جست‌وجوی استاد و پژوهشگر

Xiaoyang Wangمشاهده پروفایل

مدرس ارشد

• Graph Processing
• Graph Neural Networks
• Spatial Data Processing
• +۱۰ مورد دیگر

Xiaoyang Wang is a Senior Lecturer in the School of Computer Science and Engineering (CSE) at the University of New South Wales (UNSW). He holds a Bachelor's and Master's degree in Computer Science from Northeastern University, China, and earned his PhD from CSE UNSW. Dr. Wang's research focuses on database systems with a special emphasis on query processing and data mining on large-scale graph, spatial, and streaming data. His expertise extends to data-driven machine learning, smart contract analysis on blockchain, and FinTech with financial network analysis. His work spans Graph Processing, Graph Neural Networks, Spatial Data Processing, AI for Databases (AI4DB), Database for AI (DB4AI), and FinTech applications. His publication record shows significant contributions to the field with 7 book chapters, 56 journal articles, 61 conference papers, 7 edited conference proceedings, and 4 conference abstracts. Recent publications (2022-2025) demonstrate his strong research trajectory in advanced graph processing techniques, neural network applications, and innovative database approaches. Key themes include hierarchical contrastive learning, robust attack frameworks, temporal graph processing, influence maximization, knowledge graph-enhanced reasoning, and rumor mitigation. Dr. Wang actively recruits PhD students interested in pursuing research in related fields and encourages current undergraduate and master's students at UNSW to contact him about research opportunities. He maintains an active research agenda with practical implications for industries dealing with large-scale network data, financial technology applications, and data-intensive systems. He can be reached at xiaoyang.wang1@unsw.edu.au and is located in Engineering building K17-501D at UNSW.

• LLM-assisted agent systems
• Explainable AI
• Multimodal artificial intelligence
• +۱۲ مورد دیگر

Dr. Yifei Dong is a Research Fellow at the Data Science Institute , University of Technology Sydney, with expertise in LLM-assisted agent systems , explainable AI , and multimodal artificial intelligence . Holding a PhD in Computer Science from UNSW Sydney and over a decade of fintech industry experience including CTO roles, he has secured $2.4 million in competitive funding for AI solutions bridging academia and real-world applications in healthcare, education, and finance. Education : PhD in Computer Science from UNSW Sydney Current Role : Research Fellow at UTS Data Science Institute (2023–present) Past Academic Appointments : Lecturer at Southern Cross University and Western Sydney University Dr. Dong’s research focuses on making AI systems transparent and socially beneficial , with contributions to adversarial AI, trustworthy digital societies, and wireless sensor networks. His recent work includes: Developing AICAttack (2025) for adversarial image captioning attacks Creating the QMAD fairness metric (2025) for dynamic environments Advancing explainable ECG diagnosis systems (2025) via multimodal LLMs As a scientific awardee (2025 RegTech Social Impact of the Year), he has pioneered AI solutions for vulnerable populations, such as NDSI participants through the "My Complaint Assistant" tool. His supervision of PhD and Honours students emphasizes technical rigor and ethical responsibility.

Arif Perdanaمشاهده پروفایل

دانشیار

• Data Science and Analytics
• Digital Strategy
• Responsible AI
• +۴ مورد دیگر

Arif Perdana is an Associate Professor specializing in digital strategy and data science at Monash University. He holds a PhD in Business Information Systems from the University of Queensland (2016) and serves as Director of the Action Lab Indonesia since December 2022. His research focuses on responsible AI, blockchain, machine learning, and digital strategy applications in finance, healthcare, and education sectors. He has secured significant funding from entities like Bank Indonesia and Monash Data Future Institute. Research Interests: - Blockchain for supply chain sustainability - Ethical AI governance - FinTech and RegTech innovations - Digital transformation strategies - Data governance frameworks Awards: - Lybrand Award 2022-2023 Key Projects: - ASEAN Disinformation Index (2024-2025) - Algorithmic Systems Governance in Finance (2023-2024) - Inclusive P2P Lending Models (2023) - Digital Health Governance in Indonesia (2022-2023) Media Contributions: - Over 50 media features discussing AI ethics, cybersecurity, and tech governance - Featured in international outlets like RMIT Vietnam and Swinburne University

