جست‌وجوی استاد و پژوهشگر

• Photonics
• Radio-over-Fibre Communications
• Microwave Photonics
• +۷ مورد دیگر

Prof Christina Lim is a Professor at the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. She serves as the Associate Dean of Research for the Faculty of Engineering and Information Technology (FEIT) and manages the Tucker Lab. Previously, she held roles as Research Group Leader of the Electronics and Photonics System group and Deputy Head of Department (Teaching and Operations) Education: PhD and Bachelors from University of Melbourne Research Interests: Radio-over-Fibre, Optical Wireless Communications, Microwave Photonics, Augmented Reality Displays, Reservoir Computing, Optical Crosshaul Networks Recent publications demonstrate expertise in optical waveguide design for AR, underwater optical wireless communications, photonic switching, and network optimization. Her projects focus on next-generation wireless infrastructure, including Photonics Computing Enabled Ultra-Broadband Wireless Communications (2024-2027, $598k ARC grant) and Additive Manufacturing of Optical Elements (2025). She has secured significant funding, including ARC Discovery Projects and Future Fellowships. Scientific Honors IEEE Fellow (2022) Optica Fellow (2018) ARC Future Fellow (2009-2013) ARC Australian Research Fellow (2004-2008) Professional Service Vice-President of Conferences, IEEE Photonics Society Deputy Editor, IEEE/Optica Journal of Lightwave Technology ARC College of Experts (2014-2016)

Farha Sattarمشاهده پروفایل

مدرس

• Mathematics Education
• Geoscience Education
• STEM Education
• +۱۱ مورد دیگر

Dr. Farha Sattar is a Lecturer in Education (Mathematics) at the Faculty of Arts and Society, Charles Darwin University. With over thirty years of teaching experience in Mathematics, Science education, GIS, Remote Sensing, and e-Learning technologies at undergraduate and postgraduate levels, Dr. Sattar brings extensive expertise to her academic role. She holds a PhD in Geospatial Science from Charles Darwin University, focusing on Spatial Mathematical Modelling for 3D Gully Mapping and Erosion Quantification. Her educational background includes: PhD in Geospatial Science (Three Dimensional Gully Mapping and Erosion Quantification within a Geoinformatics Framework), Charles Darwin University (2012) Prior academic experience at several Asian and European universities Dr. Sattar's research spans multiple interdisciplinary fields with a strong focus on the intersection of education and technology. Her primary research interests include Mathematics Education, STEM Education, Geoscience Education, Spatial Mathematical Modelling, Drone Technology, Remote Sensing, Geographic Information Systems, and Innovative Pedagogies such as experiential learning and inquiry-based approaches. She has developed expertise in cognitive development, particularly in fostering critical and creative thinking skills through iSTEM approaches. An analysis of Dr. Sattar's recent publications reveals a consistent trajectory toward integrating emerging technologies like drones, augmented reality, and geospatial artificial intelligence into educational contexts. Her work demonstrates a progression from foundational geospatial research on erosion mapping to innovative applications in STEM education. Recent publications increasingly focus on drone technology for educational purposes, spatial data infrastructure for policy development, and computational thinking development through technology-enhanced learning. Dr. Sattar has received numerous accolades for her contributions to education and research: NT Science Week Awards – Inspired NT STEM Hero of the Year award (2021) Long Service Recognition Award (2023) Finalist, CDU Alumni Award (2023) Multiple Best Presentation Awards (2008, 2010, 2017) Australian College of Educators - 2021 College Medal Nominee As a supervisor, Dr. Sattar mentors postgraduate research students including Ayesha Farhan, who is working on "A Framework for Cognitive Development: Fostering Critical and Creative Thinking Skills, Using iSTEM Approach." She actively secures research funding through various projects such as "DBELaSTEM: Drone-Based Experiential Learning and STEM Education," "STEM_D & VR: Youth STEM Learning and Empowerment with Drones and VR," and "CodProg Drone Lab." Her research is supported by grants from NT Government projects and other external funding sources. Dr. Sattar leads the CodProg Drone Lab, an innovative research space exploring drone technology applications in education. She is a certified drone pilot and aeronautical radio operator, which enables her to bridge theoretical knowledge with practical applications. Her work with the "Flying Forward: Drones, STEM Equity, and Indigenous Empowerment" initiative demonstrates her commitment to community engagement and addressing educational disparities through technology.

