جستجوی استاد راهنمای دانشگاهی

• Artificial Intelligence
• Machine Learning
• Data Science
• +۷ مورد دیگر

Dr. Alireza Moayedikia is a Lecturer in Information Systems at the School of Business, Law and Entrepreneurship, Swinburne University of Technology. His research focuses on Artificial Intelligence, Machine Learning, and Data Science, with expertise in social network analysis, natural language processing, and back-end software development. He has over ten years of professional experience in AI and ML, emphasizing data preparation for machine learning tasks. Research Interests: Dr. Moayedikia’s work spans optimization algorithms for crowdsourcing, microtask management, and feature selection. His recent contributions include advancements in matrix factorization, dynamic payment systems for microtask platforms, and community detection in attributed networks. His methodologies often integrate swarm intelligence (e.g., bee colony optimization) and probabilistic models. Publications: His 19 publications reflect a strong focus on AI-driven solutions, including contributions to data-driven healthcare systems and green logistics. His articles address challenges in sparse data handling, worker reliability estimation, and multi-criteria decision-making frameworks. Grants: He contributed to the SCOPE 3 research contract (2020–2021), developing prototypes for tracking Green House Gas emissions in last-mile delivery systems. Labs/Teams: Collaborates within interdisciplinary teams at Swinburne, focusing on applied AI and sustainable logistics solutions.

Nima Talebianمشاهده پروفایل

استادیار

• Sustainable Structural Engineering
• Structural Health Monitoring
• Composite Materials in Construction
• +۶ مورد دیگر

Nima Talebian is an Assistant Professor at Bond University's Faculty of Society & Design, affiliated with the Centre for Comparative Construction Research. He is currently accepting PhD students and focuses on sustainable structural engineering, including performance evaluation, composite materials, and cold-formed steel design. His research aligns with UN Sustainable Development Goals, particularly sustainable construction practices. Education: PhD in Structural Engineering from Griffith University (2014–2018). Research Interests Dr. Talebian explores sustainable development principles in structural engineering, with emphasis on: Structural health monitoring and control Earthquake-resistant design and resilience Modular and prefabricated construction systems Energy-efficient materials and smart technologies in construction Recent Research Trends His 2023–2025 publications highlight advancements in machine learning for seismic performance assessment , IoT-based concrete monitoring , and gender equity in construction workforces . Collaborative projects include FSD-funded initiatives on robotics and composite materials. Grants & Projects 2023 FSD Research Project Grant: Investigating smart technologies in construction safety 2023 FSD Deans Award: Robotics applications in modular construction Research Infrastructure He leads research through the Centre for Comparative Construction Research, focusing on industry-academia partnerships to advance sustainable and resilient building practices.

• Data Science
• Machine Learning
• Tensor Factorization
• +۵ مورد دیگر

Dr Thiru Balasubramaniam is a Research Fellow at Queensland University of Technology (QUT), working within the Faculty of Science, School of Computer Science. His expertise lies at the intersection of data science, machine learning, and real-world applications, with a specific focus on tensor factorization methods for managing multifaceted data from IoT and Web 3.0 applications. His educational background includes a PhD from Queensland University of Technology and a Bachelor of Engineering from Anna University. Prior to his doctoral studies, he worked as a Research Assistant at the Singapore University of Technology and Design - Massachusetts Institute of Technology (SUTD-MIT) International Design Centre, where he analyzed mobility data to personalize city environments for elderly citizens in Singapore. Dr Balasubramaniam's research interests span multiple areas of data science: Tensor and Matrix Factorization methods Pattern Mining and Text Mining applications Recommender Systems development IoT data processing Web 3.0 applications Real-time analytics for multifaceted data His publication record demonstrates consistent contributions to high-impact venues including IEEE TKDE, ACM TKDD, WWW, WISE, AusDM, and PRICAI. The trend in his recent work shows increasing application of tensor factorization techniques to diverse real-world problems including environmental monitoring, pandemic modeling, social media analysis, and smart grid technology. His research often involves interdisciplinary collaborations, particularly with Professor Richi Nayak at QUT. Scientific recognition includes: QUT-CDS first byte research funding worth 30,000 AUD Dr Balasubramaniam has been actively involved in teaching data analytics subjects at QUT since 2017, including Data Exploration and Mining, Data and Web Analytics, Data Mining Technology and Applications, and Web Computing. His teaching spans both undergraduate and postgraduate levels. His research has been supported through various collaborative grants and institutional funding mechanisms at QUT.

