جستجوی استاد راهنمای دانشگاهی

Professor Maria Craig is a distinguished academic and researcher at the University of New South Wales, Faculty of Medicine & Health, specializing in childhood diabetes research. She holds a prominent position as a Professor with extensive contributions to the field of pediatric endocrinology and diabetes, particularly focusing on type 1 diabetes in children. Professor Craig's educational background includes: MB BS from the University of Melbourne MMedSc(ClinEpid) from the University of Newcastle PhD from the University of Sydney FRACP (Fellow of the Royal Australasian College of Physicians) Professor Craig's research primarily focuses on childhood diabetes, with special emphasis on prediction and prevention of type 1 diabetes. She has a significant interest in the association between viruses and type 1 diabetes, collaborating with the Virology Research Group at Prince of Wales Hospital (POWH). Together with Professor Bill Rawlinson, she leads the viral theme for the multicentre ENDIA study (endia.org.au). As principal investigator for the CoRD trial, she is conducting a world-first phase 1 study using autologous cord blood for prevention of type 1 diabetes in children with islet autoimmunity. Additionally, she serves as principal investigator for the Australasian Diabetes Data Network (ADDN). Her research portfolio also encompasses the epidemiology of various forms of childhood diabetes (type 1, type 2, cystic fibrosis related diabetes and monogenic diabetes) and diabetes complications, in collaboration with Professor Kim Donaghue at the Children's Hospital at Westmead. Professor Craig's extensive publication record, including over 361 journal articles, demonstrates her leadership in advancing our understanding of childhood diabetes. Her recent work shows increasing focus on early detection methods, risk prediction models, technological interventions for diabetes management, and the complex interplay between viral infections and autoimmune diabetes development. She has been instrumental in developing clinical practice guidelines through her role as co-editor of the International Society for Pediatric and Adolescent Diabetes (ISPAD) guidelines. Professor Craig has received numerous prestigious awards recognizing her contributions to pediatric endocrinology and diabetes research: Australian Paediatric Endocrine Group Young Investigator's Award (1997) Asia Pacific Paediatric Endocrine Society Clinical Teaching Award (2008) Lifetime Honorary Member, Caring and Living as Neighbours (2013) Australian Diabetes Society Jeff Flack Diabetes Data Award (2019) Australian Paediatric Endocrine Group Norman Wettenhall Award for Research and Innovation (2019) Throughout her career, Professor Craig has demonstrated exceptional leadership in professional societies, having served as former president/treasurer of the Australasian Paediatric Endocrine Group (APEG) and currently as Scientific Convenor of the Asia Pacific Paediatric Endocrine Society Fellows school. Her work with the ENDIA study and Australasian Diabetes Data Network represents significant collaborative research efforts involving multiple institutions across Australia and internationally. Her principal investigator roles for major studies indicate substantial research funding support. Professor Craig leads several important research initiatives including the ENDIA study, the CoRD trial, and the Australasian Diabetes Data Network. These programs involve multidisciplinary teams of researchers, clinicians, and support staff working collaboratively to advance understanding and treatment of childhood diabetes. Her work at the intersection of virology and diabetes represents a unique and innovative approach to understanding the environmental triggers of type 1 diabetes.

• Childhood Diabetes
• Type 1 Diabetes
• Virology and Diabetes
• +۴ مورد دیگر

Associate Professor Adam Irwin is an NHMRC Emerging Leadership Fellow and Associate Professor in Infectious Diseases at the University of Queensland (UQ) and Queensland Children’s Hospital. He holds positions within the UQ Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences. His work focuses on early sepsis recognition, antimicrobial stewardship, and pediatric infectious diseases. Dr. Irwin completed his medical degree at the University of Birmingham and his PhD in 2016 from the University of Liverpool’s Institute of Infection and Global Health. He has led initiatives like the Queensland Paediatric Sepsis Program, recognized with a Global Sepsis Alliance Award and Queensland Health Excellence Awards. His research spans sepsis pathway implementation, antimicrobial resistance trends, and rapid diagnostic tools. Notable grants include NHMRC funding for studies on multi-drug resistant infections and Children’s Hospital Foundation support for genomics and antimicrobial stewardship projects. He supervises PhD candidates in areas like bloodstream infections and molecular diagnostics. Dr. Irwin collaborates across institutions, contributing to projects such as the RAPIDS Study Group and the PAEDS surveillance network. Awards include the NHMRC Emerging Leadership Fellowship and recognition for sepsis program excellence. His work emphasizes translating research into clinical practice, improving outcomes for critically ill children through evidence-based protocols and innovative diagnostics.