• Cybersecurity and privacy
• Privacy protection
• AI and machine learning
• +۴ مورد دیگر

Dr. Bo Liu is an Associate Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he serves as a core member and director of the AI Security and Privacy (AISP) Research Lab at the Australian Artificial Intelligence Institute (AAII). With expertise spanning cybersecurity, privacy protection, AI and machine learning, and wireless communications, Dr. Liu has established himself as a leading researcher in the field of AI security and privacy. Dr. Liu earned his PhD from the Department of Electronic Engineering at Shanghai Jiao Tong University in 2010. His academic journey at UTS has progressed from Senior Lecturer (November 2019-December 2022) to his current position as Associate Professor (January 2023-present). Dr. Liu's research focuses on the critical intersection of artificial intelligence and security, particularly addressing emerging threats in the age of advanced AI systems. His work spans multiple dimensions of security and privacy, including deepfake detection, privacy-preserving data synthesis, AI model security, and fair machine learning. He has pioneered approaches to detect AI-generated content, protect visual privacy through de-identification techniques, and address the complex relationship between algorithmic fairness and privacy preservation. His publication record demonstrates significant contributions across multiple cutting-edge research areas, with particular emphasis on detecting and mitigating threats from generative AI systems. His recent work reveals a strong focus on deepfake detection across multiple modalities (images, video, and audio), privacy-preserving techniques for sensitive data, and the security implications of emerging AI architectures like Retrieval-Augmented Generation systems. Dr. Liu has secured substantial research funding, including as Lead Chief Investigator on multiple ARC Discovery and Linkage Projects, totaling over $3.5 million AUD. His industry collaborations include partnerships with the NSW Department of Planning and the Reserve Bank of Australia, demonstrating the practical applicability of his research. As an academic leader, Dr. Liu serves as Associate Editor for IEEE Transactions on Broadcasting and actively contributes to the academic community through conference organization, peer review for top-tier venues, and assessment for ARC grant schemes. He also teaches courses including Penetration Testing, Ethical Hacking and Offensive Security, and supervises Masters and PhD students in cybersecurity and privacy research.

• Artificial Intelligence
• Knowledge Graphs
• Semantic Technologies
• +۵ مورد دیگر

Dr Zhe Wang is a Senior Lecturer at the School of Information and Communication Technology, Griffith University, focusing on artificial intelligence, knowledge graphs, and semantic technologies. He earned his PhD in Computer Science from Griffith University (2011) and previously worked as a Research Fellow at the University of Oxford (2011-2013) on ontology-based systems. Research: Specializes in knowledge graph construction, rule mining for explainable AI, and integrating machine learning with logical reasoning. Led development of the scalable RLvLR rule-mining system and contributed to the HermiT ontology reasoner. Teaching: Instructs undergraduate and postgraduate courses including Introduction to Artificial Intelligence, Secure Development Operations, and Software Engineering Fundamentals. Grants: Funded by Australia's Economic Accelerator Ignite Grant (2025) for AI-driven marine life survey systems and Office of National Intelligence projects (2021-2022). Publications: Active in top venues like AAAI, ICASSP, and ISWC, with recent work on temporal knowledge graph reasoning, auction design algorithms, and neurosymbolic AI systems.

