جستجوی استاد راهنمای دانشگاهی

• Road Safety
• Human Factors
• Driver Behavior
• +۷ مورد دیگر

Christine Mulvihill is a Research Fellow in the Human Factors Team at the Monash University Accident Research Centre (MUARC), Faculty of Medicine, Nursing and Health Sciences, Monash University. Her work focuses on road safety, particularly driver and motorcycle rider behavior, training program development, and licensing system evaluation. Her research interests span road safety , human factors , driver behavior , motorcycle rider training , and behavioral adaptation to vehicle technologies . She has led and contributed to significant research initiatives in Victoria, Australia, addressing safety for motorcyclists, emergency vehicle operators, and rail level crossing users. The analysis of her recent publications shows a strong trend toward applied research in transportation safety, with emphasis on systems thinking , evidence-based guidelines , and human-machine interaction . Her work integrates behavioral science with engineering solutions to improve real-world safety outcomes. Scientific Contributions: Extensive research output including peer-reviewed articles, technical reports, and commissioned studies. Projects funded by Transport Accident Commission (TAC), Department of Health (Victoria), and Metro Trains Melbourne. Contributions to UN Sustainable Development Goals related to sustainable cities and road safety (SDG 3 and SDG 11). Advising and Grants: While no formal students are listed, Christine has served as a Chief Investigator on 18 research projects, managing grants from public and transport safety agencies. Her leadership in large-scale evaluations demonstrates significant responsibility in research management and implementation. Labs and Teams: She is an integral member of the Human Factors Team at MUARC, a leading research center in accident and injury prevention. The team conducts multidisciplinary research involving psychology, engineering, and public health to develop safer transport systems.

Arooran Sounthararajahمشاهده پروفایل

استاد مدعو

• Civil Engineering
• Pavement Engineering
• Material Science
• +۴ مورد دیگر

Arooran Sounthararajah is an Adjunct Professor in the Department of Civil & Environmental Engineering at Monash University, affiliated with research projects focused on pavement engineering, smart construction technologies, and infrastructure sustainability. He leads and collaborates in projects involving big data analytics, machine learning for pavement life prediction, and geotechnical solutions for road durability. Education: While specific academic credentials aren’t detailed, his extensive involvement in advanced material testing and computational modeling suggests expertise in civil engineering and materials science. Research Interests: His work spans pavement material innovation, intelligent compaction systems, dust emission quantification via AI, and infrastructure resilience against environmental stresses. Key techniques include discrete element modeling, fiber optic sensing, and semantic segmentation for real-world applications. Publications: Recent works emphasize data-driven approaches to pavement performance, fatigue analysis of cement-bound materials, and 3D printing for rehabilitation. His contributions bridge traditional engineering methods with emerging technologies like IoT and machine learning. Awards/Grants: No explicit awards are listed, but his projects have attracted funding for initiatives like geogrid-reinforced asphalt and smart sensing systems. Advising & Labs: While students aren’t listed, his project roles as 'Project Manager' indicate leadership in multi-institutional teams. Collaborations include institutions like the University of Melbourne and industry partners in construction tech. Labs/Teams: Engaged with Monash’s civil engineering labs specializing in pavement testing and smart infrastructure systems, though specific lab names aren’t provided.

Naim Rastgooمشاهده پروفایل

دانشگاهی

• Human-Machine Teaming
• Trustworthy AI
• Adaptive AI Systems
• +۴ مورد دیگر

Dr. Naim Rastgoo is a Senior Research Fellow in the Department of Data Science & AI at Monash University's Faculty of Information Technology. His research focuses on developing trustworthy and adaptive AI systems for human-machine teaming in high-stakes environments. He holds a PhD in Computer Science from Queensland University of Technology (2015–2018) and an AI Master's from Universiti Kebangsaan Malaysia (2011–2013). Key research areas include autonomous systems, AI trust/explainability, deep learning, and affective computing. He has secured over $3M in research funding, including a 2025–2027 AU$468K project on bidirectional trust modeling in human-machine teaming. His work spans academic-industry collaborations and contributes to UN SDGs through AI education and healthcare applications. Teaching Experience: Postgraduate/undergraduate courses at Monash, Deakin, QUT, and National University of Malaysia (2011–present) Award Highlights: EdTech Cool Tool Finalist, HolonIQ ANZ EdTech 50, HDR High Achiever Award Labs/Teams: Leads Monash's AI Trustworthiness Initiative and collaborates with industry partners on AI ethics and autonomous systems His 19 publications include top-tier journals like IEEE Transactions on Affective Computing and Expert Systems with Applications, focusing on multimodal fusion, human-centric AI, and safety-critical applications.

