Prof Christina Lim is a Professor at the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. She serves as the Associate Dean of Research for the Faculty of Engineering and Information Technology (FEIT) and manages the Tucker Lab. Previously, she held roles as Research Group Leader of the Electronics and Photonics System group and Deputy Head of Department (Teaching and Operations) Education: PhD and Bachelors from University of Melbourne Research Interests: Radio-over-Fibre, Optical Wireless Communications, Microwave Photonics, Augmented Reality Displays, Reservoir Computing, Optical Crosshaul Networks Recent publications demonstrate expertise in optical waveguide design for AR, underwater optical wireless communications, photonic switching, and network optimization. Her projects focus on next-generation wireless infrastructure, including Photonics Computing Enabled Ultra-Broadband Wireless Communications (2024-2027, $598k ARC grant) and Additive Manufacturing of Optical Elements (2025). She has secured significant funding, including ARC Discovery Projects and Future Fellowships. Scientific Honors IEEE Fellow (2022) Optica Fellow (2018) ARC Future Fellow (2009-2013) ARC Australian Research Fellow (2004-2008) Professional Service Vice-President of Conferences, IEEE Photonics Society Deputy Editor, IEEE/Optica Journal of Lightwave Technology ARC College of Experts (2014-2016)
Professor Stefan Maier holds the position of Head of School in Physics and Astronomy at Monash University. Previously, he served as the Lee Lucas Chair in Experimental Physics at Imperial College London (2007–2018) and built a new chair at Ludwig-Maximilians-Universität München (2019–2022). His research focuses on nanophotonics, plasmonics, and metasurface engineering, with emphasis on optical trapping, nonlinear optics, and novel photonic devices. Education: Bachelor’s degree in Physics, Technical University of Munich M.Sc. and Ph.D. in Applied Physics, California Institute of Technology (Caltech) Research Interests: Development of metamaterials and metasurfaces for light manipulation Applications of nanophotonics in sensing, imaging, and quantum technologies Optical trapping and plasmonic catalysis Nonlinear optical phenomena in nanostructured materials Articles Trends: Recent work emphasizes bound states in the continuum (BICs), 3D nanoprinted optical platforms, and active metasurfaces with tunable properties. Key themes include hybrid nanophotonics, ultra-high-Q resonators, and plasmonic nanomaterials for energy applications. Awards: ISI Highly Cited Researcher (2017–present) Grants/Projects: Chief Investigator in the All-on-chip twisted light modulator project (2022–2025) Leadership in Monash’s nanophotonics research team Labs/Teams: Directs a multidisciplinary lab at Monash focused on integrating 3D nanofabrication with optical physics, including collaborations in metafiber development and plasmonic biosensing.
Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.
Distinguished Professor Dayong Jin is a leading academic in nanotechnology and biomedical engineering at the University of Technology Sydney (UTS). He holds roles including Director of the Institute for Biomedical Materials and Devices (IBMD), ARC Laureate Fellow, and Chair Professor at Southern University of Science and Technology (China). His research focuses on photonics, luminescent materials, and their applications in healthcare, including cancer detection, rapid diagnostics, and super-resolution microscopy. Key innovations include 'Nano Torch' technology for disease detection and 'Super Dots' nanocrystals for imaging and anti-counterfeiting. Education: PhD from Macquarie University (2007). Leadership: Established UTS's IBMD and multiple research hubs, including the ARC IDEAL Research Hub and Australia-China Joint Research Centre. Research Interests: Transforming nanophotonics into diagnostic tools, rapid antigen tests (e.g., for COVID-19), and biomedical devices. His work bridges physics, engineering, and biology to address global health challenges. Awards: Australian Museum Eureka Prize (2015), Prime Minister's Prize for Science (2017), ARC Laureate Fellowship (2021), and Fellow of the Australian Academy of Technology and Engineering. Grants: Overseeing funded projects on quantum biotechnology, deep-tissue imaging, and nanoscale thermometry. Active in interdisciplinary collaborations, including with Chinese institutions. Labs/Teams: Leads IBMD, the ARC IDEAL Hub, and the UTS-SUSTech Joint Research Centre, fostering innovation in wearable biomaterials and point-of-care technologies.
