جست‌وجوی استاد و پژوهشگر

Guanliang Chenمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence in Education
• Natural Language Processing
• Learning Analytics
• +۳ مورد دیگر

Dr. Guanliang Chen is a Senior Lecturer in the Department of Human Centred Computing at Monash University, Australia. He holds a Ph.D. in Computer Science from Delft University of Technology, Netherlands. His research focuses on applying AI technologies to educational settings to create inclusive learning environments, emphasizing fairness in machine learning and automatic generation of educational materials. Education : Ph.D. in Computer Science, Delft University of Technology (2019) M.Eng. in Software Engineering, South China University of Technology (2014) Research Interests : Artificial Intelligence in Education Natural Language Processing Learning Analytics Educational Data Mining Algorithmic Fairness Key Projects : Augmenting Emergency Resuscitation Simulation with AI (2024–2027) Hierarchical Abstractions and Reasoning for Neuro-Symbolic Systems (2023–2027) Large-scale Multimodal Knowledge Management (2022–2025) Awards : Dean’s Award for Equity, Diversity and Inclusion (Research) (2021) Outstanding Paper Award (2022) He supervises multiple Ph.D. students and has authored over 90 publications. His editorial roles include serving on the boards of Computers & Education: Artificial Intelligence and Computers & Education: X Reality .

Fatemeh Babaeianمشاهده پروفایل

پژوهشگر ارشد

• Applied Electromagnetics
• High Power Microwave
• RF Sensing
• +۳ مورد دیگر

Fatemeh Babaeian is a Research Fellow in the Department of Electrical and Computer Systems Engineering at Monash University. She holds a PhD from Monash University (2016–2020), focusing on advanced electromagnetic systems. Her expertise spans applied electromagnetics, high-power microwave systems, RF sensing, antenna design, and signal processing, with notable contributions to chipless RFID technologies and cascaded oscillator modeling. Research interests include high-power RF systems, antenna-oscillator interaction modeling, and innovative RFID applications for sensor networks and secure communications. Her work addresses challenges in microwave engineering, terahertz systems, and inverse scattering problems, leveraging hybrid optimization algorithms and metamaterial principles. Fatemeh has published over 29 peer-reviewed articles, including seminal works on switched oscillator performance evaluation and phase shifter designs. She received the Postgraduate Publications Award (2020) for her impactful contributions. Current research emphasizes antenna-circuit co-design methodologies and high-data-capacity RFID systems for emerging IoT and industrial applications. Collaborations span global institutions, with active projects in high-power microwave systems, THz antenna arrays, and orientation-insensitive RFID tag innovations. She actively supervises PhD students and contributes to interdisciplinary research bridging electromagnetic theory and practical engineering solutions.

Pouya Faridiمشاهده پروفایل

پژوهشگر ارشد

• Proteomics
• Cancer Immunotherapy
• Mass Spectrometry
• +۳ مورد دیگر

Dr. Pouya Faridi is a Senior Research Fellow at Monash University's School of Clinical Sciences and heads the Translational Antigen Discovery Laboratory. He holds a pharmacy doctorate and PhD from Shiraz University of Medical Sciences, Iran, followed by postdoctoral research at ETH Zurich and Monash University. His research focuses on developing mass-spectrometry and proteomics technologies for identifying cancer immunotherapy targets, with clinical applications in cancer vaccines. He co-directs the Monash Clinical Proteomics Facility and leads projects funded by NHMRC, Cancer Australia, and the Victorian Cancer Agency. **Education**: PharmD, Shiraz University of Medical Sciences, Iran PhD, Shiraz University of Medical Sciences, Iran **Research Interests**: Biomarker discovery via mass spectrometry Immunopeptidome analysis for precision oncology Development of novel cancer vaccines Proteomics-based theranostics **Awards & Grants**: Victorian Cancer Agency mid-career fellowship (2021) Australian Melanoma Research Foundation Early Career Award (2021) Lead investigator on NHMRC grants targeting tumor antigens Supported by Isabella & Marcus Foundation for pediatric brain tumor research **Labs & Teams**: Translational Antigen Discovery Laboratory (Monash) Co-director of Monash Clinical Proteomics Facility Collaborations with Hudson Institute of Medical Research