John-Paul Nicoloمشاهده پروفایل

پژوهشگر ارشد

• Epilepsy
• Post-stroke epilepsy
• Neuroimaging
• +۷ مورد دیگر

John-Paul Nicolo is an Adjunct Research Associate in the Department of Neuroscience at Monash University, Faculty of Medicine, Nursing and Health Sciences. He is a consultant neurologist and epileptologist, currently serving as acting head of the epilepsy program at Royal Melbourne Hospital, with clinical appointments also at the Alfred Hospital and University Hospital Geelong. His research focuses on epilepsy , particularly post-stroke epilepsy , novel imaging biomarkers , and the application of 7-tesla MRI . He has pioneered advanced neuroimaging techniques to predict and understand epileptogenesis after stroke. His work also explores the role of the glymphatic system and perivascular spaces in epilepsy, and he is involved in developing machine learning models for personalized epilepsy management. The recent articles highlight a strong trend in translational neuroscience and clinical neurology , with a focus on improving diagnostic accuracy, surgical outcomes, and personalized treatment approaches in epilepsy. His publications include systematic reviews, meta-analyses, and clinical trial protocols, reflecting both methodological rigor and clinical relevance. John-Paul Nicolo is actively engaged in several major research projects, including the PERSONAL Trial, the PEPSTEP trial, and studies on med-tech dietary therapies and machine learning in epilepsy care, serving as Chief or Associate Investigator. He collaborates extensively with leading researchers in the field, including Professor Patrick Kwan, Professor Terence O'Brien, and Dr. Lucinda Vivash. His work contributes to advancing epilepsy care and aligns with global health goals, particularly those related to neurological disorders and equitable healthcare.

• Data Management
• Data Analytics
• Spatio-temporal Databases
• +۹ مورد دیگر

Mohammed Eunus Ali is a Senior Lecturer in the Department of Software Systems & Cybersecurity within the Faculty of Information Technology at Monash University, Australia. He holds a PhD in Computer Science and Software Engineering from the University of Melbourne and has previously served as a Professor at the Bangladesh University of Engineering and Technology (BUET), where he led a research group in Data Science and Engineering for over a decade. He has also held research positions at Monash University, Swinburne University, the University of Melbourne, and RMIT University. PhD : Computer Science and Software Engineering, University of Melbourne (2010) M.Sc. Engg. : Computer Science and Engineering, Bangladesh University of Engineering and Technology (2002) B.Sc. Engg. : Computer Science and Engineering, Bangladesh University of Engineering and Technology (1999) Dr. Ali’s research spans data management, analytics, and learning , with a strong focus on spatio-temporal data, geo-social networks, and multimodal high-dimensional data . His work enables applications in urban computing, intelligent transportation systems, and smart, sustainable cities . In recent years, he has expanded into Generative AI and large language models (LLMs) , exploring their role in enhancing geo-spatial query processing, SQL generation, and data engineering tasks. His publications appear in top-tier venues such as ACL, TKDE, VLDB, ICDE, SIGSPATIAL, and IEEE Access . His recent publications reflect a strong trend toward AI-driven solutions for real-world spatial and health problems , including blood glucose prediction for diabetics, seismic intensity forecasting, eco-friendly route planning, and LLM-based code generation. These works demonstrate a convergence of deep learning, spatio-temporal analytics, and real-world system design . Scientific Awards: Bangladesh University Grants Commission Award (2012) ADC Best Poster Award (2016) SSTD Best Demo Award (2017) ADC Best Paper Award (2022) Dr. Ali actively contributes to the research community as a Program Committee Member for premier conferences including SIGMOD, VLDB, ICDE, and SIGSPATIAL . He is a Senior Member of the ACM and currently supervises PhD students, focusing on cutting-edge topics in data science and AI. His collaborative research network spans institutions in Australia and Bangladesh, contributing to advancements in both academic and applied domains. His work aligns with the UN Sustainable Development Goals , particularly in the areas of sustainable cities, innovation, and quality education.

