جست‌وجوی استاد و پژوهشگر

James Payمشاهده پروفایل

پژوهشگر ارشد

• Conservation Biology
• Behavioral Ecology
• Spatial Ecology
• +۴ مورد دیگر

Dr. James Pay is a Research Fellow in Conservation Biology at the School of Natural Sciences, University of Tasmania. His work focuses on the behavioral ecology and conservation of threatened avian species, particularly the endangered Tasmanian wedge-tailed eagle (Aquila audax fleayi). He employs high-frequency GPS tracking and novel technologies to study flight behavior, habitat selection, and environmental contaminant impacts on top predators. Behavioral ecology of endangered raptors Spatial ecology and habitat use Environmental contaminant exposure (lead, rodenticides) Renewable energy mitigation strategies Population modeling for conservation His research examines how anthropogenic activities like wind farms, power lines, and land-use changes affect predator-prey dynamics and ecosystem health. Current projects address: Collision risk modeling with renewable infrastructure Population estimation methods via citizen science and genetics Acoustic-GPS tracking for habitat and vocalization analysis Detection probability estimation in threatened species James is actively involved in: Supervising doctoral research on wedge-tailed eagles and goshawks Collaborating with industry partners on eagle-safe wind farm planning Developing spatial risk models for infrastructure mitigation Leading field studies on predator response to human disturbance

Shuang Aoمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Reinforcement Learning
• Curriculum Learning
• +۴ مورد دیگر

Mr. Shuang Ao is a Postdoctoral Research Fellow at the School of Computer Science and Engineering, University of New South Wales (UNSW Sydney). He earned his PhD from the University of Technology Sydney in January 2024. His research focuses on machine learning, reinforcement learning, and curriculum learning, with applications in robotic control and antibody drug discovery. Research Interests: Machine Learning Reinforcement Learning Curriculum Learning Graph Algorithms Optimization Techniques Recent Publication Trends: Shuang's work spans large language models for location-based recommendations, spatio-temporal forecasting, reinforcement learning frameworks, and graph algorithm optimizations. His articles address both theoretical advancements and practical applications in scalable systems and data analysis. Contact: Email: shuang.ao@unsw.edu.au

• Landscape Ecology
• Conservation Biology
• Sustainable Agriculture
• +۶ مورد دیگر

Dr. Jim Radford is an Associate Professor at La Trobe University , where he leads the Landscape Ecology Lab and co-directs the Research Centre for Future Landscapes . His work focuses on natural capital accounting , conservation biology , and sustainable agriculture , addressing global challenges in sustaining ecosystems under climate change. Current Research: Farm-scale natural capital metrics, fire regime impacts on biodiversity, AI-driven ecological monitoring, and bird community condition indicators. Funded Projects: Includes National Landcare Program grants , Bushfire and Natural Hazards CRC projects , and Australian Department of Climate Change initiatives . Teaching: Coordinates Water Management (AGR3WMT) and teaches Landscape Ecology and Conservation (ENV3LEC) and Issues in Conservation (WBC2IC) . Scientific Awards: Fellow of Birdlife Australia (2024) for ornithological contributions.

• Robotics
• Human-Robot Interaction
• Virtual Reality
• +۷ مورد دیگر

Sheila Sutjipto is a Postdoctoral Research Fellow at the School of Mechanical and Mechatronic Engineering, University of Technology Sydney (UTS). Her research focuses on robotics, virtual reality, and human-robot interaction, with applications in mining safety, assistive technology, and industrial automation. She has published extensively in top robotics conferences and journals, demonstrating expertise in teleoperation systems, digital twin technology, and sensor fusion for robotic applications. Dr. Sutjipto's research spans multiple domains of robotics and human-computer interaction. Her work particularly emphasizes virtual reality interfaces for robot teleoperation , digital twin technology for industrial applications , and multi-modal perception systems . She has made significant contributions to mining safety through rock scaling robotics, assistive technology for visually impaired individuals, and haptic feedback systems for industrial robots. Her interdisciplinary approach integrates mechanical engineering, computer vision, and human factors to develop intuitive and safe robotic systems. Dr. Sutjipto's recent publications demonstrate a strong trajectory toward practical applications of robotics in challenging environments. Her work on digital twin-based teleoperated rock scaling robots addresses critical safety issues in mining operations. She has also pioneered multi-modal perception systems combining RGB, event cameras, and LiDAR for assistive robotics. A consistent theme across her publications is enhancing human-robot interaction through intuitive interfaces, whether via virtual reality, haptic feedback, or annotation-assisted control systems. Dr. Sutjipto has been involved in several funded research projects, including the HALO rock scaling robot project (stages 2 and 3), IntelliForce Tooling for hydraulic safety, and integration of live surround video for VR digital twins. She has collaborated with industry partners like Ausdrill and BTP Parts Pty Ltd. Her grant history shows a strong industry-academia collaboration focused on practical robotics applications. Dr. Sutjipto appears to be part of the robotics research group at UTS's School of Mechanical and Mechatronic Engineering. Her collaborations suggest involvement with teams focused on mining robotics, assistive technology, and industrial automation. She frequently collaborates with researchers like G. Paul, D.T. Le, and K. Nguyen, demonstrating strong interdisciplinary teamwork across engineering disciplines.