• Cyber Security
• Software Engineering
• Cloud Computing
• +۴ مورد دیگر

Dr. Hussain Ahmad is an Assistant Professor (Lecturer) at the School of Computer and Mathematical Sciences, University of Adelaide, Australia. His research focuses on Cyber Security, Software Engineering, and Generative AI, with a particular emphasis on industry-driven innovation and real-world applications. He collaborates with prestigious institutions such as the Department of State Development South Australia, Defence Science and Technology Group Australia, and Cisco. Dr. Ahmad completed his PhD at the University of Adelaide, where he explored enhancing C2 network security, software vulnerability management, and scalable microservice architectures. He has led over 15 R&D projects, resulting in 12 peer-reviewed publications in top-tier venues like CORE A* and A-ranked conferences. His teaching philosophy integrates industry relevance, continuous feedback, and cutting-edge content, ensuring students gain practical skills aligned with modern IT demands. He advises students on research projects and maintains a strong focus on cloud-native systems, self-adaptive frameworks, and AI applications. Key contributions include frameworks like Smart HPA for resource-efficient auto-scaling and Co-Evolutionary Defence for Active Directory systems. His work bridges academia and industry, addressing challenges in cyber situational awareness, DevOps practices, and large-scale system resilience.

• Software Engineering
• Cybersecurity
• Microservices Architecture
• +۴ مورد دیگر

Colin Fidge is a Professor in the Department of Computer Science at Queensland University of Technology (QUT), Australia. His research focuses on software engineering, cybersecurity, and distributed systems, with emphasis on microservices architecture, industrial control systems, and IoT applications. He collaborates extensively with institutions like QUT's School of Electrical Engineering and Computer Science, contributing to projects in smart cities, fog computing, and blockchain-based manufacturing security. Key research interests include reengineering legacy systems into microservices, anomaly detection in industrial networks, and secure communication protocols for UAVs. He has published widely in top journals like IEEE Transactions and Information and Software Technology. His work spans theoretical contributions (e.g., Petri net models for anomaly detection) and applied solutions (e.g., fog/IoT framework optimizations). Notable publications address challenges in edge computing, data distribution for large-scale systems, and cybersecurity for critical infrastructure. He has co-authored over 161 papers and contributed to books on secure manufacturing and asset management.

• Power System Stability
• Renewable Energy Integration
• Wind Farm Planning
• +۴ مورد دیگر

Dr. Yuchen Zhang is a Lecturer and ARC DECRA Fellow at the School of Electrical Engineering & Robotics, QUT. He holds a PhD in Electrical Engineering from UNSW (2018), alongside Bachelor degrees in Engineering and Commerce. His research focuses on power system stability, renewable energy integration, wind farm planning, smart grid technologies, and AI applications in power engineering. His work bridges interdisciplinary approaches in energy systems and data-driven methodologies. Education: Bachelor of Engineering (2013) Bachelor of Commerce (2013) PhD in Electrical Engineering (2018), UNSW Research Interests: Power system stability assessment and control, grid integration of renewables, wind farm planning, smart grid technologies, smart city infrastructure, and AI-driven system development. Awards: 2020 Best Paper Award for IET Smart Cities for work on smart campus frameworks. Grants & Projects: Leads the ARC-funded project 'Data-driven Wide-area System Strength Monitoring under Weak Grid Conditions' (2024–present), focusing on enhancing power grid resilience through real-time monitoring and control strategies. Teaching: Coordinates courses on renewable energy systems and power systems management. Engages in industry collaborations across renewable energy, maritime services, and IEEE standards development. Future Work: Expanding research into electrified logistics integration, smart city energy systems, and AI-driven emergency control mechanisms for power grids.

• Environmental Robotics
• Robotic Vision
• Deep Learning
• +۳ مورد دیگر

Dr. Dorian Tsai is a Research Fellow and Associate Investigator at the Queensland University of Technology (QUT) Centre for Robotics, affiliated with the School of Electrical Engineering & Robotics. His research focuses on environmental robotics, robotic vision, and deep learning applications for large-scale environmental challenges. He currently leads the Technology Development stream in the Reef Restoration and Adaptation Project (RRAP), developing robotic technologies for coral monitoring and endangered species tracking. Education: Bachelors in Engineering Science (University of Toronto), Masters in Space Science & Technology (Lulea Technical University), Robotics & Automation (Aalto University), and a PhD in Robotics from QUT. His doctoral work involved light field features for camera motion control, completed under supervisors Prof. Peter Corke, Dr. Donald Dansereau, and Dr. Thierry Peynot. Research emphasizes robotic solutions for marine conservation (e.g., Great Barrier Reef preservation), precision agriculture, and autonomous systems. His work combines machine learning, computer vision, and robotics engineering to address real-world environmental and industrial challenges. Prior to QUT, he worked at the Canadian Space Agency and completed thesis research at NASA's Jet Propulsion Lab on rover docking systems.