Shobi Sivathambooمشاهده پروفایل

پژوهشگر ارشد

• Sudden Unexpected Death in Epilepsy (SUDEP)
• Epilepsy
• Cardiorespiratory Function
• +۷ مورد دیگر

Dr. Shobi Sivathamboo is a Senior Research Fellow in the Department of Neuroscience at the Faculty of Medicine, Monash University. She also holds an external research position at Alfred Hospital. She leads the SUDEP research group, focusing on identifying biomarkers and risk factors for sudden unexpected death in epilepsy, and developing wearable technologies for out-of-hospital seizure detection and early alerts. Education: PhD in Cardiorespiratory Function in Epilepsy, University of Melbourne, 2019 Her research interests include sudden unexpected death in epilepsy (SUDEP), epilepsy, cardiac comorbidities, seizure detection technologies, wearable devices, and artificial intelligence in neurology. She investigates how cardiorespiratory dysfunction contributes to SUDEP and aims to improve early detection and intervention for high-risk patients. The recent articles highlight a strong focus on SUDEP, seizure detection using AI and EEG, clinical diagnostic criteria for epilepsy syndromes, and systematic reviews on cardiac abnormalities in epilepsy. Her work increasingly integrates technology and large-scale data analysis to improve clinical outcomes. Scientific Awards: Bridging Postdoctoral Fellowship 2020 Developing Predictive Biomarkers of Epilepsy Seizures Prize (2016) Dr. Sivathamboo has secured over $2.5 million in competitive and industry funding, including an NHMRC Emerging Leadership Grant. She is a principal investigator in a global study across 86 epilepsy centers and mentors PhD students. She is also an active member of the International League Against Epilepsy (ILAE) SUDEP Task Force. She leads the SUDEP research group at Monash University and collaborates with multidisciplinary teams across neurology, cardiology, engineering, and data science. Her lab focuses on translating research into clinical tools for precision-based epilepsy care.

Victoria Marمشاهده پروفایل

استاد مدعو

• Melanoma Research
• Clinical Dermatology
• Translational Medicine
• +۷ مورد دیگر

Victoria Mar is an Adjunct Professor at the School of Public Health and Preventive Medicine, Monash University, and Director of the Victorian Melanoma Service at The Alfred Hospital. She is an NHMRC Early Career Fellow with a strong focus on melanoma research, clinical care, and translational medicine. Her work spans clinical dermatology, public health, and AI-driven diagnostics. MBBS (Hons), FACD, PhD (Monash University/VMS and Peter MacCallum, 2014) NHMRC Early Career Fellow Fellow of the Australasian College of Dermatologists Her research interests center on early diagnosis and surveillance of high-risk individuals for melanoma. She leads and participates in numerous clinical and translational research projects, with a growing emphasis on integrating artificial intelligence into dermatological practice for improved diagnostic accuracy and patient outcomes. Her work contributes to national health policy through involvement in the Cancer Council Australia Melanoma Guidelines Working Group and leadership in the Melanoma Clinical Outcomes Registry. Recent publications highlight a strong trend in applying AI to dermatology, particularly in skin lesion classification, domain generalization, and multi-task learning models. These works aim to overcome clinical translation challenges and improve diagnostic performance using deep learning and prompt-driven frameworks. Australian Rheumatology Association, Annual Scientific Meeting, Best Clinical Paper Award (2023) Victoria Mar supervises doctoral students and leads major research projects such as 'Data driven approaches to outsmart skin cancer' and the 'Melanoma Research Victoria (MRV) Collaboration'. She is also a Chief Investigator on trials including the SiroSkin study and Melanoma-ROSA. Her work is supported by NHMRC and other national funding bodies, reflecting sustained grant success. She leads the Victorian Melanoma Service, a key clinical and research hub, and is actively involved in national and international research networks focused on improving melanoma outcomes.

