جست‌وجوی استاد و پژوهشگر

• 5G/6G Networks
• Internet of Things
• Wireless Communications
• +۲ مورد دیگر

Eryk Dutkiewicz is Professor and Associate Dean (International) at University of Technology Sydney's Faculty of Engineering and Information Technology. Former Head of School of Electrical and Data Engineering (2015-2024), his research focuses on 5G/6G networks, IoT systems, and spectrum sharing technologies. Leads industry collaborations with Intel, DFAT, and ASEAN partners on projects including Vietnam's Industry 4.0 implementation, disaster management systems, and innovation ecosystems. Developed novel frameworks for secure satellite communications and metaverse resource allocation. Educational background: PhD in Telecommunications, University of Wollongong (1995) Industry experience includes positions at Motorola Labs, OTC, and Telstra. Holder of 19 patents in wireless communications. Author of over 400 publications in areas spanning cognitive radio, IoT security, and satellite networks.

Omar Anwarمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Low Power Computing
• Wireless Sensor Networks
• +۳ مورد دیگر

Omar Anwar is a Research Fellow at the International Centre for Radio Astronomy Research (ICRAR) at the University of Western Australia. He holds a BS in Electronic Engineering from Muhammad Ali Jinnah University (2007) and an MS in Embedded Systems Engineering from the University of Leeds (2009). His research focuses on Machine Learning, Low Power Computing, Wireless Sensor Networks, and Radio Frequency Interference (RFI) mitigation in radio astronomy. Currently, he contributes to the Data Intensive Astronomy (DIA) group at ICRAR, addressing RFI challenges critical to astronomy research. Education: Bachelor of Science in Electronic Engineering, Muhammad Ali Jinnah University, 2007 Master of Science in Embedded Systems Engineering, University of Leeds, 2009 Research Interests: Anwar’s work combines machine learning with hardware optimization to solve real-world challenges. His innovations include developing low-power, long-range sensor systems for remote beehive health monitoring and pioneering the first ML model for beehive weight estimation. His current focus on RFI minimization aims to enhance radio astronomy data quality. His research bridges agriculture, embedded systems, and astrophysics, emphasizing interdisciplinary applications. Awards & Grants: No specific awards or grants are listed in the provided texts. Advising & Labs: Anwar is part of the DIA group at ICRAR, collaborating on large-scale astronomical data challenges. No formal advisee list is provided.

• Biomechanics
• Rehabilitation Engineering
• Assistive Technologies
• +۷ مورد دیگر

Alpha Agape is an Associate Professor at the Malaysia School of Engineering, Monash University. His work bridges biomechanics, rehabilitation engineering, and assistive technologies, with a focus on injury prevention, virtual reality for fall assessment, and soft robotics. He has mentored students in academic and industry roles and actively engages in community outreach for public education on sports performance and health. Graduate Certificate in Higher Education (2018) PhD in Engineering Sciences (2011) Bachelor of Mechatronics Engineering (2007) His research interests span biomechanics, cyberphysical systems for remote monitoring, and AI-driven injury prevention. Recent projects involve soft robotics for elderly support and AI-enhanced rehabilitation systems. Publications highlight trends in neural network applications for gait analysis, muscle activity estimation, and assistive device optimization. MUPA Supervisor of the Year Award, 2018 ITEX 2020 Bronze Medalist As an educator, he emphasizes interdisciplinary collaboration and research integrity. His external roles include leadership positions in the IEEE Computer Society (Malaysia) from 2013–2020. Current projects include fall prevention technology and soft robotics for object retrieval, reflecting his commitment to healthy aging and community well-being.

