Prof. Meerja Akhil Jabbar

Prof. Meerja Akhil Jabbar

Professor
Vardhaman College of Engineering, India


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

Share this Profile

Biography

Dr. M.A.JABBAR is a Vice-chair, IEEE CS Chapter , Hyderabad Section and Professor and Head Dept of AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India. He has been teaching for more than 20 years. He obtained a Doctor of Philosophy (Ph.D.) from JNTUH, Hyderabad, and Telangana.

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

Publications:
He published more than 50 papers in Scopus in various journals and conferences. He is Reviewer for Scopus and SCI journals like Springer, Elsevier, and IEEE Transactions on Systems Man and Cybernetics, Wiley. He served as a technical committee member for more than 40 international conferences. He has been Editor for 1st ICMLSC 2018 international conference held during 22nd and 23rd June 2018 at Hyderabad
Awards and achievements:
• Received best faculty researcher award from CSI Mumbai chapter and Fossee Labs IIT Bombay
• Recognized as an outstanding reviewer from Elsevier.
• Received outstanding Leadership award from IEEE Hyderabad Section.

Research interest:
His research interests include Data Mining, Big Data Analytics, Bio-Informatics, Cyber Security, Machine Learning, Attack Graphs, and Intrusion Detection Systems.
Scopus Link : https://www.scopus.com/authid/detail.uri?authorId=54079882700
Google scholar Link: https://scholar.google.co.in/citations?user=BSL5V8IAAAAJ&hl=en
Website :
Patents published:
He published 5 patents (Indian) in machine learning and allied areas.
Books published:
Published a book “Heart Disease Data Classification using Data Mining Techniques”, with LAP LAMBERT Academic publishing, Mauritius.
ISBN NO: 978-613-9-46428-9, Published in April 2019

Area of Interest:

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

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.
    CrossRef  |  Direct Link  |  
  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.
    CrossRef  |  Direct Link  |  
  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.
    CrossRef  |  Direct Link  |  
  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.
    Direct Link  |  
  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.
    CrossRef  |  Direct Link  |  
  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.
    Direct Link  |  
  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.
    CrossRef  |  Direct Link  |  
  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.
    Direct Link  |  
  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.
    CrossRef  |  Direct Link  |  
  11. Jabbar, M.A., 2012. Knowledge discovery from mining association rules for heart disease prediction. J. Theor. Appl. Inf. Technol., 41: 166-174.
    Direct Link  |  
  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.
    Direct Link  |  
  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.
    Direct Link  |