Cunjian Chenمشاهده پروفایل

عضو هیئت علمی

• Computer Vision
• Deep Learning
• Medical Imaging
• +۴ مورد دیگر

Cunjian Chen is an Adjunct Lecturer at the Department of Data Science & AI, Monash University, and a Research Fellow at Monash University Suzhou. He holds a PhD in Computer Science from West Virginia University and serves as an Associate Editor for journals like Neural Processing Letters and IET Image Processing. His research focuses on computer vision, deep learning, adversarial machine learning, and cross-spectral biometric systems. Notable contributions include advancements in thermal-to-visible face recognition, medical image segmentation, and robust adversarial defense mechanisms. Dr. Chen has received the Outstanding Area Chairs award at ICME 2021. He actively contributes to academic governance roles, including Tutorial Chair for IJCB and Area Chair for ICME, ICIP, ICASSP, IJCNN, and FG. He is currently accepting PhD and research assistant students in computer vision and deep learning, emphasizing innovative applications in security and healthcare. His research collaborations span global institutions, with recent work addressing challenges in cross-spectral imaging, medical AI, and adversarial robustness. Professional activities include patent engagements with the Monash Suzhou Research Institute. For further details, visit his personal website or Google Scholar profile .

• Ultrasonic Technology
• Nondestructive Testing
• Smart Materials and Structures
• +۵ مورد دیگر

Professor Ningqun Guo holds the dual roles of Professor in Mechanical Engineering and Head of School for both the Malaysia School of Engineering and School of Information Technology at Monash University Malaysia. He previously served at Nanyang Technological University, Singapore. His academic journey includes a B.Eng from Nanjing University of Aeronautics and Astronautics (China) and a PhD from Imperial College London (UK). His research focuses on stress wave propagation, ultrasound applications, smart materials, nondestructive testing, and civil infrastructure analysis. He has published over 130 papers, secured S$2 million in research grants, and supervised over 10 PhD students. Key research areas include ultrasonic technology for material characterization, smart material systems, and image processing for infrastructure monitoring. His work aligns with UN Sustainable Development Goals, emphasizing sustainable infrastructure and innovation. Notable collaborations span global institutions, with recent projects exploring AI-driven pavement crack detection, transparent object reconstruction, and 3D imaging systems. His contributions to magnetorheological fluid applications and nanofluidics further underscore his interdisciplinary impact. Grants and funding have supported projects in sensor development, structural health monitoring, and advanced imaging technologies. His advisory work has produced impactful PhD graduates in mechanical engineering and materials science. Prof. Guo leads research teams focused on smart materials, nondestructive evaluation, and computational imaging. His lab integrates experimental and theoretical approaches to solve challenges in infrastructure, photonics, and nanotechnology.

Surya Nurzamanمشاهده پروفایل

مدرس ارشد

• Soft Robotics
• Embodied Intelligence
• Bio-inspired Robotics
• +۳ مورد دیگر

Surya Nurzaman is a Senior Lecturer at Monash University Malaysia, specializing in soft robotics, embodied intelligence, and bio-inspired systems. He holds a PhD from Osaka University (2011) and has held research fellowships at ETH Zürich and the University of Cambridge. His work bridges robotics engineering with biomedical applications, emphasizing interdisciplinary collaboration. He teaches courses such as Dynamics II, Electromechanics, and Engineering Design. Research focuses on soft robotics for industrial and biomedical applications, including soft grippers, exoskeletons, and adaptive control systems. Projects include aerial robotics for oilfield inspection and AI-driven sensor frameworks. Nurzaman has received awards like the ITEX 2021 Gold Medal and the 2024 School of Engineering Excellence Award. He is actively involved in editorial roles for journals like IEEE Robotics & Automation Magazine and Frontiers in Robotics and AI. His contributions span over 50 publications, with recent work addressing tremor prediction, soft sensor modeling, and cross-domain learning. Collaborations include international partners in Japan, Switzerland, and the UK. Nurzaman’s research aligns with UN SDGs, particularly in advancing sustainable industry solutions and health innovations.