Steven Meikle is a Professor of Medical Imaging Physics and Head of the Imaging Physics Laboratory at the Brain and Mind Centre, University of Sydney. He also serves as Deputy Director (Preclinical) of Sydney Imaging and Deputy Director of the National Imaging Facility's Sydney node. His expertise spans advanced imaging technologies, with a focus on PET/SPECT instrumentation and molecular imaging. He holds a B.App.Sc.(Hons) from the University of Technology Sydney and a PhD from the University of New South Wales. Research focuses include developing novel PET systems like Open-field PET (for freely moving rodents) and Total Body PET, which enhance imaging sensitivity and enable real-time behavioral studies alongside brain function analysis. Collaborations include Tsinghua University (China) and UC Davis (USA). He leads projects on motion correction, quantitative imaging, and AI-driven analysis. Key achievements include over 180 peer-reviewed publications, editorial roles in Physics in Medicine and Biology , and leadership in professional societies. Awards include IEEE Senior Membership and Australian Institute of Physics Fellowship. Current student projects explore Total Body PET applications, motion correction, and radiopharmaceutical evaluation. Teaching roles include medical physics courses in diagnostic radiography and medical physics programs. He advises on imaging ethics, facility implementation, and translational research bridging basic science and clinical applications.
Dr. Chathura Bandutunga is a Research Fellow at the Centre for Gravitational Astrophysics within the Research School of Physics at the Australian National University (ANU). His research focuses on advanced optical techniques for precision measurement, with significant contributions to gravitational wave detection technology, molecular spectroscopy, and space exploration instrumentation. Dr. Bandutunga's research expertise spans digital interferometry, fiber optic sensors, and precision optical measurement systems. His work has pioneered digitally enhanced interferometric techniques that have enabled new capabilities in molecular dispersion spectroscopy, gravitational wave detection, and optical frequency referencing. He has developed innovative methods for phase noise suppression, common-mode noise rejection, and thermal-noise-limited optical measurements that operate at the boundaries of physical possibility. His publication record demonstrates consistent innovation in optical measurement technology, with recent work advancing fiber optic gyroscopes, frequency comb technology, and applications for interstellar propulsion systems like the Breakthrough Starshot program. His research bridges fundamental optical physics with practical applications in both terrestrial scientific instrumentation and space-based technologies. Dr. Bandutunga is actively involved in the Centre for Gravitational Astrophysics at ANU, contributing to Australia's participation in international gravitational wave research collaborations. His technical leadership in precision optical measurement systems directly supports next-generation gravitational wave detectors and related technologies requiring unprecedented measurement stability.
Associate Professor Andre Kyme is an academic staff member in the School of Biomedical Engineering at The University of Sydney. His research focuses on developing enabling technologies for biomedical imaging, including motion compensation in MRI/PET, robotic platforms for image-guided therapy, and cross-disciplinary applications like plant salt uptake analysis using PET. He collaborates with institutions globally and advises students on projects like lameness detection in horses and AI-based motion correction. Research Interests: Kyme's work spans motion correction in medical imaging modalities, medical robotics integration with imaging systems, and innovative applications of imaging technologies in non-traditional fields. His team emphasizes leveraging advancements in computer vision, machine learning, and instrumentation to improve imaging performance and accessibility. Recent Projects: Current research includes MRI-compatible robotic platforms for therapy applications, AI-driven lameness detection in horses, and pediatric neuroimaging improvements. He leads the BREEZE initiative to enhance MRI accessibility for children with cerebral palsy through eye-gaze communication technology. Publications: His work spans 20+ years with over 50 peer-reviewed publications in journals like Physics in Medicine and Biology and IEEE Transactions. Key areas include PET/SPECT/CT motion correction algorithms, robotic systems for medical imaging, and novel imaging applications in plant science. Teaching: Kyme instructs core biomedical engineering courses including thesis supervision and capstone projects at both undergraduate and postgraduate levels. Labs/Teams: Active in the Brain and Mind Centre and Biomedical Imaging, Visualisation and Information Technologies groups at Sydney. Collaborates with industry partners like TeleMedVet and academic institutions including University of California Davis and Chinese University of Hong Kong.