Ganeshsree Selvachandranمشاهده پروفایل

استاد

• Artificial Intelligence
• Fuzzy Mathematics
• Deep Learning
• +۱۲ مورد دیگر

Ganeshsree Selvachandran is a Professor at the School of Business, Monash University Malaysia (MUM), where she conducts cutting-edge research in artificial intelligence, fuzzy mathematics, deep learning, and computational intelligence. She is actively involved in PhD supervision and leads significant research projects in biomedical imaging and forecasting. PhD in Pure Mathematics, Universiti Kebangsaan Malaysia (UKM), 2013 MSc in Pure Mathematics, Universiti Kebangsaan Malaysia (UKM), 2010 BSc (Hons) in Mathematics, Universiti Kebangsaan Malaysia (UKM), 2009 Her research focuses on fuzzy mathematics , deep learning , computational intelligence , and hybrid AI models , with applications in biomedical imaging (e.g., lung cancer detection), financial and environmental forecasting, and emotion recognition. She develops advanced fuzzy logic systems integrated with neural networks for real-world diagnostic solutions. The recent publications highlight a strong trend in applying deep convolutional neural networks and fuzzy logic to medical diagnostics, particularly in lung cancer and diabetic retinopathy detection. Her work increasingly combines generative models and hybrid AI for data augmentation and improved accuracy in healthcare applications. She also contributes comprehensive reviews in AI subfields, establishing foundational knowledge in reinforcement learning and medical AI. Scientific Awards and Recognitions: Ranked No. 6 globally in fuzzy sets/systems research by Scopus (2019) Member, Special Interest Group on Blue Economy, Malaysian Academy of Sciences (2020) Contributor to the Position Paper on Blue Economy (2022) Recipient of multiple national and international research awards Dr. Selvachandran has secured over MYR880,000 in research funding, including four Fundamental Research Grant Scheme (FRGS) grants, an industry grant from MTSFB, and a professorial chair grant from PNB. She mentors PhD students and collaborates on interdisciplinary projects. She serves as an editor for top journals like Engineering Applications of Artificial Intelligence and Computers and Electrical Engineering , and has reviewed over 150 papers for Web of Science/Scopus-indexed journals. She is involved in active research projects such as Advancing Lung Cancer Detection through Deep Fuzzy Convolutional Neural Networks and Sustainability Impact: Case Studies of UNGCMYB Member Companies . She also holds an adjunct professorship at Symbiosis International University (2023–2025), contributing to international academic collaboration.

Kumudu MUNASINGHEمشاهده پروفایل

استاد

• Next Generation Mobile and Wireless Networks
• Internet-of-Things (IoT)
• Cyber-Physical Systems
• +۶ مورد دیگر

Professor Kumudu MUNASINGHE is the Deputy Dean of the Faculty of Science and Technology and Professor of Network Engineering at the University of Canberra. He previously served as Head of the School of IT and Systems (2020–2024) and held the Cisco Research Chair (2022–2023). With a PhD in Telecommunications Engineering from the University of Sydney (2009), his research focuses on next-generation wireless networks, IoT, cyber-physical systems, and blockchain security. He has secured over $8M in research funding from the Australian Research Council, government agencies, and industry, leading to 130+ publications (H-index 21) and prestigious awards like the IEEE Best Paper Award and VC’s Research Award. Education: PhD in Telecommunications Engineering, University of Sydney (2009) Research Interests: 5G/6G Networks & Smart Grid Communications IoT Security and Blockchain Applications Cyber-Physical Systems & Energy Efficiency AI-Driven Network Optimization Grants & Projects: Lead researcher on projects totaling $8M+, including ITTC ARC Plant Biosecurity Training Center ($4.5M) and NetApp Technology Alliance Agreement Co-investigator on 14 projects addressing smart cities, satellite communications, and biosecurity Awards & Recognition: ARC Australian Postdoctoral Fellowship (2023) IEEE Best Paper Awards (2025, 2023, 2022) Fellow of Engineers Australia and Senior IEEE Member Labs & Teams: Leads research groups in Network Engineering and Cyber-Physical Systems Collaborates with industry partners like Cisco and NetApp