• Water Pipeline Inspection
• Artificial Intelligence in Engineering
• Smart Water Networks
• +۳ مورد دیگر

Dr. Jessica Bohorquez Arevalo holds dual roles at the University of Adelaide: as a Grant-funded Researcher in the School of Architecture and Civil Engineering and as an Adjunct Lecturer in the School of Civil, Environmental & Mining Engineering. Her research focuses on innovative solutions for water infrastructure, including the use of pressure transients and artificial intelligence for pipeline inspection and monitoring. She is also actively involved in optimizing energy efficiency in water supply systems through renewable energy integration. Dr. Bohorquez Arevalo emphasizes the importance of inspiring future engineers to address water resource challenges through teaching and research communication. Her current research interests include: Transient network calming in smart water networks Active/passive pipeline inspection via neural networks and fluid transients Renewable energy (solar, battery storage) optimization in water systems Dr. Bohorquez Arevalo aims to collaborate with water utilities to develop machine learning and optimization tools for asset management and water resource challenges. She actively engages with professional networks to advance her research and educational mission.

• Reproductive Biology
• Photonics
• Embryology
• +۳ مورد دیگر

Associate Professor Kylie Dunning is an ARC Future Fellow and leads the Reproductive Success team within the Robinson Research Institute, Institute for Photonics and Advanced Sensing, and School of Biomedicine at the University of Adelaide. She specializes in reproductive biology, leveraging photonics to study oocyte and embryo development. Her work focuses on improving fertility outcomes through non-invasive diagnostic technologies. Research Interests: Light-based technologies for embryo imaging Metabolic analysis of oocytes and embryos Clinical translation of imaging tools for IVF Awards: ARC Future Fellowship Advising and Grants: Supervises postdoctoral researchers and graduate students in reproductive biology and photonics. Engages in interdisciplinary projects to bridge laboratory discoveries with clinical applications. Labs/Teams: Leads a diverse team focused on developing cutting-edge diagnostic tools for fertility and agriculture sectors.

• Biosurveillance of communicable diseases
• Infectious disease informatics
• Genomic epidemiology
• +۳ مورد دیگر

Professor Vitali Sintchenko is a public health microbiologist and informatician at The University of Sydney, affiliated with the School of Medical Sciences , Sydney Infectious Diseases Institute , and Westmead Institute for Medical Research . As a Clinical Microbiologist with NSW Health Pathology , he develops genomic epidemiology tools for communicable disease surveillance, focusing on tuberculosis, pertussis, and Salmonella. His work integrates pathogen genomics with clinical data to improve outbreak detection and control. MBBS, PhD, FRCPA, FACHI Member, Commonwealth Public Health Laboratory Network and Communicable Diseases Genomics Network Leadership in Mycobacterium Reference Laboratory and Enteric & Pneumococcal Reference Laboratories Research spans: Genomic surveillance of epidemic bacterial pathogens Development of decision support systems for outbreak response Integration of syndromic surveillance with molecular epidemiology Microbiome analysis in respiratory infections Antimicrobial resistance genomics Machine learning applications in pathogen tracking Recent publications demonstrate leadership in Salmonella and Tuberculosis genomic epidemiology, with Nature , Lancet , and PLoS contributions. His team's work on SARS-CoV-2 variants and Shigella sonnei evolution highlights real-time surveillance applications. Scientific contributions include: World's first book on Infectious Disease Informatics (Springer, 2010) Development of MGTdb genomic database Creation of DODGE outbreak detection algorithm Advancements in CRISPR-based diagnostics Key role in Australian Pathogen Genomics Program As an academic leader, he supervises students working on: Ellen Donnan : TB control strategies in NSW David Pham : Metagenomic pathogen detection Sarah Smith : Pneumococcal disease genomics Michael Wehrhahn : Dientamoeba fragilis epidemiology His laboratory at Westmead Hospital develops: Genomic outbreak detection systems AI-driven surveillance tools Pathogen transmission mapping Drug resistance prediction models

• Programming Languages
• Compiler Construction
• Parallel Computing
• +۷ مورد دیگر

