Dr. Farhad Ahamed is an academic and researcher focusing in Cybersecurity, Applied Machine Learning, and Computational Intelligence. He has contributed to research areas such as Biometrics, Smart Aging and Network Security. His research often integrates machine learning with other disciplines, such as cybersecurity, healthcare, environmental science, and industrial automation. He has worked on predictive diagnostics in healthcare, identifying early detection of dementia using machine learning and IoT, multimodal fall detection using wearable and remote sensors, multimodal heartrate based authentication using AI. His work also extends to AI-based flood estimation by analyse flood catchment data.

He was a Google mentor of Cybersecurity and Machine Learning at Western Sydney University (Google exploreCSR) and supervised ML-based projects focusing on biometrics, fake news and image identification. He is actively involved in mentoring PhD students and early-career researchers, fostering the next generation of machine-learning experts.

His current projects are listed below,

1. Artificial intelligence in Predictive Cybersecurity Analytics
2. Regional Flood Modelling Using Artificial Intelligence
3. The Challenges and Guidelines for Self-supervising AI Systems
4. Usable Biometric Authentication Using ECG and Heart Rate Data
5. Privacy Preserving Multimodal Biometric Authentication for Anti-Spoofing
6. Identifying Early signs of Dementia using AI in Smart Environment
7. Automated speech and recitation ranking using Machine Learning