• Business Law
• International Trade Law
• Environmental Law
• +۶ مورد دیگر

Ridoan Karim is a Senior Lecturer at the Department of Business Law & Taxation, School of Business, Monash University Malaysia. His work bridges Business Law, International Trade Law, Environmental Law, Energy Law, and Technology Policy , with a focus on energy justice, AI ethics, blockchain applications, and legal frameworks for emerging technologies . Primary Research Areas: Energy Justice, AI Ethics, Blockchain Legal Issues, Privacy Law, and Sustainable Development Geographic Focus: Malaysia, Bangladesh, and broader Southeast Asian contexts Recent Research Trends His publications from 2018-2025 show consistent exploration of: Legal implications of AI integration in energy, healthcare, and manufacturing Blockchain technology for energy systems, health coverage, and financial transparency Energy justice frameworks across Southeast Asia and emerging economies Privacy law development in smart cities and digital environments Comparative legal studies between common law and Islamic/Shari'ah frameworks Scientific Awards No specific awards mentioned in available texts.

Hadi Khorshidiمشاهده پروفایل

پژوهشگر ارشد

• Medical Data Mining
• Optimization
• Machine Learning
• +۳ مورد دیگر

Dr. Hadi Khorshidi is a Senior Research Fellow at the Cancer Health Services Research Unit within the Melbourne School of Population and Global Health at the University of Melbourne. He joined the CHSR Group in September 2021. Previously, he held roles as a Senior Data Analyst at the Institute for Safety, Compensation and Recovery Research (ISCRR) and as a Research Fellow in the School of Computing and Information Systems. His research focuses on medical data mining, optimization, machine learning, and uncertainty quantification applied to healthcare challenges, particularly in cancer research and injury outcomes. Dr. Khorshidi earned his PhD in Applied and Computational Mathematics from Monash University in 2016, with a thesis titled “System Reliability Optimisation via Uncertainty Quantification.” He holds prior academic and professional qualifications in related fields, including a Master’s and Bachelor’s degrees (specific details not provided in the text). His research interests span interdisciplinary domains, including medical data mining , optimization techniques , machine learning applications , and uncertainty quantification , with a focus on healthcare systems and cancer research. He has contributed to projects involving agent-based modeling for disease diagnosis, system dynamics modeling for genomic sequencing implementation, and improving decision-making through AI and collaborative human-machine approaches. Dr. Khorshidi has secured notable grants and awards, including the O&G Innovation Grant and a joint research grant through the Manchester-Melbourne Research Fund. These support his work on integrating advanced technologies into healthcare decision-making and cancer management strategies. In addition to his research, he serves as a Chief Investigator in the Manchester-Melbourne Research Fund project. His collaborative efforts include editorial roles in journals such as the International Journal of System Assurance Engineering and Management , and contributions to program committees for IEEE conferences. He is affiliated with the Cancer Health Services Research Unit and collaborates with the CHSR Group, contributing to interdisciplinary teams focused on advancing healthcare solutions through data-driven methodologies.

