Dr. Johnpaul C. I.

Email-Id

• johnpaulci@gmail.com

Academic Qualifications:

• 2017 – 2021 ] Ph.D., Computer Applications
  National Institute of Technology, Tiruchirappalli, India, Institute for Development and Research in Banking Technology, IDRBT, Hyderabad. (Established by Reserve Bank of India)
  Thesis title: Feature Based Representational Structures for Time Series
• 2011 – 2013 ] Master of Technology (M-Tech). Computer Science & Engineering.
  Amrita Vishwavidyapeetham, Coimbatore, India
  Thesis title: Graph Data Processing over Spark Based Inmemory Cluster Framework
  and Performance Evaluation with Standard Parameters.
• 2006 – 2010 ] Bachelor of Technology (B-Tech). Computer Science & Engineering.
  Government Engineering College, Sreekrishnapuram, Palakkad, Kerala, India
  University of Calicut

Area of Research:

• Feature Engineering in Machine Learning and Deep Learning

Journal Articles

• Tojo, M., Niyas, S., Johnpaul, C. I., Jyothi R, K., & Jeny, R. (2022). A novel deep classifier framework for automated molecular subtyping of breast carcinoma using immunohistochemistry image analysis. Biomedical Signal Processing and Control (BSPC), 76, 103657, Impact Factor: 3.8. doi:https://doi.org/10.1016/j.bspc.2022.103657
• Johnpaul, C. I., Munaga, V. N. K. P., Nickolas, S., & Gangadharan, G. (2021a). Fuzzy representational structures for trend based analysis of time series clustering and classification. Knowledge-Based Systems, Elsevier, 222, 106991, Impact Factor: 8.038. doi:https://doi.org/10.1016/j.knosys.2021.106991
• Johnpaul, C. I., Munaga, V. N. K. P., Nickolas, S., & Gangadharan, G. (2021b). Representational primitives using trend based global features for time series classification. Expert Systems with Applications, Elsevier, 167, 114376, Impact Factor: 6.9. doi:https://doi.org/10.1016/j.eswa.2020.114376
• Johnpaul, C. I., Munaga, V. N. K. P., Nickolas, S., & Gangadharan, G. (2020). Trendlets: A novel probabilistic representational structures for clustering the time series data. Expert Systems with Applications, Elsevier, 145, 113119, Impact Factor: 6.93. doi:https://doi.org/10.1016/j.eswa.2019.113119
• Johnpaul, C. I., Munaga, V. N. K. P., Nickolas, S., & Gangadharan, G. (2019). General representational automata using deep neural networks. Data Knowledge Engineering, Elsevier, 122,159–180, Impact Factor: 1.99.  doi:https://doi.org/10.1016/j.datak.2019.06.004
• Conference Proceedings
• Johnpaul, C. I., Munaga, V. N. K. P., Nickolas, S., Gangadharan, G., & Aiello, M. (2021). An optimal wavelet detailed-coefficient determination using time-series clustering. In N. N. Chiplunkar & T. Fukao (Eds.), Advances in artificial intelligence and data engineering (pp. 857–872). Singapore: Springer Singapore.
• Johnpaul, C. I., & Mathew, T. (2017a). A cypher query based nosql data mining on protein datasets using neo4j graph database. In 2017 ieee 4th international conference on advanced computing and communication systems (icaccs) (pp. 11–16). IEEE.
• Johnpaul, C. I., & Mathew, T. (2017b). Np-completeness of an optimization problem on plants selection using reduction method. In 2017 ieee international conference on intelligent computing, instrumentation and control technologies (icicict) (pp. 176–181). IEEE.
• Mathew, T., & Johnpaul, C. I. (2017). Reversible data hiding in encrypted images using interpolation-based distributed space reservation. In 2017 ieee 4th international conference on advanced computing and communication systems (icaccs) (pp. 112–118). IEEE.
• Johnpaul, C. I., & Sunith, S. (2015). Request based efficiency comparison of a xmpp server in erlang with a python server. In International conference on computers and communication, (iccc) (pp. 272–278). Tata McGrawHill Education.
• Johnpaul, C. I., & Neetha, S. T. (2014). Distributed in-memory cluster computing approach in scala for solving graph data applications. In 2014 ieee international conference on advances in electronics computers and communications (pp. 1–6). IEEE.
• Johnpaul, C. I., Elson, P., & Najeeb, K. (2010). Gap-genetic algorithm based power estimation technique for behavioral circuits. In In proceedings of international conference on computers, communication and intelligence. (pp. 95–100). VCET, Madhurai.

Invited Lectures

• Spark: An Inmemory Cluster Computing Framework for Distrubuted Computing at Department of Computer Science and Engineering, Amritavishwavidyapeetham, Coimbatore, May 2013, India.
• Time Series Learning and PythonWavelets Package at Kamaraj College of Engineering and Technology, Virudanagar, Tamil nadu, June 2021, India.
• Class of NP Problems at Lal Bahadur Shasthri Institute of Technology for Women, Poojapura, Trivandrum, India, July 2021
• Machine Learning and Optimization at Government Engineering College, Sreekrishnapuram, Palakkad, India, December 2021
  Time Series Analysis at National Institute of Technology, Tiruchirappalli, India, December 2021
• Deep Learning in Data Science Perspective at Government Engineering College, Sreekrishnapuram, Palakkad, India, March 2022
• Pathways Of Applied Deep Learning In Cybersecurity: Quick Basics To Deep Learning With Cyber Security Use Cases. at The National Institute of Engineering, NIE-Mysuru, Karnataka, India, April 2022

Awards and Achievements

• 2010 – Merit Award, Gate Scholarship 2011
• 2014 – Merit Award, Best Paper Award, In 2014 IEEE international conference on advances in electronics computersand communications
• 2017-2021 – Merit Award, Ph.D Research Scholarship from Ministry of Human Resource and Development (MHRD – India)
• 2018- Travel Grant, Visited University of Stuttgart, Germany during my Ph.D tenure
  for interacting with the collaborators of an Indo-Dutch project work named
  NextGenSmartDC.
• 2018-till now –  Journal Reviewer, Expert Systems With Applications (Elsevier), IEEE Access (IEEE), Sadhana (Indian Academy of Sciences) (Springer), Knowledge Based Systems (KBS) (Elsevier), IEEE Computers, Software & Applications in an Uncertain
  World (COMPSAC)
• 2019-till now –  ProgramChair, COMPSAC, Annual IEEE Conference usually held across the world. COMPSAC (2022) will be held at Torino, Italy.

Certification

• Data Science For Engineers. Indian Insitute of Technology, Madras (IIT-M) and
  NPTEL, 2019