• Infectious Diseases
• Pediatric Medicine
• Antimicrobial Resistance
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Massimo Piccardi is a Professor of Natural Language Processing (NLP), Computer Vision, and Machine Learning at the University of Technology Sydney (UTS) , where he has been since 2002. He currently serves as the Head of the School of Electrical and Data Engineering and leads the Big Data Analytics program at the Global Big Data Technologies Centre. His research focuses on advancing NLP, machine learning applications in healthcare, and cybersecurity in IoT systems. He has authored over 200 journal papers and conference proceedings, secured significant ARC and CRC grants, and holds the IEEE Computer Society Distinguished Contributor Award (2022). Education & Professional Roles: Joined UTS in 2002, progressing from Associate Professor (2002–2007) to Professor (2008–present). Serves as Associate Editor for IEEE Transactions on Big Data and Editor for Artificial Intelligence in Medicine. Active in professional societies including IEEE, ACL, and ALTA (President, 2023–2024). Research Interests: Core areas include NLP (translation, summarization, adversarial attacks), healthcare informatics (clinical NLP, health service analysis), and cybersecurity (IoT security, privacy-preserving systems). Cross-cutting themes include generative models, cross-lingual systems, and ethical AI. Grants & Projects: Principal Investigator on ARC Discovery/Linkage projects and CRC grants. Recent projects include controllable machine translation (Amazon), privacy-preserving digital agriculture, and STEM innovation (ASTRID project with NBN Co). Labs & Collaborations: Leads the UTS Global Big Data Technologies Centre, collaborating on projects like adversarial NLP attacks, medical machine translation, and secure IoT frameworks.

• Natural Language Processing
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Marcus Smith is an Associate Professor in Law at the Charles Sturt University , where he teaches LAW222 Technology Law and directs the Bachelor of Laws program. He holds advanced degrees from the Australian National University (PhD, LLM) and the University of Cambridge (MPhil). His research spans technology law and regulation , focusing on genomic data governance biometric identification AI ethics blockchain policy cybersecurity surveillance law He leads the Contemporary Threats to Australian Security research group and serves as Chief Investigator on an NHMRC-funded project (MRF2015531) addressing genomic dataset governance. His recent work analyzes algorithmic bias in facial recognition AI in healthcare blockchain's regulatory challenges post-pandemic cybercrime surveillance ethics data security frameworks He actively supervises PhD and honours students in technology law and contributes to law reform through submissions to international bodies like the UN Human Rights Council .

• Technology Law and Regulation
• Artificial Intelligence Ethics
• Genomic Data Governance
• +۴ مورد دیگر

Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.

• Natural Language Processing
• Knowledge Graphs
• Machine Learning
• +۵ مورد دیگر

Professor Khin Than Win is a leading academic in health informatics and digital health at the University of Wollongong (UOW), holding appointments as Professor in the School of Computing and Information Technology, Head of Postgraduate Studies, and Deputy Head (Research). She also serves as Academic Program Director for UOW's Master of Health Informatics and Graduate Certificate in Health Analytics programs. Her research focuses on applying information technology to healthcare, particularly in behavior change support systems, persuasive technology, and ethical AI applications. She has supervised over 20 PhD students and holds leadership roles including Deputy Chair of UOW's Health and Medical Research Ethics Committee, and membership in international committees like the Persuasive Technology Steering Committee. Education: MBBS from Rangoon University, Master's and PhD in IT from Assumption University (Bangkok) and UOW (Australia) Research Interests: Health data analytics, AI in healthcare, privacy/security of health systems Leadership: Program/General Chair roles at ACIS and Persuasive Technology conferences Awards: Best Paper Awards (2023, 2018) Her extensive funding portfolio includes ARC grants and NHMRC projects, totaling over 24 funded initiatives. Current research explores blockchain in medical passports, AI ethics, and culturally tailored health interventions.

• Health Informatics
• Digital Health
• Persuasive Technology
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Professor Irena Koprinska is a faculty member at the School of Computer Science, University of Sydney, specializing in Machine Learning, Data Mining, and Neural Networks. Her research focuses on practical applications in education, health, and energy sectors. She has received multiple awards, including the Dean’s Award for Outstanding Teaching (2017, 2008) and Best Paper Awards at CHI 2019 and other conferences. Koprinska has supervised 11 PhD and over 60 Honours students, many of whom have won prestigious scholarships like the Google Fellowship. Education: PhD and MSc in Computer Science, MEd in Higher Education. Research Interests: Develops algorithms for pattern extraction and predictive modeling in healthcare (e.g., sleep apnea prediction), education (student behavior analysis), and energy (solar power forecasting). Her work bridges algorithmic innovation with multidisciplinary collaboration. Publications: Over 100 articles in top journals/conferences, emphasizing applications of machine learning in health, energy, and education. Recent works include deep learning for sleep apnea and ensemble methods for solar forecasting. Awards: Highlighted awards include the Dean’s Teaching Awards, Best Paper recognitions, and the Thompson Research Fellowship (2018). Advising & Grants: Currently supervises Hanxue Yao. Previously led initiatives like the Data Science for Social Good workshop at ECML PKDD. Served as Associate Head for Research Education and Sub-Dean for Teaching & Learning. Labs/Teams: Leads the Computer Human Adapted Interaction Research Group, focusing on human-centric technology solutions.

