جست‌وجوی استاد و پژوهشگر

• Quantum Technologies
• Optical Nanosensing
• Nanodiamond Physics
• +۳ مورد دیگر

Associate Professor Taras Plakhotnik is a faculty member at the School of Mathematics and Physics, University of Queensland. His research integrates atomic/molecular physics, quantum optics, and nanomaterials, with emphasis on nanodiamond-based sensors for biological and quantum applications. He teaches undergraduate courses in quantum physics, electronics, and statistical mechanics. Research interests span: Quantum Technologies : Development of rubyene platforms and nitrogen-vacancy (NV) centers in nanodiamonds for quantum sensing. Optical Nanosensing : Ultrasensitive thermometry, intracellular thermal conductivity mapping, and photothermal applications using hybrid diamond nanosensors. Spectroscopy : Advanced techniques for single-molecule detection, Raman scattering in atmospheric science, and low-light spectroscopy with sCMOS cameras. Recent publications (2021–2025) predominantly explore: Nanodiamond sensors for intracellular thermal monitoring. Metamaterials for subwavelength imaging. Rubyene nanoparticles for quantum-enhanced imaging. High-precision atmospheric water-content measurements using Raman lidar. No scientific awards are documented. He has supervised three PhD students to completion, focusing on NV-center applications in thermometry/magnetometry, and holds grants from international agencies like the Human Frontier Science Program.

Joel Than Chia Mingمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Deep Learning
• Machine Learning
• +۴ مورد دیگر

Dr. Joel Than Chia Ming serves as Senior Lecturer and Head of Department for Information Technology & Software Engineering at Swinburne University of Technology's Sarawak Campus Faculty of Engineering, Computing and Science. Joining in 2020 after completing his PhD and postdoctoral work at Universiti Teknologi Malaysia (UTM), he leads research in AI-driven medical imaging solutions with national grant funding. His academic foundation includes: Bachelor of Engineering (Biomedical), Universiti Tunku Abdul Rahman (2013) Master of Philosophy, Universiti Teknologi Malaysia (2015) Doctor of Philosophy in Deep Learning & Medical Imaging, Universiti Teknologi Malaysia (2019) Dr. Than's research program bridges artificial intelligence with clinical medicine, focusing on lung disease diagnosis through deep learning and explainable AI systems. His work integrates multi-modal data fusion for applications ranging from pandemic hospital planning to coronary artery disease detection. Current projects emphasize clinical interpretability of AI models to build trust in medical decision support systems. His publication portfolio demonstrates consistent growth in medical AI, with recent work shifting toward explainable frameworks for lung severity classification and cross-domain applications like smart construction. This evolution reflects strategic expansion from pure image analysis to integrated AI solutions with real-world implementation pathways. Key recognitions include: 3-Minute Thesis Champion, IEEE ICSIPA 2019 Best Paper Award, ICBAPS 2018 IEEE Signal Processing Malaysia Best Master Thesis Award (2016) UTM Razak Faculty Best Master Student (2016) IEEE ISSBES Best Student Paper (2015) Dr. Than actively supervises research students through three active FRGS grants, maintaining close mentorship with emphasis on clinical validation and industry translation. His research group operates within Swinburne's engineering infrastructure, collaborating with Sarawak healthcare providers to ensure medical relevance. Prospective students receive direct access to grant resources including GPU computing clusters and clinical imaging datasets. The research environment fosters interdisciplinary work connecting computer science with biomedical engineering, preparing students for careers in healthcare AI through hands-on experience with real clinical challenges and international conference participation.