جستجوی استاد راهنمای دانشگاهی

• Customer Analytics
• Social Media Analytics
• Churn Management
• +۳ مورد دیگر

Ali Tamaddoni Jahromi is an Associate Professor in the Department of Marketing at Deakin Business School, part of Deakin University's Faculty of Business and Law. He holds a PhD from Monash University and a Graduate Certificate in Higher Education from Deakin University. His research focuses on customer analytics, social media analytics, churn management, and user-generated content (UGC), with publications in high-impact journals like the Journal of Marketing Research and Journal of Service Research . Dr. Tamaddoni has secured grants totaling over $38k, including a 2023 grant on AI alignment strategies and a 2022 project on churn management for Legal Super. He actively supervises doctoral and master's students on topics like consumer fake review perception, AI in e-commerce, and marketing budget allocation. His awards include the ANZMAC 2018 Best Reviewer Award and a 2008 Best Paper Award in Business-to-Business Marketing. He teaches advanced courses such as Marketing Analytics (MIS784, MIS384), Descriptive Analytics, and Business Analytics Project units. His research spans predictive modeling, customer retention strategies, and the impact of digital platforms on consumer behavior.

• Marketing Technology
• Customer Lifetime Value Modelling
• Market Response Modelling
• +۶ مورد دیگر

Andre Bonfrer is a Professor of Marketing at Deakin Business School, part of Deakin University's Faculty of Business and Law. He specializes in quantitative marketing, with expertise in marketing technology, customer lifetime value modeling, and market response analysis. Bonfrer holds a PhD from the University of Chicago Booth School of Business and has taught at institutions including the University of Melbourne and Singapore Management University. His research focuses on fast-moving consumer goods, digital marketing solutions, and adaptive market response models. Education: PhD in Business, University of Chicago (200?) MBA, University of Chicago (200?) Master of Commerce, University of Auckland Bachelor of Commerce, University of Auckland Research Interests: Marketing Technology and Analytics Customer Lifetime Value Modelling Digital Marketing Strategies Retail Competition Dynamics Brand Equity and Consumer Behavior His work bridges theoretical and applied research, addressing challenges in consumer decision-making, brand management, and policy impact (e.g., cigarette plain packaging regulations). Grants & Awards: $20,000 Conjointly AI Alignment Research Grant (2023) $18,181 Legal Super Pty Ltd Churn Management Contract (2022) ANZMAC Distinguished Researcher (2012), Best Paper Awards (2015) Multiple teaching and research fellowships (e.g., Lee Kuan Yew, Lee Foundation) Professional Contributions: Chair, ABDC Marketing Learning Standards Working Party (2011–2012) Member of AMA, ANZMAC, EMA, and INFORMS Supervision of 4 active PhD students and 1 completed student His research has been published in top journals like Marketing Science , Journal of Marketing Research , and Management Science , emphasizing data-driven insights for business decision-making.

Steve Cassidyمشاهده پروفایل

دانشیار

• Research Data Management
• Linguistic Annotation Standards
• Speech Analysis Technology
• +۳ مورد دیگر

Steve Cassidy is an Associate Professor in the School of Computing at Macquarie University. His research focuses on research data discovery, reproducibility, and accessible tools for language sciences. He specializes in linguistic annotation standards, speech analysis technologies, and interoperability infrastructure for human communication science. He holds a PhD in Computer Science from Victoria University of Wellington, an MSc in Knowledge-Based Systems from the University of Edinburgh, and a BSc in Physics with Astrophysics from the University of Leicester. He leads major projects such as FAIMS3 (Field Acquired Information Management Systems) and the Alveo Virtual Laboratory, which support digital data capture and management in diverse research contexts. His work emphasizes FAIR data principles and interdisciplinary collaboration, with applications in linguistics, archaeology, and speech technology. He has contributed to initiatives like the AusTalk corpus and Signbank, advancing open science practices and accessibility in research. Recent research highlights include machine learning models for military performance prediction and temporally rich deep learning approaches for magnetoencephalography analysis. His work has been recognized through awards including the 2024 Teaching Excellence Highly Commendation and the 2023 Inter-School Collaboration Award. Education: PhD in Computer Science (Victoria University of Wellington, 1993) MSc in Knowledge-Based Systems (University of Edinburgh, 1984) BSc in Physics with Astrophysics (University of Leicester, 1983) Postgraduate Certificate in Higher Education (Macquarie University, 2008) Key Projects: FAIMS3: Mobile field data collection platform Alveo Virtual Lab: Linguistic data repository AusTalk Corpus: Large-scale Australian English speech database His publications span machine learning applications, speech technology, and open research infrastructure. He actively collaborates across disciplines to develop tools that enhance reproducibility and accessibility in scientific research.