Jonathan Albrightمشاهده پروفایل

مدرس ارشد

• Social Media Analysis
• Journalism Studies
• Data Journalism
• +۳ مورد دیگر

Jonathan Albright is a Senior Lecturer and Principal Fellow at the University of Western Australia's School of Social Sciences, Media and Communication Department. He leads research in the Frontier Technologies and Society Research Lab, focusing on digital propaganda, social media influence, and online hate speech. His work bridges journalism studies, data analytics, and political communication. Research Interests: Social media's role in shaping public discourse Digital disinformation campaigns Algorithmic bias in health and political information Platform journalism ethics Recent work highlights include analyzing Islamophobic actors on Twitter (2022), studying abortion-related web ecosystems (2020), and examining Facebook's role in election interference (2018). His research frequently intersects with global tech policy and civic engagement challenges. Lab affiliations emphasize applied research on emerging technologies' societal impacts. Albright's work has been cited widely in policy discussions around misinformation and digital ethics.

T. Thang Vo-Doanمشاهده پروفایل

مدرس

• Biorobotics
• Cyborg Insects
• Bio-inspired Robotics
• +۱۳ مورد دیگر

Dr T. Thang Vo-Doan is a Lecturer at the University of Queensland in the School of Mechanical & Mining Engineering . He directs the UQ Biorobotics Lab and serves as an affiliate of both the Future Autonomous Systems and Technologies and the Queensland Brain Institute . PhD in Mechanical Engineering, Nanyang Technological University (2016) M.Eng. in Manufacturing Engineering, Ho Chi Minh City University of Technology (2010) B.Eng. in Mechanical Engineering, Ho Chi Minh City University of Technology (2008) His research focuses on biohybrid robotics , integrating biological systems with technology through cyborg insects , bio-inspired robotics , and fast lock-on tracking systems. He explores insect biomechanics and brain imaging in untethered insects , developing platforms for search-and-rescue missions and environmental monitoring. Recent work trends include: 2025: On-demand climbing control for cyborg beetles 2024: High-resolution insect tracking and soft textile muscles 2023: Intelligent insect–computer hybrid robots 2022: Autonomous navigation and robotic leg design 2018: Ultralightweight living robots Scientific honors: Human Frontier Science Program Cross-disciplinary Fellowship (2019-2022) He supervises projects on: Insect-machine hybrid robots Insect-inspired robotics Fast lock-on tracking Insect locomotion biomechanics Current grants include: NHMRC IDEAS Grant (2025-2028): Infrared and AI for Ross River virus surveillance Queensland Corrective Services Grant (2024-2027): Wastewater drug misuse analysis

• Energy-Efficient Computing
• Hardware Acceleration
• Machine Learning
• +۳ مورد دیگر

Dr. David Boland is a Senior Lecturer at the School of Electrical and Computer Engineering, University of Sydney. He holds an MEng and PhD from Imperial College London. His research focuses on energy-efficient hardware acceleration, particularly using FPGAs and application-specific integrated circuits (ASICs), to optimize computational efficiency in domains like machine learning and optical communications. He has contributed to projects involving custom hardware accelerators, federated learning for edge computing, and real-time signal processing. Education: MEng, Imperial College London, 2007 PhD, Imperial College London, 2012 Research Interests: Dr. Boland’s work emphasizes reducing computational overhead through customized hardware solutions. He explores techniques for minimizing unnecessary computations while maintaining accuracy, leveraging FPGA-based designs for parallelism and energy efficiency. Key areas include: Hardware acceleration for machine learning FPGA optimization for neural networks Energy-efficient algorithms for edge computing Online arithmetic and latency-accuracy trade-offs Grants & Collaborations: 2022: On-Board Federated Learning in Orbital Edge Computing (NSW Department of Industry) 2017: Fast Automated Anomaly Detection in Communication Networks (Defence Science & Technology Group) Affiliations: Member of the Net Zero Institute, collaborating on sustainable computing solutions.

