Dr. T. Maruthi Padmaja

Department:
Information Technology
Faculty Id:
VCE1332
Designation:
Professor
Years of Experience:
16 years
Employment Status:
Full Time – Non Ratified by JNTUH
Phone:
9978967155

Date of Birth:

02 June 1979

Areas of Specialization :

Machine Learning, Stream Learning, Data Mining

Qualification

Ph.D. in CSE, 2012, from University of Hyderabad
PG Degree in IT,2004, Tezpur Central University, Assam
M.SC in Computer Science,2001, Nagarjuna University, Guntur

Subjects Taught:

ML, OS, MP, PR, DMDW

Papers Published:

JOURNALS:

  1. Jhansi Lakshmi, T. Maruhi Padmaja, P. Radha Krishna, ” A Study on Class Imbalancing Feature selection and Ensembles on Software Reliability Prediction”, International journal of open source software and processes (ijossp), IGI Publishing,  (Scopus-DBLP).
  2. Jhansi Lakshmi, T. Maruhi Padmaja, “Weighted SVMBoost based Hybrid Rule extraction method for software Defect Prediction“, International Journal of Roughsets and Data Analysis,  6(2), IGI Publishing,  pp: 51-60,  2019. (DBLP)
  3. Maruthi Padmaja, Raju S. Bapi and Radha Krishna. P, Rudra N. Hota “Class Imbalance and Its Effects on PCA Preprocessing”, Int. J. Knowledge Engineering and Soft Data Paradigms, Inderscience publisher. Vol 4, No 3, 2014, pp: 272-294. (DBLP)
  4. T. Maruthi Padmaja, Raju S. Bapi and Radha Krishna. P, “ Probabilistic Cost Sensitive Active Learning Approach for Class Imbalance Problem”, Int. J. Knowledge Engineering and Soft Data Paradigms, Inderscience publisher, Vol. 4, No. 1, 2013, pp: 85-106. (DBLP)
  5.  Anil-Kumar Thurimellaand Maruthi T.Padmaja, “Software Product Line Engineering: A Review of Recent Patents”, Recent Patents on Computer Science, Bentham Science Publishers, Vol. 3, No. 2, June 2010, pp: 148-161. (SCOPUS)
  6. Sk. Z. Bhasha, T. Maruthi Padmaja, G. N. B. Balaji, “Computer Aided Fracture Detection System“,  Journal of Medical Imaging and Health Informatics, Vol 8, No 3  pp:526-531, 2018.  (Scopus)
  7. B Suvarna, TM Padmaja, “A Recommonder System for Proactive sharing of Architecural Knowledge”,  AMA_B journal, IIETA Publisher,  Vol 62(6), pp:1-10, 2019. (Scopus)
  8. B Suvarna, TM Padmaja, “Enhanced Matrix Chain Multiplication“, Journal of Cyber Security and Mobility, Vol.7, No. 3, 2018. (Scopus)
  9. K. Praveen Kumar, T. Maruthi Padmaja, “A Study on Dimensionality Reduction Methods for Finding Similarity in Indian English Author Poetry“, International Journal of Recent Technology and Engineering, Vol 7, No.6, 2019. (Scopus)
  10. S. Chinna Gopi, B. Suvarna, T. Maruthi Padmaja,”High Dimensional Unbalanced Data Classification Vs SVM Feature Selection”, Indian Journal of Science and technology, Vol 9(30), 2016. (Scopus)
  11. Ramakrishna, V., Narasinga M. R. Rao and T. Maruhi Padmaja, “Software Reliability Prediction using Neural Networks”, Int.  J. of Computer Applications Vol. 60, No.7, December 2012, pp: 44-48.
  12. NarasingaRao M R, T M Padmaja, GR Sridhar, Marcus Lind, K. Madhu, V. Ramakrishna, “Assessment of Wellbeing in Diabetes-A Comparison of MLP with Back- propagation and Support Vector Regression”, Journal of Life Medicine (JML), Vol. 1, No. 3, 2013, pp: 55-60.

 BOOK CHAPTERS:

  1. A.K. Thurimella, T. Maruthi Padmaja, “Economic Models and Value-Based Approaches for Product Line Architectures”, Edited by Ivan Mistrik, Rami Bahsoon, Rick Kazman, Kevin Sullivan, Yuanyuan Zhang. Economics-Driven Software ArchitectureElsevier,  pp:11-34, 2014. (Scopus)
  2. Maruthi Padmaja, Raju S. Bapi and P. Radha Krishna. “Unbalanced Sequential data classification using Extreme Outlier Elimination and sampling Techniques”, Edited by Pradeep Kumar, P. Radha Krishna, Bapi S. Raju. Pattern Discovery Using Sequence Data mining: Applications and Studies. IGI Publishing, pp: 83-93, 2012. (Scopus)
  3. Pradeep Kumar, P. Radha Krishna, Raju S. Bapi and T. Martuhi Padmaja, “Advances in Classification of Sequence Data”, Edited by  Dvid Taniar, Data Mining And Knowledge Discovery Techniques, IGI Publishing, pp:143-174.(Scopus)