Nur Hazlizaمشاهده پروفایل

مدرس

• MEMS
• IoT
• Embedded Systems
• +۳ مورد دیگر

Nur Hazliza is a Lecturer in the Department of Common Engineering at the Malaysia School of Engineering, Monash University Malaysia. She holds a PhD in Electrical & Electronics Engineering from Universiti Kebangsaan Malaysia (UKM), completed in 2019, with a focus on MEMS-based true north determination. Her research has been recognized with awards, including the Islamic Innovation Challenge 2019 Gold Medal and a gold medal at the 2017 International Conference and Exposition on Inventions. She has over ten years of teaching experience, previously serving as Head of Tutor and Diploma Coordinator at UCSI University (2008–2015) and part-time lecturer at Segi University (2017–2018). Her expertise spans MEMS, IoT, embedded systems, control systems, robotics, and digital signal processing. Education: PhD (UKM, 2019), MSc Microelectronics (UKM, 2015), Bachelor of Electronics Engineering Technology (UniKL, 2008). Current Project: Leading as Chief Investigator in the 'Agriculture 4.0' project (2023–2025), focusing on digital twins and deep learning for agriculture. Her research trends emphasize sensor development, navigation systems (e.g., gyrocompassing), and applications in agriculture and food safety (e.g., honey adulteration detection). Recent articles highlight innovations in MEMS, optical fiber sensors, and machine learning. Awards: Islamic Innovation Challenge Gold Medal (2019), 2017 National Intellectual Property Awards finalist. Activities: Peer reviewer for journals like Spectrochimica Acta and Measurement , mentor for internships, and organizer of STEM programs like Long Pasia Solar STEM.

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

Sylvie Thiebauxمشاهده پروفایل

استاد

• Artificial Intelligence
• Energy Systems
• Optimization
• +۵ مورد دیگر

Sylvie Thiebaux is a Professor at the School of Computing, Australian National University (ANU). Her research focuses on artificial intelligence, particularly in planning algorithms, heuristic search, and their applications to energy systems and optimization. She holds a Dipl.Eng. from INSA Rennes, an MSc from Florida Tech, and a PhD from Université de Rennes/CNRS. Her work integrates machine learning with classical AI techniques to address challenges in smart grids, renewable energy integration, and multi-objective decision-making. Key projects include optimizing distribution networks with high PV penetration, developing robust control strategies for volt/Var systems, and advancing neuro-symbolic AI for planning under uncertainty. She has contributed to over 90 publications and actively supervises research students in computational planning and energy systems. Her research also explores ethical considerations in AI, including normative compliance in planning systems. Collaborative initiatives with industry and academia have led to advancements in energy market frameworks and distributed resource coordination.

Mehdi Mobliمشاهده پروفایل

استاد

• NMR Spectroscopy
• Structural Biology
• Biomolecular Modeling
• +۲ مورد دیگر

Mehdi Mobli is Professor and Group Leader at the Australian Institute for Bioengineering and Nanotechnology, University of Queensland. His research focuses on biomolecular structure and dynamics using NMR spectroscopy, with applications in peptide engineering and ion channel modulation. Key research areas: Advanced NMR techniques for protein structure determination Peptide toxin engineering for ion channel modulation Computational methods for biomolecular design Structural basis of venom peptide function Development of cyclic peptide therapeutics Honors include the ASBMB Merck Medal, Tregear Award, Sir Paul Callaghan Medal, and ARC Future Fellowship. Research has yielded novel peptide therapeutics and computational tools for structural biology.

Georgios Angelisمشاهده پروفایل

پژوهشگر ارشد

• Medical Imaging
• Biomedical Engineering
• PET/SPECT Image Reconstruction
• +۳ مورد دیگر

Dr Georgios Angelis is a National Imaging Facility Fellow at the University of Sydney, specializing in PET/SPECT image reconstruction and pharmacokinetic modeling. His research focuses on developing advanced imaging techniques for neuroscience and oncology applications, including motion correction algorithms, parametric image analysis, and deep learning approaches. He holds a PhD in Biomedical Engineering from the University of Manchester and has held postdoctoral roles at the University of Sydney's Brain and Mind Centre and the Northern Sydney Cancer Centre. His work bridges imaging physics and clinical practice, with contributions to open-field PET systems and tumor tracking for radiotherapy. Key research areas include: medical imaging algorithms, neurochemical PET analysis, machine learning in imaging, and translational imaging tools for freely moving subjects. Recent work emphasizes integration of MRI and PET data for improved spatial-temporal resolution, and development of Bayesian methods for neurotransmitter quantification. His projects frequently involve collaborations in oncology and neuroscience, with applications to both preclinical and clinical settings.

