Dr. Meerja Akhil Jabbar
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Dr. Meerja Akhil Jabbar

Professor
Vardhaman College of Engineering, India


Highest Degree
Ph.D. in Data Mining from Jawaharlal Nehru Technological University, Hyderabad, India

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Biography

Dr. M.A.JABBAR is a Professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India. He obtained Doctor of Philosophy (Ph.D.) in the year 2015 from JNTUH, Hyderabad, and Telangana, India. He has been teaching for more than 20 years. His research interests include Artificial Intelligence, Big Data Analytics, Bio-Informatics, Cyber Security, Machine Learning, Attack Graphs, and Intrusion Detection Systems.

He published more than 50 papers in various journals and conferences. He served as a technical committee member for more than 70 international conferences. He has been Editor for 1st ICMLSC 2018, SOCPAR 2019 and ICMLSC 2020. He also has been involved in organizing international conference as an organizing chair, program committee chair, publication chair and reviewer for SoCPaR, HIS, ISDA, IAS, WICT, NABIC etc. He is Guest Editor for The Fusion of Internet of Things, AI, and Cloud Computing In Health Care: Opportunities and Challenges (Springer) Series, and Deep Learning in Biomedical and Health Informatics: Current Applications and Possibilities –CRC Press,Guest Editor for Emerging Technologies and Applications for a Smart and Sustainable World-Bentham science ,Guest editor for Machine Learning Methods for Signal, image and Speech Processing –River Publisher.

He is a senior member of IEEE, and Lifetime member in professional bodies like the Computer Society of India (CSI) and the Indian Science Congress Association (ISCA). He is serving as a chair, IEEE CS chapter Hyderabad Section. He is also serving as a member of Machine Intelligence Laboratory, USA (MIRLABS) and USERN, IRAN , Asia Pacific Institute of Science and Engineering (APISE) Hong Kong , Member in Internet Society (USA), United States , Member in data science society USA, Artificial Intelligence and Machine Learning Society of India (AIML), Bangalore.

He Received best faculty researcher award from CSI Mumbai chapter and Fossee Labs IIT Bombay ,and Recognized as an outstanding reviewer from Elsevier, Received outstanding Leadership award from IEEE Hyderabad Section. He published 5 patents (Indian) in machine learning and allied areas and published a book on “Heart Disease Data Classification using Data Mining Techniques”, with LAP LAMBERT Academic publishing, Mauritius in 2019.

Area of Interest:

Computer Sciences
100%
Data Mining
62%
Big Data Analysis
90%
Intrusion Detection System
75%
Algorithms
55%

Research Publications in Numbers

Books
8
Chapters
5
Articles
23
Abstracts
16

Selected Publications

  1. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2016. Prediction of Heart Disease Using Random Forest and Feature Subset Selection. In: Innovations in Bio-Inspired Computing and Applications. Snasel, V., A. Abraham, P. Kromer, M. Pant and A.K. Muda (Ed.). Springer International Publishing, Switzerland, ISBN: 978-3-319-28030-1, pp: 187-196.
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  2. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2016. Intelligent heart disease prediction system using random forest and evolutionary approach. J. Network Innov. Comput., 4: 175-184.
  3. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2016. A Novel Algorithm for Utility-Frequent Itemset Mining in Market Basket Analysis. In: Innovations in Bio-Inspired Computing and Applications. Snasel, V., A. Abraham, P. Kromer, M. Pant and A.K. Muda (Ed.). Springer International Publishing, Switzerland, ISBN: 978-3-319-28030-1, pp: 337-345.
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  4. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2013. Knowledge Discovery Using Associative Classification for Heart Disease Prediction. In: Intelligent Informatics, Abraham, A. and S.M. Thampi (Ed.). Springer Berlin Heidelberg, Germany, ISBN: 978-3-642-32062-0, pp: 29-39.
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  5. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2013. Heart disease classification using nearest neighbor classifier with feature subset selection. Ann. Comput. Sci. Ser., 11: 47-54.
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  6. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2013. Graph Based Approach for Heart Disease Prediction. In: Proceedings of the Third International Conference on Trends in Information, Telecommunication and Computing, Das, V.V. (Ed.). LNEE., Vol. 150, Springer, New York, USA., ISBN: 978-1-4614-3362-0, pp: 465-474.
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  7. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2013. Classification of heart disease using artificial neural network and feature subset selection. Global J. Comput. Sci. Technol. Neural Artif. Intell., 13: 5-14.
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  8. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2013. Classification of heart disease using K-nearest neighbor and genetic algorithm. Procedia Technol., 10: 85-94.
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  9. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2012. Data partitioning and bit vector approach for weighted frequent item set mining. Int. J. Comput. Theory Eng., 4: 980-982.
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  10. Jabbar, M.A., B.L. Deekshatulu and P. Chandra, 2012. An Evolutionary Algorithm for Heart Disease Prediction. In: Wireless Networks and Computational Intelligence, Venugopal, K.R. and L.M. Patnaik (Eds.)., Springer, Berlin Heidelberg, ISBN: 978-3-642-31685-2, pp: 378-389.
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  11. Jabbar, M.A., 2012. Knowledge discovery from mining association rules for heart disease prediction. J. Theor. Appl. Inf. Technol., 41: 166-174.
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  12. Jabbar, M.A., P. Chandra and B.L. Deekshatulu, 2011. Cluster based association rule mining for heart attack prediction. J. Theoret. Applied Inform. Technol., 32: 196-201.
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  13. Deepthi, T., M.A. Jabbar and A.C. Sharma, 2011. Solving imbalanced data problem with a new approach. Digital Image Process., 3: 43-46.
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