Professor David Taubman is a distinguished academic serving as Professor and Deputy Head of School (Research) at the School of Electrical Engineering and Telecommunications (EE&T) at the University of New South Wales (UNSW) in Sydney, Australia. He is also co-director of Kakadu Software Pty. Ltd. and its affiliates Kakadu R&D and Kakadu GPU. With a career spanning over three decades, Professor Taubman has made significant contributions to the field of image and video compression, most notably as the author of the EBCOT coding algorithm adopted in the JPEG2000 international standard. Professor Taubman earned his B.Sc. in Mathematics and Computer Science (1986) and B.E. (Medal) in Electrical Engineering (1988) from the University of Sydney, followed by an M.Sc. (1992) and Ph.D. (1994) in Electrical Engineering from the University of California at Berkeley. His professional journey includes engineering work at the Electricity Commission of N.S.W. (1988-1990), research positions at Hewlett-Packard Laboratories in Palo Alto (1994-1998), and an academic career at UNSW where he progressed from Senior Lecturer (1998-2003) to Associate Professor (2004-2009) and finally to Professor (2009-present). He has held various leadership roles including Head of the EE&T Telecommunications Research Group (2003-2014), Head of the EE&T Signal Processing Research Group (2014-present), Director of Research for the School of EE&T (2011-2016), and Deputy Head of School (Research) since 2017. Professor Taubman's research interests center on image and video compression, with particular expertise in JPEG2000 standards and implementations. His work spans signal processing, wavelet transforms, scalable video coding, motion modeling, and multimedia systems. He has pioneered numerous compression algorithms and frameworks, including the EBCOT coding algorithm that became central to the JPEG2000 standard. His recent research focuses on efficient motion modeling with cuboidal partitioning, learned lifting-based transform structures, and high-throughput implementations of JPEG2000 for video applications. His work bridges theoretical foundations with practical implementations, as evidenced by the commercially successful Kakadu Software tools that have garnered around 500 commercial licensees. Analysis of Professor Taubman's recent publications reveals a consistent focus on advancing compression technologies with particular emphasis on scalability, efficiency, and adaptability. His work spans traditional image compression (JPEG2000 extensions), video coding (cuboid-based partitioning for UHD/360-degree video), and emerging applications (nanopore sequencing data compression). A notable trend is the integration of machine learning techniques with traditional compression frameworks, as seen in his work on learned lifting-based transform structures. His research maintains strong connections to real-world applications across diverse domains including medical imaging, astronomical data processing, and genomic sequencing. IEEE Fellow Engineers Australia Fellow (by invitation) Professor Taubman has served as Associate Editor for the IEEE Transactions on Image Processing for two four-year appointments (2003-2005 and 2010-2013). He has been actively involved in numerous research grants focused on image and video compression technologies, particularly those related to the JPEG2000 standard and its extensions. His work has received significant industry support, reflected in his consultancy with various U.S., Japanese, and Australian corporations. He has also contributed to international standards development as a member of Standards Australia Technical Committee MS-065 (mirroring ISO TC42 on Digital Photography) and as a constitutional member of Standards Australia Technical Committee IT-029 (Coded Representation of Picture, Audio and Multimedia/Hypermedia Information). Professor Taubman co-directs Kakadu Software Pty. Ltd. and its research affiliates Kakadu R&D and Kakadu GPU, which have developed the commercially successful Kakadu Software tools for JPEG2000. His research group at UNSW focuses on advanced image and video compression techniques, with particular expertise in wavelet-based methods, scalable coding, and motion modeling. The group maintains strong industry connections and has contributed significantly to the development and standardization of image compression technologies worldwide.
Prof. Jay Guo is a Distinguished Professor and Founding Director of the Global Big Data Technologies Centre at the University of Technology Sydney (UTS). He also leads the New South Wales Connectivity Innovation Network (CIN) and the TPG-UTS Network Sensing Lab. With over 700 publications, 350+ IEEE journal papers, and 27 patents, his work focuses on 5G/6G antennas, integrated sensing and communications (ISAC), and environmental sensing using 5G/6G networks. Research Interests: 5G/6G Antenna Systems (reconfigurable arrays, multibeam antennas) In-Band Full-Duplex Wireless Systems Integrated Sensing and Communications (ISAC) Environmental Sensing via Network Infrastructure Awards & Recognition: IEEE Schelkunoff Prize Paper Award (2023) Fellowships: IEEE, Australian Academy of Engineering, Royal Society of NSW Australia Engineering Excellence Award (2007) Australia's Top Researcher in Electromagnetics (2020-2023) Highly Ranked Scholar (top 0.05% globally) Grants & Projects: NSW Government-funded environmental sensing projects Industry collaborations with TPG Telecom, Telstra, and CSIRO Leadership in global antenna conferences (e.g., IEEE APS, ISAP) Labs & Initiatives: Global Big Data Technologies Centre TPG-UTS Network Sensing Lab NSW CIN (Connectivity Innovation Network)
Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.
Dr. Ghazal Bargshady is a Lecturer at the University of Canberra , with expertise in Affective Computing , Artificial Intelligence , and Healthcare Technology . Her roles include teaching units such as Computer Vision, Data Analytics, and Soft Computing, as well as supervising PhD and Master by Research students in AI-driven projects for healthcare and road safety. Education: She earned her PhD in Artificial Intelligence and Computer Vision from the University of Southern Queensland in 2020. Research Interests: Dr. Bargshady specializes in Computer Vision Deep Learning Biosignal Processing Facial Expression Analysis Human Factors in AI Wearable Sensors Multimodal Data Fusion Brain–Computer Interfaces Her work addresses real-world challenges in pain assessment, depression recognition, and driver safety using cutting-edge AI models. Article Trends: Her recent publications focus on Transformer architectures , fNIRS signal analysis , multimodal pain detection , and depression severity estimation via facial video data. These studies highlight her contributions to AI in healthcare , transportation safety , and biomedical signal processing . Teaching Activities: Dr. Bargshady has lectured units including Programming for Data Science , Computer Vision , and Soft Computing , emphasizing practical AI applications.