Adamu Muhammad Buhariمشاهده پروفایل

مدرس

• Computer Vision
• Artificial Intelligence (AI)
• Real-Time Machine Learning Algorithms
• +۷ مورد دیگر

Adamu Muhammad Buhari is a Lecturer at the School of Information Technology, Monash University. His expertise spans Computer Vision, Artificial Intelligence, Real-Time Machine Learning, and IoT integration in smart systems. He holds a PhD in Engineering (Computer Vision) from Multimedia University, alongside advanced degrees in Engineering and Telecommunication. Research interests include micro-expression recognition using graph-based features, real-time emotion analysis algorithms, and scalable video coding with watermarking. His work bridges theoretical advancements with practical applications in embedded systems and energy-efficient IoT networks. Recent collaborations focus on smart building HVAC automation and solar-powered sensor networks for smart homes. He has been awarded the School Research Grant 2022 for contributions to clinical pharmacy education research. His publications span journals like Journal of Imaging and Multimedia Tools and Applications , with a focus on real-time systems and machine learning applications. Research output highlights include: Invisible emotion magnification algorithms for micro-expression detection IoT-based HVAC systems using machine learning Scalable video coding with low-complexity watermarking His work emphasizes real-world impact through embedded systems and energy harvesting solutions.

Greg Falzonمشاهده پروفایل

دانشیار

• Precision Agriculture
• Artificial Intelligence
• Data Science
• +۸ مورد دیگر

Greg Falzon is an Associate Professor of Precision Agriculture Systems at Flinders University's College of Science and Engineering. His work focuses on advancing agricultural technology through artificial intelligence, data science, and machine learning to address food security challenges. He holds a PhD in Biomedical Image Analysis from the University of New England (2011) and has a strong record in industry-funded research, including over $26 million in grants. Notable projects include the e-Technology Hub for pest management and the Wild Dog Alert System. His research spans agriculture sectors like cotton, dairy, grains, and livestock, with global impacts. Awards include the 2020 Australian Academy of Technology & Engineering ICM Agrifood Award and the 2016 President’s Medal from the Australian Society of Sugar Cane Technologists. Falzon teaches courses in Artificial Intelligence, Data Science, and Statistics, and actively mentors students in these fields. Key contributions include innovative systems for wildlife monitoring (e.g., Sentinel Bait Station), livestock vocalization detection, and automated cattle counting. His work emphasizes interdisciplinary approaches, combining computational, biological, and physical sciences for tangible agricultural outcomes.

• Forestry
• Geospatial Science
• Remote Sensing
• +۴ مورد دیگر

Dr. Grant Pearse is a Senior Lecturer in Remote Sensing and Geographic Information Systems (GIS) at Flinders University, specializing in the integration of remote sensing technologies and artificial intelligence for applications in managed forestry systems. His expertise spans LiDAR, UAV systems, multispectral/hyperspectral imaging, and satellite data analysis. Qualifications: PhD (University of Canterbury), Bachelor of Forestry Science (First Class Honours, University of Canterbury) Research Focus: Innovations in 3D deep learning, synthetic data generation, multi-sensor Earth Observation (EO) data integration, and cloud-native geospatial workflows. His work has pioneered automated analysis techniques for regional-scale forest inventory and health monitoring. Scientific Awards: Recognized with multiple honors including the Roger Newman Award for Science Excellence and the NZIF Schlich Memorial Prize.

• Computational Geophysics
• Seismology
• Machine Learning Applications
• +۷ مورد دیگر