• Robotics
• Autonomous Systems
• Data Fusion
• +۷ مورد دیگر

Hugh Durrant-Whyte is a Professor at the University of Sydney and Director of the Centre for Translational Data Science. He holds a BSc (Eng) from the University of London, an MSE, and a PhD from the University of Pennsylvania. Previously, he served as CEO of National ICT Australia (NICTA) and Director of the Australian Centre for Field Robotics (ACFR). His research focuses on robotics, autonomous systems, and data fusion, with over 350 publications and four successful startups. Education: BSc (Eng) in Engineering, University of London MSE in Robotics, University of Pennsylvania PhD in Robotics, University of Pennsylvania Affiliations: Director, Centre for Translational Data Science Former CEO, NICTA (2010-2014) Former Director, ACFR (1995-2010) His research interests span robotics, autonomous systems, and sensor networks. Notable contributions include foundational work on SLAM (Simultaneous Localization and Mapping) and decentralized data fusion. He has pioneered applications in mining automation, autonomous vehicles, and environmental modeling. His work emphasizes practical real-world systems, with projects like autonomous straddle carriers for container terminals and terrain mapping for mining operations. Awards & Honors: NSW Scientist of the Year (2010) Fellow of the Royal Society (FRS), Australian Academy of Science (FAA), and IEEE (FIEEE) Recipient of multiple IEEE Best Paper awards Grants & Labs: Leadership in securing multi-million-dollar grants for robotics and data science initiatives Centre for Translational Data Science: Focuses on translating data science into real-world impact He advises on numerous government and industry projects, bridging academic research with industrial applications. His research teams have developed influential algorithms for autonomous navigation and multi-agent systems.

• Hardware Security
• Side-Channel Attacks
• Cryptographic Circuits
• +۳ مورد دیگر

Darshana Jayasinghe is a Postdoctoral Research Associate at the School of Electrical and Information Engineering (EIE) , University of Sydney. He holds a PhD from the University of New South Wales (UNSW), completed in 2017, and worked as a Research Associate there until December 2022. His research focuses on hardware security, particularly side-channel analysis attacks and countermeasures. Education: PhD, University of New South Wales (2017) Research Interests include: Side-channel analysis attacks (Power Analysis, EM Attacks, Fault Injection) Countermeasures (Balancing, Random Execution, Masking) On-chip sensors for FPGA monitoring FPGA reliability under power fluctuations Publication Trends reveal expertise in: Hardware Security (15/15 articles) FPGA Vulnerabilities (10/15 articles) Cryptographic Countermeasures (12/15 articles) Sensor Development (5/15 articles)

• Data Visualization
• Machine Learning
• Neural Networks
• +۵ مورد دیگر

Professor Masa Takatsuka is a faculty member in the School of Computer Science at The University of Sydney, holding the rank of Professor. He serves as Associate Head of School (Postgraduate). His research focuses on data visualization, machine learning, and human-computer interaction, with notable contributions in spectral clustering, neural networks, and collaborative systems. He teaches courses such as COMP5048 Visual Analytics, COMP5116 Design of Networks & Distributed Systems, and others. Research interests include: Data visualization techniques (e.g., SOM-based methods) Graph neural networks and spectral clustering algorithms Interactive systems for large displays and collaborative environments Geospatial analysis and visualization tools like GeoVISTA Studio Recent publications span topics like random projection forests in graph convolutional networks (2023), topology-aware clustering (2018), and crowd-powered evaluation visualization (2017). His work emphasizes practical applications in domains like medical data analysis and social media sentiment exploration. He has secured grants including ARC Linkage Projects (2011, 2010) and industry partnerships. Current research students include Michael ASHSHIDDIQ PODBURY working on topological clustering methods. Labs/teams: Collaborations involve UnderworldGUI (geodynamic modeling tools) and projects leveraging self-organizing maps (SOM) for multidimensional data analysis.

