Areas of Interest

• Big Data - Cleaning, Analytics, Security, Hadoop, Spark
• Health data and signal analytics - Heart rate and Respiratory rate variability
• Security and Privacy
• Cognitive Computing
• Mobile and Sensor Networks

Education

• B.Sc - Electrical Engineering, University of Wales
• M.Sc - Electrical Engineering and Computer Science, University of Edinburgh, Scotland
• Ph.D - Computer Science, University of Reading, England

Research

Selected Articles

• Ashwin Viswanathan Kannan, Goutam Mylavarapu and Johnson Thomas, Biologically Inspired Augmented Memory Recall Model for Pattern Recognition, 2018 International Conference on Cognitive Computing, Springer Lecture Notes in Computer Science (Springer LNCS), 2018
• Ashwin Kumar Thandapani Kumarasamy, Xiaofei Hou, Johnson P Thomas and Hong Liu, Content Sensitivity Based Access Control Framework For Big Data, Digital Communications and Networks, Special Issue on Big Data Security and Privacy, (Elsevier), Vol 3, Is 4, 2017
• T.K.Ashwin Kumar, J.P. Thomas and S Parepally. An Efficient and Secure Information Storage and Retrieval Framework for Content Centric Networks. Journal of Parallel and Distributed Computing (Elsevier). Vol 104, 2017.
• Hong Liu, Ashwin Kumar TK, Johnson P Thomas and Xiaofei Hou. Cleaning Framework for BigData: An Interactive approach for Data Cleaning. 2nd IEEE International Conference on Big Data Computing Service and Applications (IEEE BigDataService). 2016
• Goutam Mylavarapu and Johnson P Thomas, A Multi-task Machine Learning Approach for Comorbid Patient Prioritization, Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI), co-located with 2107 IEEE International Conference on Big Data (IEEE BigData)
• Xiaofei Hou, Ashwin Kumar T K, Johnson P Thomas and Hong Liu, Dynamic Deadline-constraint Scheduler for Hadoop YARN, Proceedings 2017 IEEE Conference on Cloud and Big Data Computing (CBDCom 2017), 2017
• Xiaofei Hou, Doyel Pal, Ashwin Kumar T K, Johnson Thomas and Hong Liu. Privacy Preserving Rack-based Dynamic Workload Balancing for Hadoop MapReduce. 2nd IEEE International Conference on Big Data Security on Cloud (BigDataSecurity). 2016
• Praveen Khethavath, Johnson P Thomas and Eric Chan-Tin. Towards an efficient Distributed cloud computing architecture. Peer-to-peer Networking and Applications (Springer), Vol 10, Is 5, 2016
• Ashwin Kumar TK, K M George and Johnson P Thomas. An empirical approach to detection of topic bubbles in tweets. Proceedings 2nd IEEE/ACM Symposium on Big Data Computing. 2015
• Doyel Pal, TingtingChen and Johnson Thomas. Sequential Pattern Mining Across Multiple Medical Sites. Annual Symposium of the American Medical Informatics Association. Poster. 2015
• Hong Liu, Johnson Thomas and Praveen Khethavath. Moving Target with Load Balancing in a Hierarchical Cloud. International Journal of Cloud Computing (IJCC). Vol. 2. No. 3. 2014
• Hong Liu, Ashwin Kumarasamy and Johnson Thomas. Cleaning Framework for Big Data. IEEE BigData Congress 2015, Research Track
• Doyel Pal, Praveen Khethavath*, Johnson Thomas and Tingting Chen. Multilevel Threshold Secret Sharing in Distributed Cloud. 3rd International Symposium on Security in Computing and Communications. Springer Communications in Computer and Information Science Series (CCIS): Security in Computing and Communications ISSN: 1865:0929, 2015
• Xiaofei Hou, Ashwin Kumar T K and Johnson P Thomas. Dynamic Workload Balancing for Hadoop MapReduce. 4th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2014)
• Dileep Nagireddygari and Johnson Thomas. MAC-TCP Cross-Layer attack and its Defense in Cognitive Radio Networks. Proceedings 10th ACM International Symposium on QoS and Security for Wireless and Mobile Networks. 2014
• Hong Liu, Ashwin Kumarasamy and Johnson Thomas. Efficient Structuring of data in Big Data. Proceedings IEEE International Conference on Data Science and Engineering. 2014
• ZhengMing Shen and Johnson Thomas. Security and QoS Self-Optimization in Mobile Ad Hoc Networks. IEEE Transactions on Mobile Computing. Volume 7. Issue 9. September 2008
• Sandhya Peddabachigari, Ajith Abraham, Crina Grosan and Johnson Thomas. Modeling Intrusion Detection System Using Hybrid Intelligent Systems. Journal of Network and Computer Applications. Elsevier Science. Volume 30. Issue 1. January 2007

Ph.D Students

• Goutam Mylavarapu - Machine Learning for Data Quality analysis
• Ashwin Kannan - Brain inspried Cognitive Models
• Mounika Kasaraneni- Cognitive Computing for Immersive Systems

Research supported by:

• National Science Foundation
• United States Department of Agriculture
• Department of Defense - Army Research Office
• NASA Epscor
• Oklahoma State University