Flora Salimمشاهده پروفایل

استاد

• Ubiquitous computing
• Machine learning
• Data science
• +۶ مورد دیگر

Professor Flora Salim is a leading academic at the University of New South Wales (UNSW) Sydney, holding a full Professorship in the School of Computer Science and Engineering. She serves as Deputy Director (Engagement) of the UNSW AI Institute and contributes to multidisciplinary research at the intersection of ubiquitous computing, machine learning, and data science. Human-centred AI and ethical systems Spatio-temporal data modeling Applications for climate resilience and urban mobility Her research focuses on multimodal foundation models, continual learning, and responsible AI deployment in real-world environments. She explores: Time-series and sensor data analysis Wearable and environmental sensing AI for sustainable infrastructure Robustness and trustworthiness in models Recent publications highlight her work on: Transformer-based climate downscaling Cross-modal fairness in mobility Privacy-preserving spatio-temporal generation Patient similarity networks in healthcare She has received multiple competitive fellowships including: Humboldt Fellowship Bayer Fellowship Victoria Fellowship ARC Australian Postdoctoral Industry (APDI) Fellowship Additional accolades include: Women in AI Award Australia and New Zealand (2022) IBM Smarter Planet Industry Innovation Award As Chief Investigator in: ARC Centre of Excellence for Automated Decision Making and Society (ADM+S) ARC Training Centre for Whole Life Design for Carbon Neutral Infrastructure She maintains active collaborations through: Associate position at ELLIS Alicante Visiting Professor roles at University of Kassel (2019-2020) and University of Cambridge (2019) Editorial board memberships in ACM TIST, IEEE Pervasive Computing, and Nature Scientific Data

Rand Lowمشاهده پروفایل

دانشیار

• Quantitative Finance
• Portfolio Optimization
• Risk Management
• +۹ مورد دیگر

Dr Rand Low is an Associate Professor of Quantitative Finance at Bond Business School , with an Honorary Associate Professor role at the University of Queensland. He works at the Centre for Data Analytics and holds a Chartered Professional Engineer designation from Engineers Australia. PhD in Finance, University of Queensland (2009-2013) Bachelor's degrees in Engineering and Computer Science, University of Melbourne (2001-2005) Graduate Diploma in Project Management, University of New England His research focuses on portfolio optimization , risk management , and machine learning applications in finance, particularly for corporate bonds , digital assets , and commodities . He has published in top journals including Journal of Banking & Finance and Energy Economics . Dr Low's work has been recognized through awards like the Australia Awards - Endeavour fellowship and Dean's Award for Research Higher Degree Excellence . He actively supervises HDR students and serves on editorial boards for journals with Q1 rankings. Industry experience includes leadership roles at Bank of America Merrill Lynch and BlackRock in New York, where he developed quantitative models for market risk , structured products , and model governance . He currently works on the RBA's CBDC Pilot for blockchain-based corporate bond settlement.

Adrian Geppمشاهده پروفایل

استاد

• Business Failure Prediction
• Fraud Detection
• Big Data
• +۳ مورد دیگر

Adrian Gepp is a Professor at the Bond Business School and a member of the Centre for Data Analytics at Bond University in Australia. His research focuses on applying statistical modeling and data analytics to economic and social challenges, including fraud detection, fintech, health analytics, and business failure prediction. Gepp has published extensively in peer-reviewed journals and conferences, with recent work spanning deep learning in portfolio management, ESG investing, and combating financial crime through AI. Research Interests : Big data, predictive modeling, financial statement fraud, car insurance fraud, quantum algorithms, and cross-border economic models. Professional Affiliations : The Actuaries Institute, American Accounting Association, and Association of Certified Fraud Examiners. Article Trends : His 2025 publications emphasize machine learning applications in finance, fraud analytics, and interdisciplinary data-driven solutions. Earlier works (2024) explore tourism forecasting and research methodology frameworks. Media & Activities : Regularly featured in media discussions on fraud detection, big data, and financial technology. Serves on editorial boards for journals like Accounting and Finance and Journal of Accounting Literature .