• Granular Mechanics
• Geotechnical Engineering
• Soil Dynamics
• +۳ مورد دیگر

Associate Professor Pierre Rognon is a researcher in the School of Civil Engineering at the University of Sydney, specializing in granular mechanics and geomechanics. His research focuses on predicting soil failure mechanisms, landslides, and avalanche dynamics to enhance safety measures. He holds a PhD from École Nationale des Ponts et Chaussées (France). Research interests include dense granular flows, soil-structure interaction, and the rheology of particulate materials. He collaborates with industry partners like Abergeldie and Transgrid to address challenges in geotechnical engineering, energy storage, and infrastructure design. Current projects involve optimizing energy farm foundations and developing cost-effective soil anchors. Pierre has authored over 80 peer-reviewed articles, including studies on granular diffusion, shear-induced phenomena, and machine learning applications in granular analysis. His work bridges geophysics, materials science, and computational modeling. He advises students on topics like desiccation crack impacts and energy infrastructure resilience. Key collaborations include partnerships with CNRS (France) for granular dynamics research and the development of the patented Stadium Shear Device to study dense granular flows. His research also extends to biomimetic anchor designs inspired by tree roots.

Basem Suleimanمشاهده پروفایل

مدرس ارشد

• AI-driven Software Services
• Applied Artificial Intelligence (GenAI/LLM, Machine Learning)
• Education Technologies (Personalized Learning)
• +۴ مورد دیگر

Dr. Basem Suleiman is an Adjunct Senior Lecturer in Advanced Computing at the University of Sydney and Deputy Director of the Software Engineering Program at UNSW Sydney. He holds a Ph.D. in Computer Science from UNSW (2012) and has over a decade of experience in academia and industry, including roles at SAP, CSIRO’s Data61, and leading universities. Education: Ph.D. in Computer Science, UNSW Sydney (2012) Graduate Certificate in Research Commercialization & Management, UNSW Sydney Master of Computing (Software Engineering), Western Sydney University Research Interests: AI-driven Software Services: Federated Learning, Recommender Systems, Human-Machine Interaction Applied AI: GenAI/LLMs, Machine Learning, Deep Learning for FinTech, Healthcare, and Education Cloud Computing: Elasticity, Workload Management, Privacy-Preserving Techniques Key Contributions: Developed AI models for structural health monitoring, personalized learning systems, and anomaly detection Secured research grants and published 80+ papers in venues like ACM Transactions, IEEE Conferences, and IJCAI Supervised 15+ PhD/MPhil students and led industry partnerships with SAP, CSIRO, and global tech firms Awards & Recognition: Runner-up Best Paper Award (2023) Dean’s Commendation for Teaching Excellence Invited Keynote Speaker (2022 ICoSEIT) Engagement: Leads industry collaborations as UNSW’s Industry Capstone Liaison Officer, fostering partnerships for student projects and curriculum innovation.

• Bayesian Methodology
• Statistical Machine Learning
• Variational Bayes
• +۳ مورد دیگر

Dr. Minh-Ngoc Tran is an Associate Professor in Business Analytics at the University of Sydney Business School and an Associate Investigator in the ARC Centre of Excellence for Mathematical and Statistical Frontiers. His research develops Bayesian and machine learning methods for complex models with big data. His methodological innovations include quantum-enhanced variational Bayes, manifold optimization techniques, and subsampling MCMC algorithms. Current research focuses on time series modeling for financial markets, quantum computing applications in statistics, and variational inference for models with intractable likelihoods. Dr. Tran teaches quantitative methods, data mining, and predictive analytics. He currently supervises PhD students in deep learning for financial time series, explainable AI, and quantum machine learning. Recent research grants support quantum computation in business analytics and deep learning-based financial forecasting. His work has been recognized through awards including the University of Sydney Business School Emerging Scholar Research Fellowship and designation as Australia's top researcher in Probability and Statistics with Applications in 2021.

Gayan Chaminda Lankeshwaraمشاهده پروفایل

پژوهشگر ارشد

• Grid Integration of Distributed Energy Resources
• Active Distribution Network Management
• Machine Learning Applications in Power Systems
• +۳ مورد دیگر

Gayan Chaminda Lankeshwara is a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland (Australia). He holds a B.Sc.Eng. (Hons.) and M.Sc.Eng. in Electrical and Electronic Engineering from the University of Peradeniya, Sri Lanka (2016 and 2021), and a Ph.D. in Electrical Engineering from The University of Queensland (2023). His research focuses on grid integration of distributed energy resources, active distribution network management, and machine learning applications in power systems. His work emphasizes dynamic operating envelopes frameworks, demand response mechanisms, and low-voltage distribution networks optimization. Key contributions include developing control schemes for thermostatically controllable loads, peer-to-peer energy trading models, and hierarchical control strategies for residential loads under uncertainties. His research bridges theoretical advancements with practical applications in smart grid technologies. Lankeshwara has contributed to over 11 publications, including 8 journal articles and 3 conference papers, focusing on renewable energy integration, demand response algorithms, and network-aware control systems. His doctoral thesis (2023) explored 'Network-aware demand response in the presence of uncertainties.' He collaborates with the Power, Energy and Control Engineering research group at UQ, contributing to projects that enhance grid resilience and efficiency through advanced control methodologies and data-driven approaches.