Muhammad Ikramمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Privacy-Preserving Systems
• Machine Learning for Security
• +۵ مورد دیگر

Dr. Muhammad Ikram is a Senior Lecturer in Cybersecurity at Macquarie University's School of Computing, affiliated with the Information Security and Privacy (ISP) group and the Macquarie Cybersecurity Hub (MCHUB). His research focuses on privacy/security in mobile/Web platforms, leveraging machine learning for fraud detection and vulnerability analysis. He holds a PhD in Electrical Engineering from UNSW, a Master's from Ajou University, and a Bachelor's from UET Peshawar. Ikram has published 64+ works in top conferences/journals like Usenix Security, NDSS, and ACM TOPS. His notable contributions include analyzing iOS app vulnerabilities, tracking prevention mechanisms, and mobile health app privacy risks. He received the Best Paper Award at AsiaCCS 2019 and Outstanding Paper at Mobiquitous 2021. Research Interests: Mobile/Web Security, Malware Detection, Privacy-Preserving Systems Grants: Led projects on network security, telecommunications obligations, and cybersecurity hubs Media Impact: Featured in The Guardian and over 50 outlets for work on web resource loading (~11M audience reach) Service Roles: Technical Program Committee member at WWW/PETS, reviewer for CCS/PETS He previously held roles as a Postdoc at University of Michigan and Research Scientist at Data61. His work bridges academic research with real-world impact in cybersecurity policy and industry standards.

Yan Liمشاهده پروفایل

مدرس

• IoT
• Mobile Computing
• Wireless Sensor Networks
• +۷ مورد دیگر

Dr. Yan Li is a Lecturer in IoT and Networking at the School of Computing, Macquarie University. She holds a PhD in Electrical and Electronic Engineering from the University of Melbourne and a Master of Research in Electronic Engineering from the University of Technology Sydney. Previously, she was a Research Fellow at the Telstra-UoW AIoT Hub. Her research focuses on IoT, inertial navigation, mobile computing, wireless sensor networks, and machine learning applications in sensor data analytics. She has been recognized with the Michael Richey Medal and a DIN Pilot Project Grant, and contributed to initiatives like the Future Communications Research Centre and Smart Green Cities Research Centre. Education: Bachelor of Engineering in Aerospace Engineering, Northwestern Polytechnical University PhD in Electrical and Electronic Engineering, University of Melbourne Master by Research in Electronic Engineering, University of Technology Sydney Research interests include: IoT and networking infrastructure Indoor localization and tracking systems Wearable sensor technologies Machine learning for sensor data analytics Healthcare mobility monitoring Smart home situational awareness Notable awards and grants include the Michael Richey Medal (2023), DIN Pilot Project Grant (2022-2023), and the 2023 Faculty of Science and Engineering Award for Inter-School Collaboration. Her work spans over 300 citations and 25 research outputs, emphasizing practical applications in telecommunications and smart environments. Advising and grants: Supervises PhD/Master students in IoT, localization, and machine learning. Active in collaborative projects like the Future Communications Research Centre, focusing on IoT and smart infrastructure solutions. Labs/Teams: Affiliated with Macquarie's Future Communications Research Centre and Smart Green Cities Research Centre, advancing IoT and sustainable urban technologies.

