Email: ashishdutt@yahoo.com.my

Researchgate Github: duttashi, StackOverFlow: ashish, Twitter: @duttashish_

Education


2014-2018 (expected)

  • PhD

    Faculty of Computer Science and Information Systems University of Malaya, Kuala Lumpur, Malaysia

    Field of Research; Computer Science (Educational Data Mining)

    Thesis- A soft set approach to evaluate academic performance based on student’s academic and demographic data

2010-2012

  • M.Sc, University of Staffordshire, UK

    Majors: Computer Science

    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

    Majors: Botany

RESEARCH PUBLICATIONS


  1. Dutt, A., Ismail, MA., Herawan, T., A Systematic Review on Educational Data Mining (2017). IEEE Access.

  2. Sardareh, S. A., Aghabozorgi, S., & Dutt, A. (2015). Applying Clustering Approach to Analyze Reflective Dialogues and Students’ Problem Solving Ability. Indian Journal of Science and Technology, 8(11).

  3. Dutt, A., Aghabozorgi, S., Maizatul, A.B.I., Mahroeian, H. (2014). Clustering Algorithms Applied in Educational Data Mining. International Journal of Information and Electronics Engineering (IJIEE), 5(2).

  4. Dutt, A., Aghabozorgi. (2014). A Framework for mining top call drivers as experienced in technical contact centres to facilitate self help portals. 6th International Conference on Education and Information Management (ICEIM-2014), Kuala Lumpur, Malaysia.

  5. Aghabozorgi, S., Mahroeian, H., Dutt, A., Wah, T.Y., Herawan, T.. (2014). An Approachable Analytical Study on Big Educational Data Mining. In: Murgante, B., Misra, S., Rocha, A.M.A.C., Torre, C., Rocha, J.G., Falcão, M.I., Taniar, D., Apduhan, B.O., Gervasi, O. Computational Science and Its Applications (ICSSA). Springer International Publishing. 721-737.

  6. Sardareh, S. A., Aghabozorgi, S., & Dutt, A. (2014). Reflective Dialogues and Students’ Problem Solving Ability Analysis Using Clustering. Paper presented at the The 3rd International Conference on Computer Engineering and Mathematical Sciences (ICCEMS 2014), Langkawi, Malaysia.

Reviewer


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

Active reviewer for the following journals
  • IEEE Access Journal (ISSN: 2169-3536)

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)

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)

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.

Past/Inactive reviewer for the following journals
  • IETE Journal of Research Journal (ISSN: 0377-2063) is a bimonthly journal published by the Institution of Electronics and Telecommunication Engineers (IETE), India. It publishes 6 issues/year.

  • Soft Computing Journal (ISSN: 1432-7643) is dedicated to system solutions based on soft computing techniques. It is published by Springer Berlin Heidelberg.

CAREER PATH


  • Data Analyst (Jun 2015 Apr 2016)

  • Graduate Research Assistant (Data Science)(Jun 2014 Jun 2015)

  • Teaching Assistant (Data Science)(04/06/2012 until 01/03/2013)

  • Technical Consultant Level 2 (14/12/2009 until 20/02/2011)

  • Technical Consultant Level 1 (18/07/2006 until 16/12/2009)

  • Project Assistant (12/04/2004 until 11/09/2006)

  • Senior Lecturer (Data Science) (02/12/2002 until 31/03/2004)

  • Lecturer (Data Science) (02/07/1999 until 30/11/2002)

Programming Skills


  • R

Functional Knowledge


  • Python 2.7
  • SQL
  • SAS

Projects

Completed Projects

  1. 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.

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

    Project duration: February 2017

    Objective: 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.

  3. 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.

  4. Project: Exploratory data analysis of the GapMinder dataset

    Project duration: February 2016

    Objective: Analyze the dataset to determine the causes of breast cancer in women.

    Deliverable: Used the Gap minder dataset and performed exploratory and inferential data analysis. The findings are listed on my blog and the python code is listed on GitHub.