CONFERENCES:

International

  1. Himaja, T. Maruthi Padmaja, P. Radha Krishna, “An Unsupervised Drift Detector for Online Imbalanced Evolving Streams“,  In Proc .of  DATA-2019, Prague, Czech Republic.
  2. Himaja, T. Maruthi Padmaja, P. Radha Krishna, “Oversample Based Online Support Vector Machine for Class Imbalance Problem“, In Proc. of BIG DATA Analytics,2018. NIT Warangal. (Acceptance Rate:19%).
  3. Maruthi Padmaja, Raju S. Bapi and P. Radha Krishna, “A Class Specific Dimensionality Reduction Framework for Class Imbalance Problem: CPC_SMOTE”, In Proc. of Knowledge Discovery and Information Retrieval KDIR, pp: 237-242, INSTICC Press, Spain 2010.
  4. Maruthi Padmaja, P. Radha Krishna and Raju S. Bapi, “Reverse-NN Curve based Cluster Counting Approach”, In Proc. Of ICDM-2009, Ghaziyabad, Feb-2009.
  5. Maruthi Padmaja , P. Radha Krishna and Raju S. Bapi, “Majority Filter Based Minority Prediction (MFMP) an Approach for Unbalanced Datasets”, In Proc. of Annu. International. Conf. Tencon, No: 4766705, HYDERABAD, 2008.
  6. Maruthi Padmaja, Narendra Dhulipalla, P. Radha Krishna1, Raju S. Bapi, and A.Laha, “An Unbalanced Data Classification Model Using Hybrid Sampling Technique For Fraud Detection”, In Proc. of Pattern Recognition and Machine Intelligence (PreMi), pp.341-348, Springer-Verlag, ISI-kolkata, 2007.
  7. Maruthi Padmaja, Narendra Dhulipalla, Raju S. Bapi and P. Radha Krishna, “Unbalanced Data Classification using extreme outlier Elimination and Sampling Techniques for Fraud Detection”, In Proc. of Advanced Computing and Communications ADCOM, pp: 511-516, IEEE Computer Society Press, IIT-Guwahati, 2007.
  8. Maruthi Padmaja, P. Jhansi Lashmi, “Hybrid Rule Extraction Method for One_Class Support Vector Machines”, In Proc.of IEEE  Intelligent Systems and Control (ISCO) -2015, Coimbattore.
  9. Bhargavi, A. KavithaT. M. Padmaja,  “Securing BIG Storage: Present and Future” In Proc. of  IEEE Green Engineering and Technologies (IC-GET), 2016.
  10. Bhargavi, D. Veerayia, T.M. Padmaja, “Securing BIG DATA: A Comparative Study AcrossRSA, AES, DES, EC and ECDH”, Third International Conference on Computer & Communication Technologies, In Proc.of  IC3T-2016, pp:355-362, 28 – 29 October 2016 Vijayawada, Andhra Pradesh.
  11. M.V. Sowjanya, T.M. Padmaja, “Varied Density Based Graph Clustering Algorithm for Socical Networks“, In Proc.of IEEE I-SMAC17, 2017.
  12.  Sk. Z. Bhasha, T. Maruthi Padmaja, G. N. B. Balaji, “Automatic X-ray Image Classification System“, In Proc.of  SCI-2017, Spinger.
  13. K. Praveen Kumar, T. Maruthi Padmaja, ” An Analysis on Computational Approach for Finding Similarity in Indian English Authors Poetry“, In Proc.of SMART DSC-2017, ASTL publications.
  14. K. Praveen Kumar, T. Maruthi Padmaja, “Computational Analysis on Differences in Indian and American Poetry”, In Proc. of. ICCIDE-2018, VFSTR University.

 

National

  1. T. Maruthi Padmaja and P. Radha Krishna, “A Combined Decision Tree Algorithm”, DIT-05, Dehradun.
  2. S. Kranthi, T. Maruthi Padmaja, “Survey on Machine Learning and Non machine Learning Techniques for Spam Detection”, NCNSC’18, VFSTR University.

Books Published:

None

Research Projects Undertaken:

  • An Adaptive Classifier for Unbalanced Evolving Streams: An Application to Fraudulent Data Streams” , 9.10 lakhs,  2017-2019, ER & IPR, DRDO, New Delhi.  (NOV 2,2017-2019). Sanction code: ERIP/ER/DG-MED&CoS/990516502/M/01/1695.

Invited Talks:

  1.  “Unbalanced Data Classification Problem: Static to Streaming Data”, DLRL (DRDO LAB) CEP course on “Signal Analysis and Data Extraction”, 2017.
  2. Classification of Unbalanced Evolving Streams with Concept Drift”, Center for Artificial Intelligence and Robatics, (DRDO LAB) CEP course, 2017.
  3. Big Data Analytics Present and Future“, Universal College of Engineering and Technology, 2016