed on my research blog and the R code is listed on GitHub. See exploratory data analysis code and predictive modeling.

  4. Project: Predicting employment related factors in Malaysia- A regression analysis approach

    Project duration: February 2017

    Objective: Determine the factors which contribute to accurately predicting unemployment rate from historical statistical data on labour force data in Malaysia.

    Deliverable: Used the labor force data from the Department of Statistics, Malaysia and performed exploratory, inferential and predictive data analysis. The findings are listed on my research blog and the R code is listed on GitHub.

  5. Project: Predicting rubber plantation yield- A regression analysis approach

    Project duration: February 2017

    Objective: To determine the factors which contribute to accurately predicting high rubber yield per kg based on historical rubber plantation data.

    Deliverable: Used the agriculture data from the Department of Statistics, Malaysia and performed predictive analytics. The findings are presented on my blog and the R code is listed GitHub.

  6. Project: House price prediction using advanced regression techniques

    Project duration: September-November 2016

    Objective: Analyze the dataset to improve upon feature engineering and advanced regression algorithms like random forests, gradient boosting with xgboost

    Deliverable: Used the Ames housing dataset and performed exploratory and inferential data analysis. The findings are listed on my blog and the R code is listed on GitHub.