Professor Anya M. Reading is a distinguished academic in the School of Natural Sciences at the University of Tasmania, where she serves as Professor of Physics. She leads the Compute Antarctic Group and holds key leadership positions including Program Lead for Circum Antarctic and East Antarctic at the Australian Centre of Excellence for Antarctic Science (ACEAS) since 2021, and Chair of the Coordinating Committee for East Antarctica at the International Lithosphere Program. Professor Reading earned her PhD from the University of Leeds (1997), BSc from the University of Edinburgh (1991), and a Diploma of Music from the Open University (1998). Her academic journey has positioned her as a world leader in computational geophysics and Antarctic research. Professor Reading's research spans three interconnected domains that have defined her 30+ year career in geophysics. Her primary focus is on computational data inference , where she pioneers advanced techniques in inverse theory and machine learning applied to earthquake seismology, plate tectonic structure, and environmental applications of seismology. She has made significant contributions to pioneer geophysical data collection , leading observational seismology and interdisciplinary field programs in remote environments including Antarctica and outback Australia. Her work on interdisciplinary insight generation focuses on East Antarctica, developing innovative computational strategies to optimize data collection in regions of societal relevance. Her research bridges geophysics, climate science, and computational methods to address critical questions about ice sheet dynamics and Earth systems. Professor Reading's recent publications reveal a strong trend toward integrating machine learning with traditional geophysics to study Antarctic ice sheets. Her work increasingly focuses on cryoseismology - using seismic signals to monitor glacial processes hidden from satellite observation. A significant portion addresses the ice-bedrock interface, examining how geothermal heat flow influences ice sheet stability. Her publications demonstrate growing emphasis on interdisciplinary approaches combining seismology, magnetotellurics, and computational modeling. Professor Reading's significant honors include: University of Tasmania College of Sciences and Engineering Research Award (Medal, 2021) Vice-Chancellor's Leadership Award (Medal, 2019) Fulbright Senior Scholar (2016/17) As an educator and mentor, Professor Reading has supervised over 15 PhD students since 1998. She has secured substantial research funding, with current projects totaling over $6.5 million including an ARC Discovery Project on Antarctic outlet glaciers and the GRIT Phase 3 project for continental-scale geophysical monitoring in Antarctica. Her leadership extends to directing major research infrastructure initiatives that have transformed Australia's capacity for Antarctic research. Professor Reading leads the Compute Antarctic Group, a dynamic research team focused on computational geophysics and Antarctic research. She also plays a central role in the Australian Centre of Excellence for Antarctic Science, coordinating interdisciplinary research across multiple institutions. Through these groups, she fosters a collaborative environment that integrates field observations, computational modeling, and machine learning to address pressing questions about Antarctic systems and their global implications.

John George Lockمشاهده پروفایل

مدرس ارشد

• Cell Biology
• Cancer Research
• Personalized Medicine
• +۱۱ مورد دیگر

Dr. John George Lock is a Senior Lecturer and Head of the Cancer Systems Microscopy lab within the Department of Pharmacology at the School of Biomedical Sciences, University of New South Wales (UNSW). He also serves as Associate Director of Research for the School of Biomedical Sciences, Deputy Chair of the School's Research Strategy Committee, and Chair of the HDR review panel. Dr. Lock is affiliated with multiple research networks including the UNSW Artificial Intelligence Institute, Data Science Hub, and AI & Data Science Network, as well as the Garvan Institute of Medical Research Imaging Platform Strategic Advisory Committee. Dr. Lock earned his PhD from the Institute for Molecular Bioscience at the University of Queensland (2001-2006), preceded by First Class Honours in Biochemistry (2000-2001) and a BSc in Biochemistry (1997-2000). His postdoctoral research began at the Karolinska Institute in Stockholm with fellowships from the Wenner-Gren Foundation and Swedish Cancer Foundation. He was accelerated to Assistant Professor for pioneering Systems Microscopy and leading a 9-person multidisciplinary team before returning to Australia to work with Professor Katharina Gaus at UNSW. Dr. Lock's research centers on Systems Microscopy, an innovative approach that integrates imaging-based methods with computational analysis to advance cancer treatment outcomes. His Cancer Systems Microscopy (CSM) lab focuses on three main areas: Precision Diagnostics using automated multiplexed quantitative imaging of circulating tumor cells; Targeted Therapies through novel high-content strategies for drug discovery; and Fundamental Insights into cancer progression mechanisms. The CSM lab has established collaborations with fundamental and translational cancer researchers, clinicians, commercial technology developers, and data science experts, creating a truly multidisciplinary ecosystem. Analysis of Dr. Lock's extensive publication record reveals a strong focus on advancing cancer diagnostics and treatment through the integration of imaging technologies and artificial intelligence. His work consistently bridges fundamental cell biology with clinical applications, particularly in prostate cancer and metastasis research. A significant trend across his recent publications involves developing computational methods to analyze cell state plasticity, tumor heterogeneity, and signaling pathways using advanced imaging techniques. Eva & Alex Wallestroms Foundation Award (2008) Karolinska Institute Young Researcher Award (2010) Ramaciotti Biomedical Research Award (2017) Finalist in Shenzhen Innovation & Entrepreneurship International Competition (Australasia), 3rd place (2021) UNSW Scientia Fellow (2023) Dr. Lock actively supervises research students as Primary supervisor of 4 HDR students and Joint Supervisor of 1 HDR student. His grant portfolio demonstrates substantial funding success, with recent awards including NHMRC Ideas grants (2024), an NHMRC Equipment Grant (2024), a UNSW Scientia Fellowship (2023-2027), and multiple NHMRC and ARC grants spanning from 2016 to present. These grants support his work on liquid biopsy for personalized medicine, AI-driven image analysis, and drug discovery platforms. Dr. Lock co-founded the Systems Microscopy Australia Network and co-organizes the Functional High Throughput Technologies Australia meeting, demonstrating leadership in building national research capacity. The Cancer Systems Microscopy lab operates as a cutting-edge facility that has grown significantly since its initiation in 2018. Dr. Lock helped conceive and fund Australia's first dedicated Systems Microscopy facility with $2.5M funding from the Australian Research Council and the Ramaciotti Biomedical Research Award. The lab's multidisciplinary team integrates expertise in cell biology, microscopy, statistics, machine learning, and data visualization to tackle complex cancer research questions. The CSM lab has established strategic partnerships with the Ingham Institute for Applied Medical Research, PeterMacCallum Cancer Centre, and various commercial technology developers, creating a robust ecosystem for translating basic research into clinical applications.