• Urban Design
• Architecture
• Sustainable Urban Development
• +۱۲ مورد دیگر

Professor Marcus White is a distinguished academic and practitioner in architecture and urban design at Swinburne University of Technology, where he serves as Professor in the School of Design and Architecture. He co-directs the architectural firm Harrison and White Pty Ltd and leads the Spatio-Temporal Research Urban Design and Architecture Lab (STRUDAL) at Swinburne. His work bridges academia and professional practice, focusing on sustainable urban development, digital design, and healthcare environments. Education: PhD in Spatial Information Architecture, RMIT University (2009) Professor White’s research centers on innovative urban design solutions using computational methods such as parametric modeling, agent-based systems, virtual and augmented reality, and machine learning. His work addresses critical urban challenges including walkability, noise pollution, aging populations, and equitable access to public space. He also pioneers patient-centered design in stroke rehabilitation, integrating clinical insights with architectural innovation through Living Lab frameworks and VR-based co-design. His recent publications span topics such as pedestrian safety in metro stations, traffic noise annoyance mapping, AI-based SDG classification, and age-friendly urban design. These works reflect a consistent trend toward interdisciplinary, human-centered, and data-driven approaches to shaping healthier, more sustainable cities. Scientific Awards: National Citation for Outstanding Contributions to Student Learning Venice Biennale selection (2010, 2025) Victorian Architecture Medal (2018) Australian Institute of Architects Urban Design and Jackson Educational Awards (2018) European Healthcare Design Award (2022) RAIA Haddon Travelling Scholarship (2002) AIA National Emerging Architect Award Professor White actively supervises PhD students and has secured major grants from the Australian Research Council (ARC), The Florey Institute, and iMOVE Australia. His leadership in projects like NOVELL (Neuroscience Optimised Virtual Environments Living Lab) demonstrates a strong commitment to translating research into real-world impact. He collaborates extensively with clinicians, urban planners, and technologists to advance evidence-based design across sectors. Labs and Teams: Spatio-Temporal Research Urban Design and Architecture Lab (STRUDAL) NOVELL (Neuroscience Optimised Virtual Environments Living Lab) Collaborations with The Florey Institute of Neuroscience and Mental Health ARC Training Centre for Next-Gen Architectural Manufacturing

• Biomedical Engineering
• Artificial Intelligence
• Machine Learning
• +۱۲ مورد دیگر

Associate Professor Rifai Chai is a faculty member in the Department of Biomedical Engineering at the School of Engineering, Swinburne University of Technology. He serves as the Academic Director (Partnerships), reflecting his leadership in academic-industry collaboration. His research focuses on the intersection of biomedical engineering and artificial intelligence, with applications in brain-computer interfaces, medical technologies, robotics, and embedded systems. University: Swinburne University of Technology School: School of Engineering Department: Biomedical Engineering Position: Associate Professor Email: rchai@swin.edu.au His educational and professional background includes over a decade of experience in product development in hardware, firmware, and software design in Indonesia and Australia from 2000 to 2011. His research interests are extensive and include: Artificial Intelligence and Machine Learning Brain-Computer Interfaces Medical Device Design Assistive Technology (e.g., smart wheelchairs, exoskeletons) Cognitive Fatigue and Workload Monitoring Back Pain Assessment and Rehabilitation Embedded Systems EEG and Physiological Signal Processing Rifai Chai's recent publications demonstrate a strong focus on AI-driven healthcare solutions. His work spans advanced computational intelligence in medical imaging (e.g., lung cancer and thyroid cancer detection), EEG-based systems for driver fatigue and emotion classification, rehabilitation technologies using exoskeletons, and cybersecurity in industrial IoT. He employs deep learning, hybrid models (e.g., MLP-BiLSTM), and advanced signal processing techniques to solve real-world biomedical problems. His research consistently targets practical, non-invasive, and real-time applications in clinical and industrial settings. His scientific contributions include numerous high-impact publications in journals such as IEEE Access, Sensors, and Medical & Biological Engineering & Computing, as well as book chapters with Elsevier and Springer. He has secured multiple research grants from industry partners and the Australian Research Council, supporting projects in breast electromagnetic scanning, solar-powered charging poles, and haptically-enabled motion simulation. Rifai Chai actively supervises PhD and Master’s students, with current HDR projects covering areas such as brain-computer interfaces for prosthetics, cognitive workload monitoring, distracted driving detection, and AI in medical imaging. He leads a multidisciplinary research team working at the forefront of biomedical innovation. His lab integrates AI, robotics, and physiological sensing to develop technologies that improve health outcomes and human performance.