Rajan Shankaranمشاهده پروفایل

مدرس ارشد

• Network Security
• Mobile Communication Protocols
• Internet of Things
• +۴ مورد دیگر

Rajan Shankaran is a Senior Lecturer at Macquarie University's School of Computing, part of the Faculty of Science and Engineering. He serves as Course Director for postgraduate programs in Networking and IoT, and chairs the IEEE VTS NSW Chapter. His roles include membership in the University Academic Senate Curriculum Subcommittee and representation on the FSE Faculty Board. Education: MBA (MIS) from Maastricht School of Management; M.Sc. (Hons.) and Ph.D. in Network Communications and Security from University of Western Sydney. Research focuses on Network Security, Mobile Communication Protocols, IoT, Network-on-Chip, and Medical Implant Security. He has led projects like 'Digital Health Records Storage and Analysis for Global Patients' and organized IEEE events such as NOMS 2017. Notable awards include IEEE Senior Member status. Recent work includes publications on wireless network security, optimization algorithms, and IoT-enabled healthcare systems. He advises on over 70 research outputs and has contributed to 4 major projects addressing cybersecurity and network efficiency. Labs/Teams: Active in the Future Communications Research Centre, collaborating on 5G/IoT security and edge computing applications.

Michael Shengمشاهده پروفایل

استاد

• Web of Things
• Internet of Things (IoT)
• Big Data Analytics
• +۵ مورد دیگر

Dr. Michael Sheng is a Distinguished Professor and Head of the School of Computing at Macquarie University. He previously served at the University of Adelaide's School of Computer Science for a decade in senior roles such as Interim Head of School and Deputy Head. His academic journey includes a PhD from the University of New South Wales (UNSW), a postdoc at CSIRO ICT Centre, and a visiting research fellowship at UNSW. With industry experience as a senior software engineer for six years, he bridges academia and practice. His research focuses on Web of Things, IoT, Big Data Analytics, and Service-oriented Computing. Recognized for his impact, he holds awards like the AMiner Most Influential Scholar Award on IoT (2019) and ARC Future Fellowship (2014). He leads initiatives in Smart Green Cities and is active in IEEE and ACS advisory roles. Recent projects include Revolutionizing Dynamic Pricing and Management Optimization through Synergizing Generative AI, Predictive Analytics, and Game Theory (2024–2028) and Central Bank Digital Currency – Infrastructure & Applications (2023–2028). He supervises students in cutting-edge areas like fraud detection and federated learning, as evidenced by awards like the 2021 IEEE ICDM Best Paper Award. Sheng's affiliations span multiple research centers at Macquarie, including the Frontier AI Research Centre and Smart Green Cities Research Centre, reflecting his interdisciplinary contributions.

Dinusha Vatsalanمشاهده پروفایل

مدرس ارشد

• Privacy-Preserving Technologies
• Record Linkage
• Data Mining
• +۴ مورد دیگر

Dr. Dinusha Vatsalan is a Senior Lecturer in Cyber Security at the School of Computing, Macquarie University. She joined in May 2022 and holds a PhD in Computer Science from Australian National University and a BSc (Hons) in Information and Communication Technology from the University of Colombo School of Computing, Sri Lanka. Previously, she was a Research Scientist at Data61, CSIRO. Her research focuses on privacy-preserving technologies, including record linkage, data mining, machine learning, and privacy risk quantification. She has authored over 60 scientific articles and received notable awards such as the Australian government’s Endeavour Postgraduate Research Award, Ruby Payne-Scott Award (CSIRO), and the Manthan Award South Asia (2009). Her work spans privacy-preserving data sharing, adversarial machine learning defenses, and secure data integration across domains like healthcare and mining. Recent publications highlight contributions to trusted data sharing in mineral exploration, privacy-preserving deep learning models, and adversarial training defenses. She is affiliated with the Future Communications Research Centre and actively collaborates internationally on cyber security and privacy initiatives.

• Intelligent Mechatronics
• Robotics
• Agricultural Automation
• +۵ مورد دیگر

Associate Professor Tien-Fu Lu is a faculty member in the School of Electrical and Mechanical Engineering at the University of Adelaide, affiliated with the Faculty of Sciences, Engineering and Technology. He holds a Reader position and specializes in intelligent mechatronics, robotics, and automation systems. His work spans nano-positioning technologies, industrial robotics, agricultural automation, and mining engineering. Research Interests: - Robotics and mechatronics in agriculture (vineyard pruning, stockpile management) - Underwater robotics and autonomous systems - Energy harvesting using piezoelectric materials - Human-machine interaction through exoskeletons - Precision motion control and sensor systems Recent work focuses on automated pest detection in agriculture, real-time stockpile modeling for mining, and advanced robotic systems for industrial applications. He has secured over $12M in research funding, including major grants from CSIRO, GRDC, and SmartSat CRC. Awards: Web of Science High-Citation Paper (2018) ASPEN2015 Conference Best Paper Award StateWeb Excellence Award (2007) Grants and Supervision: He leads teams in multidisciplinary projects, supervising Masters/PhD candidates in robotics and mechatronics. Active collaborations involve industry partners like CSIRO, GRDC, and Wine Australia. Labs/Teams: - Robotics and Automation Lab - Agricultural Mechatronics Group - Mining Automation Research Cluster