• Machine Learning
• Data Mining
• Neural Networks
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Professor Heiko Spallek is Head of School and Dean at the University of Sydney’s Sydney Dental School, leading the school’s integration with the Faculty of Medicine and Health. He also serves as Academic Lead for Digital Health and Health Service Informatics at the faculty level. His research focuses on advancing dental informatics, teledentistry, and evidence-based practice, while advocating for improved oral health policy and public health initiatives. He holds roles including director at Community Connections Australia and membership in the Charles Perkins Centre. Education: DMD, Dr. med. dent., MSBA(CIS), FACD, FAIDH Leadership: Oversees Sydney Dental School’s academic and clinical programs, emphasizing interprofessional education and digital health innovation. Research interests include leveraging big data and machine learning in dentistry, improving access to oral healthcare through teledentistry, and addressing systemic issues in dental education and policy. He has led projects on laser dentistry applications, dental caries prevention, and healthcare workforce regulation. Notable contributions include the OpenWide conference series, the BigMouth dental data repository, and advocacy for equitable dental funding in Australia. Grants include initiatives on oral hygiene in aged care and analysis of healthcare advertising perceptions. Media engagements highlight his role in public discourse on dental access and policy, including commentary on Australia’s dental crisis and aged care reforms. He actively promotes interdisciplinary collaboration through platforms like the Dental Informatics Online Community. Labs/Teams: Directs the Sydney Dental School’s research programs in informatics and public health, collaborating with national and international networks such as the National Dental PBRN.

• Dental Informatics
• Teledentistry
• Oral Health Policy
• +۴ مورد دیگر

Dr. Jannah Baker is a Research Fellow at the Sydney School of Public Health, University of Sydney. She holds a PhD in Statistics specializing in Bayesian spatiotemporal modelling of chronic diseases, alongside dual postgraduate diplomas in Public Health and Statistics. Her clinical background includes five years as a practicing physician. Her research focuses on cancer prevention (breast, endometrial, melanoma), spatiotemporal disease modeling, health economics, and clinical trial design. She has led projects on sepsis detection systems, diabetes management, and surgical outcomes analysis. Notable contributions include a seminal systematic review on fertility-sparing endometrial cancer treatments referenced in international guidelines. Jannah has attracted $6M+ in collaborative funding and oversees grants such as the 2023 NHMRC-funded ROADMAP trial and a Department of Health-funded study on pediatric sepsis management. Her work spans 50+ peer-reviewed articles across journals like Journal of Medical Internet Research and PLOS One . Professional activities include clinical trials statistics, health economics analysis, and implementation science lectures. She has mentored multiple research teams and maintains an ORCID profile (0000-0002-2208-6584).

• Breast Cancer Prevention
• Spatiotemporal Disease Modelling
• Health Economics
• +۳ مورد دیگر

Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.

• Machine Learning
• Computer Vision
• Medical Image Analysis
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Rajendra Acharya is a Professor (Artificial Intelligence in Health) at the University of Southern Queensland's School of Mathematics, Physics and Computing. He holds qualifications including BEng, MTech, two PhDs, and a DSc. His research focuses on AI applications in healthcare, pattern recognition, and medical diagnostics, with notable contributions to EEG analysis, deep learning, and disease detection. Awards include multiple Research.com Leader Awards in Computer Science for Australia and Singapore (2022–2025). His work spans over 650 publications, with high-impact studies on automated disease diagnosis via AI, including COVID-19 detection using X-rays and EEG-based seizure detection. His research interests integrate machine learning, signal processing, and healthcare technologies. He collaborates internationally and advises on AI-driven health solutions. No student list provided; however, his extensive supervision is implied through his research output.