• Artificial Intelligence
• Machine Learning
• Complex Networks
• +۴ مورد دیگر

Dr. Shahadat Uddin is a Senior Lecturer at the University of Sydney, holding dual positions in the School of Electrical and Computer Engineering and the School of Project Management within the Faculty of Engineering. He earned a PhD in Data Science (2011) from the University of Sydney, a Master's in Information Systems from Central Queensland University, and a Bachelor's in Computer Science from Bangladesh University of Engineering and Technology. His research focuses on AI, machine learning, and complex networks applied to health informatics and project analytics. Notably, he is recognized in the Stanford-Elsevier list of top 2% global scientists in AI and image processing since 2021. Education: PhD in Data Science, University of Sydney (2011) Masters in Information Systems, Central Queensland University Bachelor in Computer Science and Engineering, Bangladesh University of Engineering and Technology Research Interests: Dr. Uddin's work emphasizes ethical AI, equitable decision-making algorithms, and applications in healthcare and project management. His contributions include predictive models for adverse drug reactions, stakeholder network analysis in projects, and fairness assessment in deployed ML systems. Awards: University of Sydney Strategic Research Fund Award (2024) World's top 2% Scientists in AI & Image Processing (2021–Present) Dean’s Research Award (2014), Research Excellence Award (2010) Advising & Grants: He supervises projects like Tommy Zhou's work on adverse drug reaction prediction. His grants include the 2024 University of Sydney Strategic Research Fund. He also leads projects on predictive analytics and stakeholder engagement in projects. Labs/Teams: Active collaborations with the Sydney Southeast Asia Centre and Charles Perkins Centre on interdisciplinary research.

• Civil Engineering
• Geotechnical Engineering
• Materials Science
• +۴ مورد دیگر

Dr. Ilija Vego is a Research Fellow at The University of Sydney's School of Civil Engineering. He holds a PhD from Université Grenoble Alpes (2023), specializing in hygroscopic particle assembly through multi-modal imaging techniques. His research focuses on microstructural analysis of materials using X-ray tomography, neutron tomography, and MRI, with applications in geotechnics, mining, biology, and industrial sectors like food and pharmaceuticals. Education: Bachelor's/Master's in Civil Engineering (University of Padova, Italy) PhD in Hygroscopic Particle Assembly (Université Grenoble Alpes, France) Collaborative research at Georgia Institute of Technology (USA) and Université Grenoble Alpes Research Interests: Imaging techniques for material characterization Multi-phase systems mechanics Swelling and degradation of hygroscopic materials Bio-inspired engineering solutions His work bridges civil engineering and materials science, with tools like the open-source SPAM software for practical material analysis. Current projects explore granular media behavior under humidity and root-inspired anchorage mechanics.

Sara Khalifaمشاهده پروفایل

عضو هیئت علمی

• Internet of Things (IoT)
• Energy Harvesting
• Human Activity Recognition
• +۳ مورد دیگر

Dr. Sara Khalifa is an Adjunct Lecturer at the School of Electrical Engineering & Computer Science, University of Queensland. She specializes in interdisciplinary research at the intersection of IoT, energy harvesting, and machine learning. Her work focuses on human activity recognition, speech emotion analysis, and sustainable energy systems. She can be contacted at s.khalifa@uq.edu.au . Her research explores innovative applications of energy harvesting in IoT devices, leveraging solar and kinetic energy for self-sustaining systems. She also develops advanced machine learning techniques for speech emotion recognition, emphasizing deep learning and representation learning. Recent projects include FusedAR (2023), which integrates multiple energy sources for activity recognition, and surveys on IoT task scheduling (2021). Publications span IEEE Transactions and conferences like BMVA 2022 and PerCom 2021, demonstrating cross-domain contributions to embedded systems, sensor networks, and neural network analysis. While no specific grants or awards are listed, her collaborative work with industry partners like Marius Portmann and Raja Jurdak highlights active research engagement.