• Labour Economics
• Health Economics
• Education Economics
• +۵ مورد دیگر

Dr. Zhang Wei is a Grant-Funded Researcher (C) at the University of Adelaide's School of Economics and Public Policy, affiliated with the Future of Employment and Skills Research Centre. He holds a PhD in economics and has held roles including Associate Lecturer at the University of Adelaide and Senior Research Fellow at Flinders University's National Institute of Labour Studies. His research focuses on labour economics, health economics, education economics, international trade, and applied game theory. Current projects include evaluations of the National Disability Insurance Scheme, impacts of ageing populations on productivity, job mismatches, and education's role in labour markets. Education: PhD in economics (thesis on multilateral vs. bilateral trade liberalisation) Research interests span policy-relevant areas such as workforce dynamics, healthcare economics, and trade agreements. He has contributed to projects funded by ARC/NHMRC, NCVER, and government departments, addressing topics like retirement policy, VET completers' job mobility, and economic security. Supervision eligibility includes co-supervision for Masters/PhD candidates.

Xuyun Zhangمشاهده پروفایل

دانشیار

• Scalable Machine Learning
• Big Data Privacy
• Cyber Security
• +۵ مورد دیگر

Dr. Xuyun Zhang is an Associate Professor at the School of Computing, Macquarie University, Australia. He holds a PhD from University of Technology Sydney (2014), and Master's/Bachelor's degrees from Nanjing University (China). His research focuses on scalable machine learning, big data privacy, cyber security, edge computing, and IoT. He has led 11 research projects including Next-Gen Banking (2024-2028) and Scalable Document Intelligence (2022-2027). His work spans secure AI, privacy-preserving techniques, and edge-cloud collaboration. He has received awards such as the Chancellor's Best PhD Thesis (2015) and Early-Career Research Excellence (2019). His recent publications address areas like metaverse service offloading, hypergraph trust prediction, and federated learning frameworks. He actively organizes conferences like the Australasian Information Security Conference (2017) and chairs industry-research initiatives in cloud computing and mobile networking. Education: PhD (UTS, 2014), MEng (Nanjing University, 2011), BSc (Nanjing University, 2008). Teaching includes Machine Learning in Cybersecurity, Data Science, and Software Engineering. Key research contributions include privacy-preserving publishing, edge computing offloading methods, and blockchain-based secure access management. His projects often integrate AI with cloud-edge systems to address real-world challenges in finance, healthcare, and smart manufacturing.

Quan Z. Shengمشاهده پروفایل

استاد

• Internet of Things
• Big Data Analytics
• Machine Learning
• +۳ مورد دیگر

Quan Z. Sheng is a Distinguished Professor and Head of the School of Computing at Macquarie University, Australia. Previously, he held senior leadership roles at the University of Adelaide. He earned his PhD from the University of New South Wales (UNSW) and has extensive industry experience as a senior software engineer. His research focuses on Internet of Things (IoT), Big Data Analytics, Machine Learning, and Web Science, with significant contributions to services computing and trust management. Sheng has received notable awards, including the AMiner Most Influential Scholar Award (2018) and ARC Future Fellowship (2014). His research interests span IoT service ecosystems, graph-based machine learning, and federated learning. Recent achievements include advancements in graph-level learning and fraud detection systems. Sheng leads major grants like the ARC Research Hub in IoT for Water and collaborates with industry through CRC partnerships. His team has produced over 500 publications, with impactful work featured in Communications of the ACM and top conferences like IEEE ICDM. Sheng advises a diverse group of PhD students and oversees research centers including the Data Horizons and Smart Green Cities. Awards: AMiner Most Influential Scholar Award on IoT (2018) ARC Future Fellowship (2014) Chris Wallace Award for Outstanding Research (2012) Best Paper Awards at IEEE ICDM 2021 and PDCAT 2019 Grants & Collaborations: Leads ARC Industrial Transformation Hubs ($10M+), Digital Finance CRC, and Smart Cities projects. Active in IEEE Technical Communities and ACS IoT Advisory Board. Teams & Labs: Directs research groups in AI, IoT, and data science. Collaborates globally through visiting scholars and industry partnerships.

