Dr Ramesh Kumar Ayyasamy
Funding in UTAR
  • a coherent knowledge-driven deep learning model for implicature opinion mining using social big data, UTARRF, August 2020 - July 2021.
  • feature based detection of new and unknown malware to predict threat, UTARRF, August 2020 - July 2021.
  • integrated sem-neural network approach to improve cyber security behaviour through cyber hygiene among employees of software development smes, UTARRF, August 2020 - July 2021.
  • comparative studies to determine the different quality features (or aspects) for sentiment assignment and sentiment scoring in sentiment analysis utilizing deep learning method, UTARRF, December 2020 - December 2021.
  • impact of industry 4.0?s digital technologies and information systems on innovation performance of manufacturing firms ? sem+ann approach, UTARRF, December 2021 - December 2022.
  • an adaptive covid-19 sentiment analysis model by coupling textual lexicon and transfer learning, UTARRF, December 2022 - December 2023.
  • an exploratory study to investigate the sustainability of diabetes self-management interventions based on motivational theories, UTARRF, December 2022 - December 2023.
  • a framework to enhance the usefulness of unstructured customer data for improved customer insights, UTARRF, December 2022 - December 2023.
  • the study on the impact of entrepreneurial orientation on project performance using machine learning, UTARRF, July 2023 - June 2024.
  • developing a fine-tuned transformer model to detect social media hate speech texts, UTARRF, November 2023 - October 2024.
  • from waste to wealth: determining the readiness factors to embrace blockchain technology in the palm oil industry to facilitate circular economy transition, UTARRF, November 2023 - October 2024.
  • digitalization of utar hospital towards smart hospital, UTAR HOSPITAL, May 2024 - April 2025.
  • hand gesture recognition using emg signals with a smaller number of electrodes through machine learning, UTARRF, June 2024 - May 2025.
  • decoding unconventional patterns: a machine learning approach to unusual activity identification, UTARRF, June 2024 - May 2025.
  • reducing digital burnout in malaysian healthcare professionals through digital minimalism, UTARRF, November 2024 - October 2025.
  • developing a multi-label sentiment analysis model for pandemic reviews using the bert-based fine-tuning approach, MOHE FRGS, August 2024 - July 2027.
Funding not in UTAR
  • slowing the spread of diabetes: investigating health knowledge, beliefs, and lifestyle among sociocultural groups in malaysia., MOHE FRGS, December 2013 - November 2016.