Fabrizzio Horta Nunezمشاهده پروفایل

مدرس

• Reproduction
• Obstetrics & Gynecology
• Fertility/Infertility
• +۷ مورد دیگر

Dr Fabrizzio Horta Nunez is a medical reproductive scientist and lecturer at the University of New South Wales (UNSW), Faculty of Medicine, where he teaches in the Master of Reproductive Medicine program. He maintains dual appointments at UNSW's Wallace Wurth Building in Kensington and the Royal Hospital for Women in Randwick, reflecting his clinical and academic integration in women's reproductive healthcare. Dr Horta Nunez's research spans reproductive biology, assisted reproductive technology, and the innovative application of artificial intelligence to fertility treatments. His work focuses on developing non-invasive biomarkers for gamete and embryo quality assessment, with particular emphasis on metabolic imaging techniques and machine learning algorithms that can predict IVF outcomes. His research bridges fundamental reproductive science with clinical applications, aiming to revolutionize diagnostic approaches in infertility treatment. His publication portfolio demonstrates a clear trajectory toward integrating advanced computational methods with reproductive medicine, with recent work emphasizing non-invasive metabolic imaging, pharmacogenomics in IVF, and AI-driven clinical decision support systems. This research direction reflects the growing intersection of data science and reproductive healthcare, with potential to significantly improve success rates in assisted reproductive technologies. The best student of Medical Technology in 2005, Diego Portales University ($500 AUD) Chilean master scholarship 'Becas Chile' (2012, $80,000 AUD) Monash Graduate Scholarship (2016) Multiple SIRT Student Travel Awards (2017-2018) Best research presentation at EPRD 30-year symposium (2018, $1,000 AUD) Monash accelerator program Pitch award (2020, $2,000) ARCS exchange session prize at SIRT/FSANZ conference (2022, $5,000) Fellowship FMNHS ECR award ($35,000) Best overall presentation, Melbourne emerging leaders (2023, $0.4K) As a chief investigator on multiple significant grants totaling over $3.3 million AUD, Dr Horta Nunez demonstrates strong research leadership in reproductive medicine. His collaborative approach is evident in his partnerships with clinicians, engineers, and data scientists across institutions. While specific student supervision isn't detailed in the available information, his role as lecturer in the Master of Reproductive Medicine program suggests active involvement in graduate education. His research infrastructure includes collaborations with engineering teams developing microfluidic platforms for non-invasive imaging, indicating interdisciplinary laboratory capabilities.

