Mukunthan

About

I am a Senior Lecturer at the University of Jaffna, Sri Lanka, and an AI researcher with expertise in Artificial Intelligence, Digital Health, and IoT. My work bridges academia and industry, developing explainable ML models, portable diagnostic platforms, and smart control systems for digital healthcare and energy.

Industrial Experience

• Specialist Software Engineer – LSEG Technology (Apr 2017 – Apr 2018)
  • Led MiFID II implementation and improved trading systems.
• Senior Software Engineer – LSEG Technology (Apr 2016 – Mar 2017)
  • Developed components for capital market automation.
• Software Engineer – MillenniumIT (Apr 2014 – Mar 2016)
  • Contributed to FIX-to-FPML testing automation and Post Trade systems.

Research and Teaching Experience

• Senior Lecturer – University of Jaffna (2023–Present)
  • Course coordinator, Undergraduate Research supervisor, industry collaborator (SLT, Dialog).
• Lecturer (Probationary) – University of Jaffna (2018–2019)
• Research Associate – King’s College London (2022–2023)
  • Led research on interpretable AI models for lung cancer detection.
• PhD Researcher – University of Surrey (2019–2022)
  • AI models for AMR, SARS-CoV-2, poultry pathogen detection.

Project Collaboration

• 📱 Vidiia Hunter – COVID-19 diagnostic platform (Vidiia, Lancaster)
• 🔌 ADB Smart Grid – AI market prediction & control (SL Utilities + Unis)
• 🧠 E-carebetics – Explainable AI diabetic eye disease detection
• 👋 CONTENT4ALL – Sign-translation for deaf communities (EU Project)

Consultation

• Machine Learning Consultant – SenzMate Pvt Ltd (Jan 2022 – Present)
• Projects: AI models for agricultural price forecasting, anomaly detection in logistics, and GANs for image generation.

Research

• Explainable AI for disease prediction (Lung cancer, AMR, Diabetic Retinopathy)
• AI-based smart grid optimization and predictive load control
• IoT + Edge AI in diagnostic systems (ai-LAMP, poultry pathogens)

Publications

• M. Tharmakulasingam et al., "TransAMR: An Interpretable Transformer Model...", IEEE Access, 2023. [Link]
• M. Tharmakulasingam et al., "Explainable DL for AMR with Missing Labels...", IEEE Access, 2022. [Link]
• M. Tharmakulasingam et al., "VIDIIA Hunter...", Front. Mol. Biosci, 2023. [Link]
• S. Jeyakumar, M. Tharmakulasingam et al., "Blockchain DBMS for IoT", Knowledge Eng. Rev, 2020. [Link]

Awards

• 🏆 2nd Runner-up – McGinnis Venture Competition (Carnegie Mellon, $15,000)
• 🏅 MIT Hack4TheFuture Winner – AI & Healthcare Track
• 🎓 EPSRC Impact Grant – COVID-19 Diagnostic Device
• 📜 Conception X DeepTech Fellow (2022)
• 📖 Zoetis + CVSSP PhD Studentship (UK, 2019–2022)
• 🎖️ Dialog Merit Scholarship (2008 – District Top Ranker)