Mahbuba Afrinمشاهده پروفایل

مدرس

• Machine Learning
• Edge Intelligence
• Networked Robotics
• +۲ مورد دیگر

Dr. Mahbuba Afrin is a Lecturer at Curtin University's School of Elec Eng, Comp and Math Sci (EECMS), with affiliations to the Faculty of Science and Engineering. She holds a Ph.D. from Swinburne University of Technology, an M.S. and B.S. in Computer Science and Engineering from University of Dhaka. Her research specializes in Internet of Things-enabled Cyber-Physical Systems, Networked Robotics, and development of efficient learning models for intelligent systems. Research focuses include resource allocation optimization, autonomous network management, and edge intelligence applications in agricultural technology, fraud detection, and livestock management. Current projects explore UAV-based solutions for bushfire detection and real-time robotic task allocation using deep reinforcement learning. Afrin has secured multiple grants including the Strong and Resilient Communities Grant (AUD $360,000), Innovation Challenge for Generative AI (AUD $50,000), and three Pawsey Supercomputing grants. Her 15 most recent publications (2018-2025) demonstrate consistent focus on machine learning applications in networked systems, spanning UAV coordination, blockchain security, cloud robotics, and agricultural technology. Awards include the 2024 WiTWA Tech Rising Star Award in STEM Academia, People's Choice Award at Pawsey Supercomputing Project Showcase (2022-23), and Vice-Chancellor's Postdoctoral Fellowship (2021). She teaches courses including Data Structures and Algorithms, Fundamentals of Programming, and Computer Science projects.

• FinTech
• Cyber Security
• Data Science
• +۴ مورد دیگر

Dr. KC Chan is a Senior Lecturer at the University of Southern Queensland (USQ) in the School of Business, specializing in Information Systems. He holds academic affiliations as an Honorary Senior Research Fellow at La Trobe University and a Visiting Fellow at the University of New South Wales (UNSW). With over 30 years of professional experience, his career spans academia, industry, and research. He has published over 100 refereed papers focusing on FinTech, Cyber Security, AI/ML applications, and data science. Dr. Chan's educational background includes a BASc and MASc from the University of Toronto and a PhD in Manufacturing Engineering from UNSW. His research interests emphasize the intersection of technology and business, particularly in financial systems security, blockchain applications, and data-driven decision-making. He has supervised numerous doctoral and master's students, including projects on quantum computing risk management, intrusion detection in web systems, and cognitive approaches to cryptocurrency frameworks. Dr. Chan's work bridges academia and industry, with notable contributions to smart building AI integration, manufacturing big data ecosystems, and healthcare informatics. His recent publications (2023-2025) address cryptocurrency trading analysis, mental health monitoring systems, and sustainable corporate strategies. He actively contributes to teaching advanced cybersecurity topics like CIS8500 and CIS8711.

Cynthia Caiمشاهده پروفایل

مدرس ارشد

• FinTech (Machine Learning Algorithms/Blockchain)
• Information Economics
• Financial Innovations
• +۵ مورد دیگر

Cynthia Cai is a Senior Lecturer in the Department of Applied Finance at Macquarie University, where she specializes in FinTech, blockchain, and financial innovations. With over 15 years of academic and professional experience across Australia and internationally, she holds a PhD in Accounting/Finance from The University of Melbourne and is a CPA Australia member. Her research focuses on cutting-edge topics such as blockchain, machine learning algorithms, and sustainable investment. Notably, her work on FinTech has earned prestigious awards, including the Peter Brown Manuscript Award (2018) and the Ray Ball Prize Runner-Up (2019). She is a sought-after reviewer and editorial board member for top-tier journals. In teaching, Dr. Cai designs and delivers core FinTech courses for Macquarie’s pioneering master’s program, including 'FinTech and Innovations' and 'Payment, Cryptocurrencies and Blockchain'. She actively supervises PhD students in areas like central bank digital currencies (CBDC) through the CSIRO Next Gen R&D Program. Her projects include research on CBDC infrastructure, sustainable investment literacy, and cryptocurrency-EUA market interactions. She has contributed expert commentary on financial trends for media outlets and collaborates with institutions like the DFCRC and ANZ.