Georgy Sofronovمشاهده پروفایل

دانشیار

• Statistical Analysis
• Operations Research
• Change-Point Detection
• +۶ مورد دیگر

Georgy Sofronov is an Associate Professor in Statistics and Director of Research Training at Macquarie University's School of Mathematical and Physical Sciences. He holds a PhD in Probability Theory and Mathematical Statistics from Moscow State University (2002). Previously, he held academic positions at the University of Queensland and the University of Wollongong. He serves on editorial boards for Statistical Papers and Methodology and Computing in Applied Probability , and is Treasurer of the Modelling and Simulation Society of Australia and New Zealand. His research focuses on change-point detection, statistical quality control, optimal decision rules, and computational statistics. Research Interests : Change-point problem, statistical quality control Optimal decision rules, operations research Markov chain Monte Carlo methods, Cross-Entropy method Statistical modelling and data analysis Statistical Software (R-package 'breakpoint') Affiliations : Biomolecular Discovery Research Centre Centre for Risk Analytics Data Horizons Research Centre Smart Green Cities Research Centre Transforming Energy Markets Research Centre Teaching : Courses include Statistical Theory , Probability , Market Research and Forecasting , and Statistical Inference . Grants & Projects : SmartCrete CRC (2020–2027) Multiple change-point detection methods for big data (2017–present) Awards : Learning and Teaching Award (2016) Award for Excellence in HDR Supervision (2021) Collaborations : Active in Australia, New Zealand, and international networks focusing on computational statistics and risk analytics.

• Electrical and Electronic Engineering
• Applied Mathematics
• Physical Sciences
• +۳ مورد دیگر

Ali Moradi Amani is a Senior Lecturer at the RMIT University School of Engineering , specializing in Electrical & Electronic Engineering. Based at the City Campus in Australia, his research focuses on clean energy systems, machine learning applications in power networks, and smart grid technologies . Affiliation: RMIT University, School of Engineering Academic Rank: Senior Lecturer Email: ali.moradiamani@rmit.edu.au His recent publications (2020-2025) demonstrate expertise in: AI-driven energy sustainability solutions Electric vehicle charging infrastructure optimization Community battery storage systems Multi-energy system demand response Dynamic grid operating envelopes Solar system demand management He actively supervises Masters and PhD research projects in these areas, emphasizing scalable and robust energy solutions through data-driven approaches and advanced optimization techniques.

Michael H. Breitnerمشاهده پروفایل

استاد مدعو

• Energy Systems
• Digital Transformation
• IT Security
• +۷ مورد دیگر

Michael H. Breitner is an Adjunct Professor at the Institute of Business Information Systems (Wirtschaftsinformatik) within the Faculty of Economics and Management at Leibniz University Hannover. He serves on the Executive Board of the Leibniz Research Centre for Energy and holds leadership roles in the Finance Group and Faculty Council. His research focuses on energy systems transformation, digital transformation in universities, AI/ML applications, big data analytics, and cybersecurity. His academic career includes extensive work in energy informatics, mobility logistics, and decision support systems. Key projects include SiNED (secure power grids), TEN.efzn (digital energy research), and 5GAPS (5G-based positioning systems). He collaborates with industry partners like Lenze and government bodies such as the Lower Saxony Ministry of Science. Publications span journals like Decision Support Systems, Energy Policy, and Electronic Markets, with a focus on AI applications, energy systems optimization, and IT governance. His work addresses challenges in renewable energy deployment, smart city technologies, and ethical AI implementation across global contexts. Breitner advises on interdisciplinary projects involving energy policy, logistics optimization, and cybersecurity frameworks. His lab, BEAM (Behavioural Energy Analytics & Modelling), integrates behavioral science with energy system research.