MrMuhammad Sakib Khan Inan

I am a PhD student focused on developing novel deep learning methods for IoT time series sensor data classification, with a strong emphasis on real-world applications. My research is supported by an Australian Research Council (ARC) Discovery Project (DP), which aims to establish a common IoT sensor data sharing platform. This platform addresses the global challenge of effectively sharing vast amounts of IoT data from heterogeneous sensors, many of which lack accurate textual metadata, thereby promoting sensor data reusability. Beyond my PhD research, I have significant experience working with medical imaging data, including breast ultrasonography and brain MRI, where I have applied computer vision and deep learning techniques for automated disease diagnosis. My work in this domain has contributed to advancements in early detection methods for diseases like breast cancer and Alzheimer's. I have also tackled various machine learning research problems in domains such as biomedical research and geotechnical engineering, including landslide susceptibility mapping, using tabular data. In addition to my academic pursuits, I am an active leader in the global tech community. As a Gold-level Microsoft Student Ambassador, I have mentored and taught students worldwide about emerging technologies through seminars, workshops, and educational content, leveraging support from Microsoft. I also bring industry experience in MLOps, where I contributed to the development of tools integrating the feature of training loggers / callbacks for effectively tracking the lifecycle of machine learning experiments. My diverse expertise bridges academia, industry, and community leadership, reflecting my passion for impactful research and knowledge sharing.