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Ruitao Feng is a Lecturer in IT (Cybersecurity) at the Faculty of Science and Engineering, Southern Cross University. He holds an adjunct role as a Research Fellow at Nanyang Technological University (Singapore). His expertise spans cybersecurity, software engineering, and AI-driven security solutions. He earned his Ph.D. in Computer Science from NTU (2016–2021) and a Bachelor’s degree from Tianjin University (2010–2014). His research focuses on security and quality assurance in software systems, particularly leveraging AI4Sec & SE for intrusion detection, malware analysis, and vulnerability detection. He actively collaborates with students and researchers to advance these fields. He teaches courses like DATA2001 Database Systems and INFO6002 Cybersecurity Essentials . Ruitao is recruiting self-motivated Ph.D. candidates with strong programming skills and seeks honors/minor thesis students from SCU. His work has been published in top-tier conferences/journals (CORE A/A*, CCF A) in computer security and software engineering.

Fanzhen Liuمشاهده پروفایل

پژوهشگر ارشد

• Graph Mining
• Anomaly Detection
• Trustworthy AI
• +۳ مورد دیگر

Dr Fanzhen Liu is a Postdoctoral Research Fellow at Macquarie University's School of Computing and a Visiting Scientist at CSIRO’s Data61 since March 2024, specializing in graph-based artificial intelligence research. He earned his PhD from Macquarie University in 2024, following Master of Research studies where he received the Executive Dean's Commendation for Academic Excellence. His research pioneers graph mining , anomaly detection , and trustworthy AI using deep learning methodologies. Key contributions include novel frameworks for graph anomaly detection with limited labels and comprehensive surveys on deep learning for community detection, addressing critical challenges in network security and social media analysis. His work bridges theoretical advancements with practical applications like e-commerce fraud detection. Analysis of his publication trajectory reveals consistent focus on graph neural networks and unsupervised learning , with increasing emphasis on real-world deployment challenges in trustworthy AI systems. Recent outputs demonstrate methodological innovations in data augmentation and residual analysis for graph-structured data. His distinguished recognition includes: Most Influential IJCAI2020 Paper Award HDR Research Rising Star (2022) Vice-Chancellor’s Commendation for Academic Excellence (2024) As a Postdoctoral Research Fellow, Dr Liu actively collaborates with CSIRO’s Data61 and contributes to Macquarie University's research ecosystem through high-impact publications and methodological innovations, though specific grant details and student supervision are not documented in the provided materials. He operates within Macquarie's School of Computing research community and maintains strategic partnerships with national research agencies through his CSIRO affiliation.

• Air Transport
• Aviation Management
• Airline Business Models
• +۱۲ مورد دیگر

Professor Zheng Lei is a Professor of Aviation at Swinburne University of Technology, School of Engineering, where he serves as Chair of the Department of Aviation within the Faculty of Science, Engineering and Technology. He holds a PhD in Air Transport and Tourism Management from the University of Surrey and has previously held academic roles at the University of Surrey and Cranfield University. He also serves as a Visiting Professor at the Civil Aviation University of China and is the founder and President of the Institute for Aviation Research, a think tank focusing on aviation in China. His research expertise lies in airline business models, air transport market analysis, regulation and policy, and aviation’s role in regional competitiveness. His work emphasizes real-world impact, advising airlines, airports, regulators, and aviation authorities globally. His fields of research include transportation, logistics, supply chains, and urban and regional planning. The 15 most recent publications reflect a consistent focus on aviation economics, policy, and digital transformation. Key themes include aviation resilience during the pandemic, market liberalization, airline competition, digital technologies like AI and blockchain, service quality assessment via NLP, and sustainable connectivity. His work employs advanced econometric, modeling, and data analytics methods to inform policy and industry practice. Professor Lei has secured significant external research funding from government and industry, including grants from the Department of Foreign Affairs and Trade, Department of Infrastructure, and Civil Aviation Safety Authority, focusing on hydrogen in aviation, alternative fuels, and advanced air mobility. He actively supervises PhD and Master’s students on topics such as hydrogen adoption, autopilot liability, advanced air mobility, airport security, and pilot success prediction, demonstrating a strong commitment to training the next generation of aviation professionals. He has led or contributed to numerous research projects and contracts, including 'Hydrogen to the Skies' and 'Regional AAM Surrogate Trial,' working with partners such as Textron Systems and government agencies. His leadership in both academic and applied research underscores his role as a key figure in contemporary aviation studies.