Wayne Kelly is an Associate Professor in the School of Computer Science at Queensland University of Technology (QUT), Faculty of Science. He has over 25 years of academic experience and serves as the Academic Lead for Teaching and Learning and Course Coordinator for the Bachelor of Information Technology degree. PhD in Computer Science, University of Maryland, College Park, 1996 BSc (Hons) in Computer Science, University of Queensland, 1989 His research expertise lies in Programming Languages, Compiler Construction, and Parallel Computing, with significant contributions to High Performance Computing, Big Data, and Bioinformatics. His work has led to collaborations with Microsoft Research and over $2 million in external funding. His recent publications reflect a strong trend in parallel and distributed systems, embedded computing, bioinformatics data analysis, and remote sensing. Key themes include optimization of computational systems, memory management, and scalable data processing. Wayne Kelly has made impactful contributions to both teaching and research, guiding numerous postgraduate students and leading curriculum development in information technology. Optimizing I/O cost and managing memory for bioinformatics A communication model for streaming applications on MPSoC Ruby.NET: a compiler for the Common Language Infrastructure He is actively engaged in real-world technology development, including a project with a vision-impaired student to improve public transportation accessibility, currently trialed by transport authorities in Australia and the US.

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

Branislav Hredzakمشاهده پروفایل

پژوهشگر

• Control and management of distributed renewable energy resources
• Reconfigurable and hybrid energy storage systems
• Advanced control systems for power electronic converters
• +۴ مورد دیگر

Dr. Branislav Hredzak is a researcher at the Faculty of Engineering , University of New South Wales . His work focuses on power electronics, renewable energy systems, and advanced control strategies for energy storage and smart grids.

• Photovoltaics
• Solar Cells
• Machine Learning Applications in Energy
• +۴ مورد دیگر

Professor Ziv Hameiri is a faculty member at the University of New South Wales (UNSW) in the School of Photovoltaic and Renewable Energy Engineering. He holds a PhD from UNSW (2011) and a BSc from Ben-Gurion University (2005). His research focuses on photovoltaic device characterization, machine learning applications in energy, and novel solar cell technologies like tandem cells and AgriPV systems. He leads the ACDC Research Group and has received awards such as the UNSW Vice-Chancellor’s Research Fellowship (2013) and ARC DECRA (2015). Education: PhD in Photovoltaic and Renewable Energy Engineering, UNSW (2011) BSc in Electrical and Computer Engineering, Ben-Gurion University (2005) Research Interests: Development of new characterization methods for photovoltaic devices Machine learning algorithms for PV applications Defect analysis in silicon and non-silicon devices Passivation techniques for solar cell surfaces AgriPV and betavoltaic device innovation Articles Trends: Recent work emphasizes AI-driven defect analysis, luminescence imaging, and tandem solar cell optimization. Over 140 journal articles and 250 conference papers highlight his contributions to photovoltaic science. Awards: Excellence Award in Industry Engagement (2023) Multiple HDR supervision awards (2021–2020) Scientist Medal (International Association of Advanced Materials, 2018) Advising & Grants: Supervised over 15 PhD/MSc students, including notable theses like Yoann Buratti’s work on machine learning for silicon cell characterization. Active in securing grants for PV innovation and industry partnerships. Labs/Teams: Leads the ACDC Research Group, focusing on transformative photovoltaic technologies. Collaborates with UNSW facilities like the Mark Wainwright Analytical Centre.

Silvia Chowdhuryمشاهده پروفایل

پژوهشگر ارشد

• Metal-Organic Frameworks (MOFs)
• Nanotechnology
• Electrochemistry
• +۶ مورد دیگر

Dr. Silvia Chowdhury is a Postdoctoral Research Fellow at the Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland. She holds a PhD in Materials Science from UQ (2025), an MSc (Research) in Mechatronics Engineering from IIUM Malaysia, and a BSc in Electrical and Electronics Engineering from AIUB Bangladesh. Her research focuses on designing metal-organic frameworks (MOFs) for gas and biosensing applications, integrating nanotechnology and electrochemistry. Education: - PhD in Materials Science, UQ (2025) - MSc (Research) Mechatronics Engineering, IIUM Malaysia - BSc Electrical and Electronics Engineering, AIUB Bangladesh Research Interests: Dr. Chowdhury’s work emphasizes MOF engineering for enhanced sensing capabilities, including gas detection (e.g., ammonia, glucose) and electrochemical applications. Her studies explore material morphology, porosity, and functionalization to optimize performance in energy storage (e.g., supercapacitors) and biomedical contexts. Recent advancements include bimetallic MOFs for catalytic and energy applications, and template-free synthesis techniques. Awards: - Silver Medal from KERIE (2025) - Over 15 peer-reviewed publications, including 6 first-author papers, with >650 citations and an h-index of 12 Supervision: Available for PhD/MSc supervision in nanomaterials, MOFs, and electrochemical sensing. Contact via email . Labs/Teams: Affiliated with AIBN’s Materials and Nanotechnology Research Group, collaborating on interdisciplinary projects at the interface of materials science and biotechnology.