Karthick T. Sharma

HDR Student @ QUT

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I am a Machine Learning Research Engineer and incoming MPhil student at Queensland University of Technology (QUT), where I will focus on Healthcare AI research. My work sits at the intersection of machine learning, natural language processing, and real-world healthcare applications.

Previously, I completed my Bachelor’s in Computer Engineering from the University of Sri Jayewardenepura. I have had the opportunity to work with research groups at Nanyang Technological University (NTU) and Singapore University of Technology and Design (SUTD), contributing to projects in online learning systems, data streams, and biomedical imaging.

My research interests include developing AI systems for clinical decision support, medical diagnostics, and knowledge distillation techniques. I am passionate about building practical, scalable solutions that can make a meaningful impact in healthcare settings.

selected publications

  1. ASOC
    Data-Centric Single Teacher Guided Knowledge Distillation for Alleviating Sub-Optimal Supervision in Image Classification
    Karthick Sharma and Bhagya Nathali Silva
    Applied Soft Computing Journal, 2026
    In Press
  2. Preprint
    ED-Triage-Agent: A Framework for Human-AI Collaborative Emergency Triage
    Karthick Sharma, Harikrishnan Sivadas, and Sandeep Reddy
    medRxiv, 2026
  3. ICDE
    Scalable Machine Learning for Real-Time Fault Diagnosis in Industrial IoT Cooling Roller Systems
    Dandan Zhao, Karthick Sharma, Hongpeng Yin, and 2 more authors
    In IEEE International Conference on Data Engineering (ICDE), 2025
  4. ISBI
    MUM: Enhancing Medical Diagnostics through Unpaired Multimodal Data Integration
    Karthick Sharma, Mokeeshan Vathanakumar, Gamika Seneviratne, and 1 more author
    In IEEE International Symposium on Biomedical Imaging (ISBI), 2025
  5. EMNLP
    SentiStream: A Co-Training Framework for Adaptive Online Sentiment Analysis in Dynamic Data Streams
    Yuhao Wu, Karthick Sharma, Chun Wei Seah, and 1 more author
    In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023