• Artificial Intelligence
• Healthcare
• Machine Learning
• +۵ مورد دیگر

Dr. Thilina Halloluwa is a Teaching Focused Lecturer in the Department of Human-Centred Computing at The University of Queensland (UQ). He holds a PhD in Human-Computer Interaction from Queensland University of Technology (2019) and a Computer Science undergraduate degree from the Sri Lanka Institute of Information Technology. With over 15 years of academic and industry experience, his research emphasizes real-world impact in education technology, financial inclusion, smart agriculture, and HCI. Educational Background: PhD in Human-Computer Interaction, Queensland University of Technology (2019) Bachelor of Computer Science, Sri Lanka Institute of Information Technology Research Interests: Education for All: Leveraging technology to enhance collaborative learning and social experiences in education. Human Money Interaction: Designing ethical AI solutions for financial services, particularly for underserved communities. Smart Agro: Developing AI-driven tools for crop disease detection, yield optimization, and precision agriculture. Software Project Estimation: Improving effort estimation accuracy through explainable AI (Metrix project). Key Contributions: Developed UrbanAgro (tomato disease detection) and BellCrop (bell pepper disease datasets). Pioneered Dhana Labha , a financial management tool for rural Sri Lankan communities. Advanced online exam proctoring systems for low-resource settings. Previous Roles: Lecturer at University of Sydney (2023) Senior Lecturer at University of Colombo (2013–2023) Lab/Team Affiliations: Smart Agro Project: AI-driven agricultural solutions Metrix Initiative: Software project estimation frameworks

• Human-Computer Interaction
• Educational Technology
• Artificial Intelligence
• +۴ مورد دیگر

Prof Raphaël Phan is a Professor and Deputy Head of the School of IT at Monash University Malaysia. His expertise spans security, cryptography, malicious AI, emotion recognition, motion analysis, and generative AI. He has published over 220 papers and led significant projects including privacy-preserving data mining funded by UK MoD and Malaysian government grants exceeding RM4 million. He co-designed the BLAKE hash function (SHA-3 finalist) and has an h-index of 50. Education: PhD in Cryptography (Multimedia University, 2005), MEngSci (2001), BEng (Hons) Computer Engineering (1999). Research focuses on adversarial AI, brain networks, and secure systems. Current projects include Æmbience: emotion-aware virtual assistants using motion magnification. Supervised 15 PhD graduates and 19 current students. Professional affiliations: Chartered Engineer (IET, UK), HEA Fellow, Board of Engineers Malaysia. Recent work emphasizes causal bias detection in micro-expressions, brain tumor detection via advanced YOLOv8, and generative adversarial networks for medical imaging. His work bridges cybersecurity with neuroscience applications.

• Security
• Cryptography
• Malicious AI
• +۵ مورد دیگر

Associate Professor Dan Dongseong Kim is Deputy Director of UQ Cybersecurity and an Associate Professor at The University of Queensland (UQ), Australia. Previously, he held permanent academic positions at The University of Canterbury (UC), New Zealand (2011-2018) as a Senior Lecturer and Lecturer. His research focuses on Cybersecurity and Dependability for AI, IoT, Autonomous Vehicles, Cloud Computing, and Moving Target Defenses (MTD). Doctor of Philosophy in Computer Engineering from Korea Aerospace University Postdoctoral Research at Duke University (2008-2011) Visiting Scholar at University of Maryland (2007) Dan's work explores Graphical Security Models , Moving Target Defense for proactive resilience, and AI-Driven Cybersecurity with emphasis on adversarial robustness and interpretable models. His recent publications (2024-2025) span journals like IEEE Transactions on Dependable and Secure Computing and conferences such as DSN , addressing automated defense, evolving attacks, and hardware-aware security frameworks. He has advised 15 Ph.D. graduates, including researchers now at institutions like RMIT University, La Trobe University, and CSIRO's Data61. Current supervision includes projects on Automated Penetration Testing , AI-Based Intrusion Response , and Moving Target Defense . Dan's research is funded by agencies including the Republic of Korea's Agency for Defence Development and US Army Research Lab . His professional roles include Associate Editor for IEEE Communications Surveys and Tutorials and Steering Committee Chair for IEEE PRDC .

• Cybersecurity
• Cybersecurity Modeling and Analysis
• Moving Target Defense
• +۷ مورد دیگر

Professor George Buchanan is a leading researcher in human-computer interaction and digital libraries at RMIT University . His work bridges information science, digital humanities, and health informatics, focusing on usability in sensitive contexts like healthcare and misinformation. Deputy Dean, Research at RMIT University Former Director, University of Melbourne iSchool Research Interests: Digital information interaction Health and aging informatics Disinformation analysis Mobile interface design Digital library systems Key Contributions: Developed mobile web usability benchmarks, spatial hypertext tools, and thermal feedback interfaces. Currently seeking PhD students for 2025 projects on digital browsing and view change dynamics. Awards: Over twenty best paper awards and Honorary Life Fellow of the Royal Society of Arts. Advising: Accepting Masters/PhD supervision in information interaction and digital health domains.

• Human-Computer Interaction
• Digital Libraries
• Information Retrieval
• +۵ مورد دیگر