Cormac Fay is a Research Fellow in Artificial Intelligence for Smart Cities at the School of Computing and Information Technology (SCIT), University of Wollongong, within the Faculty of Engineering and Information Sciences. His roles include affiliations with the SMART Infrastructure Facility and the ARC Centre of Excellence for Electromaterials Science. Previously, he held positions at Dublin City University, including post-doctoral roles in sensor research and data analytics. He holds a PhD in Engineering from Dublin City University (2013), an M.Eng. in Telecommunications Engineering (2007), and a B.Eng. in Mechatronic Engineering (2005). His research focuses on AI-driven smart city technologies, sensor systems for environmental monitoring, and advanced 3D printing materials. Key areas include IoT-enabled carbon-emission tracking, wearable biomedical devices, and sustainable sensor networks for landfill gas management. He has developed innovative solutions such as cryogenic 3D printing techniques for biocompatible inks and LED-based optical sensing platforms. Dr. Fay has secured grants totaling over $X million, including projects on military diver monitoring, blue carbon ecosystems, and low-cost sensor networks for agriculture and environmental safety. His work integrates interdisciplinary approaches, bridging materials science, biomedical engineering, and environmental engineering. Grants: Led projects on carbon-emission IoT systems, oyster farming sensors, and vibration monitoring. Supervision: Advised a Master's project on biomimetic microfluidic fabrication (2017–2019). Labs/Teams: Collaborates with the SCIT, SMART Infrastructure Facility, and global institutions like École Polytechnique Fédérale de Lausanne.
Assoc. Professor Enbang Li is a Senior Lecturer at the School of Physics within the Faculty of Engineering and Information Sciences at the University of Wollongong. His research focuses on photonics, medical physics, and optical sensor technologies with applications in radiation dosimetry, biomedical engineering, and wearable devices. He has supervised numerous PhD and Master’s students in areas such as fiber-optic dosimetry for radiotherapy, blood glucose sensing, and microfluidics. His work includes advancements in fiber-optic dosimeters for MRI-LINAC systems, polymer-based biosensors for glucose monitoring, and integrated photonic sensors for temperature and pressure measurements. He has secured funding from organizations like the Australian Synchrotron Research Program and the University of Wollongong for projects related to dosimetry and photonic integration. Recent publications highlight innovations in HDR brachytherapy dosimetry, flexible electro-optic modulators for ECG signals, and lab-on-a-chip systems. His research also extends to material science, including corrosion studies of Al-Mg alloys and the dynamic behavior of sunscreens under in-service conditions.
Ediz Cetin is an Associate Professor in Digital Electronics Engineering at Macquarie University's School of Engineering and a member of the Astrophysics and Space Technologies Research Centre. He serves as Course Director for the MEng Electronics Engineering program and Chair of the School's Postgraduate Coursework Committee. His research focuses on radio frequency interference mitigation, fault-tolerant reconfigurable circuits for space applications, machine learning in RF signal analysis, and low-power digital circuit design. Education: PhD in Signal Processing (Unsupervised Adaptive Signal Processing Techniques for Wireless Receivers) B.Eng. (Hons.) in Control and Computer Engineering Research Interests: RF interference detection and localization GNSS anti-jamming and spoofing detection FPGA-based reconfigurable systems Space instrumentation and CubeSat technologies Machine learning for signal processing Awards: Excellence in Learning Innovation (FSE Teaching Award, 2022) Highly Commended Finalist – Vice-Chancellor’s Award for Learning Innovation (2022) Innovative Approaches – Highly Commended (FSE Teaching Award, 2020) Key Projects: SmartSat CRC (2020–2026): Smart Satellite Technologies and Analytics Spacecraft Innovation Lab (2021–2022) CubeSat Biological Payload (2019–2022) Teaching Contributions: Led the 'Improving Student Engagement with Anywhere and Any-time Laboratory Access' initiative (2019–2020), enhancing remote lab accessibility for students.
Dr. Xiaoyi Tian is a Researcher at the School of Electrical and Computer Engineering, University of Sydney. They are affiliated with the University of Sydney Nano Institute and specialize in microwave photonics, sensor technology, and machine learning applications. Their research focuses on integrating machine learning with photonic sensors, particularly using microresonators and optical signal processing for high-resolution sensing. Key areas include microwave-photonic hybrid systems, signal processing algorithms, and sensor optimization. Dr. Tian has contributed to advancements in athermal sensors, subwavelength grating resonators, and recurrent neural networks for sensor performance enhancement. Their work spans conferences like OFC, CLEO-PR, and IEEE journals. No formal awards or student advisees are listed, though their publications reflect active collaboration in interdisciplinary research.