Christopher Bamboroughمشاهده پروفایل

پژوهشگر ارشد

• Architectural Data
• Digital Fabrication
• Computational Design
• +۶ مورد دیگر

Dr Christopher Bamborough is a Research Fellow at the University of New South Wales, working within the ARC Centre for Next-Generation Architectural Manufacturing (Arch_Manu). He is affiliated with the School of Built Environment in the Faculty of Arts, Design & Architecture. His research examines the role of data in architectural practice, focusing on its technical, cultural, and material impacts. His PhD thesis argued that while data has long been integral to architecture, its digital form introduces a significant and evolving non-human influence on practice. AI and automation are central to this shift, raising critical questions about authorship and the evolving role of human designers. Dr Bamborough's work highlights the moments where architects enter into machine collaboration and explores the practical and material consequences of these interactions. Dr Bamborough's recent publications focus on the intersection of data, architecture, and digital fabrication. His work explores how data shapes architectural practice and how emerging technologies transform the built environment. Key themes include the cultural implications of data in architecture, the relationship between human designers and AI systems, and sustainable approaches to digital fabrication in construction. His scientific contributions include: "Consolidated Empirical Bio-material Repository" (2025) "Towards an interdisciplinary academia industry research nexus - Collaborative Pathways to Sustainable Digital Innovation in AEC" (2025) "The nature of data in early modern architectural practice." (2019) "Running out of STE(A)M: A critical perspective on the political rhetoric of innovation." (2016) Dr Bamborough actively supervises MPhil candidates engaged in practice-based design research, investigating topics related to data and circularity, and digital transformation in the architecture, engineering and construction (AEC) sector. With over fifteen years of teaching experience, he has designed curriculum and coordinated courses across undergraduate design, construction, and history/theory. His teaching approach emphasizes student-centered learning techniques and innovative digital pedagogy. He is also involved in creative projects including audio-visual works under the "smth::motion" series, which explore the intersection of music, movement, and digital visualization through technologies like the Xbox Kinect.

Jiankun Huمشاهده پروفایل

استاد

• Cyber Security
• Intrusion Detection
• Applied Cryptography
• +۱۶ مورد دیگر

Professor Jiankun Hu is an IEEE Fellow and full professor of Cyber Security at the School of Engineering and Information Technology, University of New South Wales at the Australian Defence Force Academy (UNSW@ADFA), Australia. His primary research focuses on computer networking and security, particularly biometric security and cybersecurity applications. Professor Hu earned his Bachelor's degree in industrial automation in 1983 from Hunan University, China, followed by a PhD in engineering in 1993 from Harbin Institute of Technology, China. He completed a Master's degree in computer science and software engineering from Monash University, Australia in 2000. His postdoctoral work includes research at Harbin Shipbuilding College (1995), Ruhr University in Germany as an Alexander von Humboldt Foundation fellow (1995-1997), and Delft University of Technology in the Netherlands (1997). His research spans multiple domains including cybersecurity, biometrics, image processing, and artificial intelligence. Key areas include intrusion detection systems, applied cryptography, network security, biometrics security, image and video processing, and machine learning applications. He has made significant contributions to fingerprint recognition systems, privacy-preserving biometric authentication, and cybersecurity for smart grids. Professor Hu's recent publications demonstrate a strong focus on privacy-preserving technologies for biometric systems, blockchain security, smart grid protection, and advanced machine learning applications for cybersecurity. His work bridges theoretical advances with practical implementations in real-world systems, particularly in securing critical infrastructure and developing robust biometric authentication methods. He has received significant recognition including IEEE Fellow status and has been awarded ten Australian Research Council Grants. He has served in editorial roles for prestigious journals including IEEE TIFS (as Senior Area Editor), Journal of Security and Communication Networks, KSII TIIS, IET CPS, and IEEE OJCS. Professor Hu has held leadership positions in major conferences, serving as Security Symposium Co-Chair for IEEE GLOBECOM '08 and IEEE ICC '09, and Program Co-Chair of the 2008 International Symposium on Computer Science and its Applications. He maintains an active research program with numerous publications across top-tier venues.