Lei Chenمشاهده پروفایل

استاد

• Data-Driven Machine Learning
• Crowdsourcing-based Data Processing
• Web Data Management
• +۶ مورد دیگر

Lei Chen is a Chair Professor at the Department of Computer Science and Engineering , Hong Kong University of Science and Technology (HKUST) , where he serves as Director of the Big Data Institute . He received his PhD from the University of Waterloo after completing BS and MS degrees at Tianjin University and Asian Institute of Technology , respectively. As an IEEE Fellow and ACM Distinguished Scientist , his research spans Data-Driven Machine Learning , Crowdsourcing-based Data Processing , Uncertain Databases , and Knowledge Graphs . His work on graph neural networks , spatial crowdsourcing , and privacy-preserving systems has earned multiple best paper awards at top venues like VLDB , SIGMOD , and KDD . Current research focuses on agentic neural graph databases and large language model optimization . His 15 most recent publications (2022-2025) address: Secure spatial query systems (Hu-Fu) Decentralized graph neural network training (Sancus) Explainable AI frameworks Temporal graph learning Polynomial activation functions for weather forecasting Knowledge graph applications in recommender systems Scientific Awards: VLDB Best Research Paper (2022) SIGMOD Test-of-Time Award Google Faculty Award (2013) Multiple conference best paper awards He has supervised 40+ PhD/MPhil students , many of whom now hold academic/research positions at institutions like BeiHang University , Sun Yat-sen University , and Huawei Noah's Ark Lab . His group ( Database Research Group ) leads projects in graph neural networks , knowledge graphs , and blockchain systems .

Elaheh Yadegaridehkordiمشاهده پروفایل

مدرس

• Management Information Technology
• Technology Adoption
• Sustainability
• +۷ مورد دیگر

Dr. Elaheh Yadegaridehkordi is a Lecturer in Information & Communications Technology at CQUniversity's School of Engineering and Technology, where she teaches courses including Business Process Management, Professional Communications Skills for ICT, and Foundations of Business Computing. She has earned international recognition including being named among the World's Top 2% Scientists by Stanford University and Elsevier in 2023 and receiving a Teaching Excellence Award for her innovative instructional methods. Her research focuses on management information technology, technology adoption, sustainability, big data, educational technology, health information systems, and tourism management. With over 80 impactful publications in leading academic journals and more than 3,300 citations, her work spans diverse areas including AI applications, sustainable business practices, and technology adoption across multiple sectors. She has published 44 articles in Q1/Q2 WoS journals, with 11 receiving the highest A*/A designation according to the Australian Business Deans Council list. Dr. Yadegaridehkordi has successfully supervised master's and PhD students while securing research grants that advance knowledge in her fields of expertise. Her research demonstrates consistent trends toward applying advanced analytical methods (PLS-SEM, ANFIS, SEM-ANN) to understand technology adoption across diverse contexts including autonomous vehicles, food delivery apps, and sustainable manufacturing. Her work bridges technical AI/ML approaches with practical business and societal applications. World's Top 2% Scientists (Stanford University and Elsevier, 2023) Teaching Excellence Award (2023) Qualified as a Global Talent by the Australian Government (2022) Prestigious fellowship from Iranian Vice-Presidency for Science and Technology (2020) Full PhD Scholarship from Ministry of Education Malaysia (2011-2015) Three Minutes Thesis (3MT) Competition Winner (2015) Dr. Yadegaridehkordi is actively involved in research supervision across multiple fields including Information Systems, Education Systems, Commerce and Management, Artificial Intelligence, Data Management, and Machine Learning. She serves on editorial boards and as a committee member for numerous international conferences, contributing to the advancement of knowledge in her fields. Her current research projects focus on the intersection of technology adoption, sustainability, and advanced analytical methods across diverse sectors.