Hadi Mousaviمشاهده پروفایل

پژوهشگر ارشد

• Antenna Design
• Medical Imaging
• Electromagnetic Systems
• +۳ مورد دیگر

Hadi Mousavi is a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on advanced antenna design for medical imaging applications, particularly in electromagnetic torso imaging systems. He holds a PhD in Electrical Engineering (2025) from the same institution, where his thesis addressed compact wideband antenna solutions for enhanced medical diagnostics. Key research interests include: Antenna optimization for deep torso imaging Substrate integrated waveguide (SIW) antennas Dual-polarized and circularly polarized antenna systems Wideband performance enhancement Medical imaging system integration Microwave filter design His recent work (2023-2025) emphasizes compact, high-performance antennas with applications in biomedical diagnostics. Notable contributions include SIW cavity-backed antennas, tapered graded index lens antennas, and dual-sense circularly polarized designs. Articles frequently address challenges like penetration depth, bandwidth optimization, and polarization control in medical imaging contexts. Collaborations involve co-authors from leading institutions, focusing on antenna modeling, electromagnetic simulations, and experimental validation. Current research trends emphasize reconfigurable antennas and integration with clinical imaging systems. No scientific awards are explicitly mentioned in the provided materials.

Hanna Kurniawatiمشاهده پروفایل

استاد

• Robotics
• Decision-Making Under Uncertainty
• Motion Planning
• +۴ مورد دیگر

Hanna Kurniawati is a Professor at the ANU School of Computing and holds the SmartSat CRC Professorial Chair for System Autonomy, Intelligence, and Decision-Making. She leads the ANU Node and Planning & Control theme of the ARIAM Hub, and founded the Robot Decision Making group. Her research focuses on scalable algorithms for decision-making under uncertainty, particularly in robotics and autonomous systems. She has received prestigious awards, including the RSS 2021 Test of Time Award and multiple best-paper recognitions. She is an active conference organizer and editorial board member for journals like IEEE Transactions on Robotics. Education: BSc Computer Science, University of Indonesia PhD Computer Science (Robot Motion Planning), National University of Singapore (2008) Research Interests: Planning under uncertainty and POMDP frameworks Robot motion planning and computational geometry Integration of planning and reinforcement learning Autonomous system assurance and safety Service and Leadership: Former President of the Australian Robotics and Automation Association (2019–2020) Keynote speaker at ICRA 2025, IROS 2018, and ICAPS 2025 Program Co-Chair for ICRA 2022 and Editor roles for IEEE TRO and RA-L Teaching: Advanced Topics in AI (COMP4620/8620) Advanced Topics in Machine Learning (COMP4680/8650) Algorithms (COMP3600/6466)

Liang Zhengمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Deep Learning
• Person Re-identification
• +۳ مورد دیگر

Liang Zheng is a Senior Lecturer in the School of Computing at The Australian National University (ANU). He holds a Computer Science Futures Fellowship and an ARC DECRA Fellowship. His research focuses on computer vision applications such as person re-identification and medical image understanding, alongside fundamental challenges in dataset-level learning and synthetic data analysis. Zheng has contributed to influential datasets like Market-1501, PRW, and MARS, advancing person re-identification and multi-camera tracking. He has served as Area Chair for CVPR, ECCV, and ACM Multimedia, and is an Associate Editor for IEEE T-CSVT. Education: PhD (Electrical Engineering) from Tsinghua University (2015), Bachelor of Science (Life Science) from Tsinghua University (2010). His research integrates deep learning and generative models, addressing challenges in image generation, adversarial robustness, and multi-agent systems. Notable awards include the Computer Science Futures Fellowship (ANU) and ARC DECRA Fellowship (2020). Key contributions include pioneering work on re-identification datasets and methods, as well as advancements in cross-modal retrieval and domain adaptation. Ongoing research emphasizes scalable models, synthetic data generation, and ethical AI practices.