Juliana Hamzahمشاهده پروفایل

دانشیار

• Targeted Drug Delivery
• Nanotechnology
• Cancer Research
• +۳ مورد دیگر

Associate Professor Juliana Hamzah serves as Cancer Council WA Research Fellow and Head of the Targeted Drug Delivery, Imaging and Therapy Laboratory at the Harry Perkins Institute of Medical Research, affiliated with the University of Western Australia. With over 13 years of research experience, she specializes in developing targeted delivery platforms for imaging and treating cancer and atherosclerosis. Her academic journey includes a PhD completed in 2005, followed by postdoctoral training at the WA Institute of Medical Research (2006-2009) under Professor Ruth Ganss, and at Sanford-Burnham Medical Research Institute in California (2009-2012) as an American Heart Association Postdoctoral Fellow in Professor Erkki Ruoslahti's laboratory. She returned to Perth in 2013 as an NHMRC/National Heart Foundation R.D. Wright Biomedical Fellow. Hamzah's research focuses on targeted drug delivery and imaging for chronic inflammatory diseases, particularly cancer and atherosclerosis. Her team develops tissue-specific homing peptides to deliver contrast agents and therapeutics to pathological sites using in vivo imaging (microPET/CT, MRI, confocal) and nanotechnology platforms. Key projects include detecting early-stage tumors/plaques and developing dual-action therapies that destroy pathological lesions while reprogramming inflammatory microenvironments in breast carcinoma, insulinoma, and atherosclerotic lesions. Analysis of her 2022-2025 publications reveals strong emphasis on atherosclerosis mechanisms , cancer imaging (especially breast cancer via optical coherence elastography), and nanoparticle-based drug delivery (silica nanoparticles for antimicrobial/photodynamic therapy). Her work consistently bridges cardiovascular and oncological applications through integrated theranostic approaches. Her scientific contributions are recognized through significant awards: Cancer Council WA Research Fellow American Heart Association Postdoctoral Fellowship NHMRC/National Heart Foundation R.D. Wright Biomedical Fellow Hamzah actively mentors students and offers research projects in her laboratory, supported by competitive fellowships indicating substantial grant funding. Her Targeted Drug Delivery, Imaging and Therapy Laboratory comprises researchers developing peptide-based targeting strategies and nanotechnology platforms for disease-specific applications.

Lee Sue Hanمشاهده پروفایل

مدرس ارشد

• Computer vision
• Artificial intelligence
• Machine Learning
• +۲ مورد دیگر

Dr. Lee Sue Han serves as Senior Lecturer and Head of Department for Information and Communication Technologies at Swinburne University of Technology Sarawak's Faculty of Engineering, Computing and Science. She joined Swinburne in April 2020 following post-doctoral research with Pl@ntNet (CIRAD and INRIA) in France. Her academic credentials include a BEng (Hons) in Electronic Engineering from Multimedia University (2011), MSc in Electrical and Electronic Engineering from Shinshu University, Japan (2014), and PhD in Computer Science from University of Malaya (2018). Dr. Lee's research bridges artificial intelligence and plant biology, focusing on computer vision, machine learning, and deep learning applications for plant disease identification, cross-domain classification, and environmental monitoring. Her work explores how deep learning models interpret botanical features and align with human perception in disease diagnosis, with significant contributions to automated plant health systems. Recent publications (2021-2022) demonstrate advanced work in multi-task learning for disease identification, global-scale plant recognition, and interpretable AI models. Her research consistently appears in top venues including Frontiers in Plant Science, IEEE Transactions, and Pattern Recognition. Her accolades include the 2022 Outstanding Student Feedback on Teaching award, 2022 Swinburne Research Success Award, and Best Paper Awards in 2020 and 2018. She actively secures research funding as PI for FRGS 2021 and co-PI for FRGS 2022 and SDEC 2021 projects. Dr. Lee supervises research in generative models, sign language production, drug discovery, animal re-identification, and plant disease modeling. She maintains international collaborations initiated during her France-based post-doctoral work and participates in global challenges like PlantCLEF.

• Internet of Things
• Artificial Intelligence
• Smart Systems

Albe Chai Bing Zhe serves as an Associate Lecturer at Swinburne University of Technology's Faculty of Engineering, Computing and Science in Sarawak, having joined the institution in 2025 while completing his PhD at the same university. His academic qualifications include: Bachelor of Engineering (Hons) in Electrical and Electronic Engineering, Swinburne University of Technology, Sarawak Campus (2022) PhD in progress (examination stage), Swinburne University of Technology, Sarawak Campus Dr. Chai's research bridges Internet of Things (IoT) infrastructure with artificial intelligence to solve practical problems in agriculture and transportation. His work on smart incubators for microalgae cultivation demonstrates IoT applications in sustainable food production, while his road safety research develops machine learning models for accident prediction using non-visual data sources. This interdisciplinary approach connects engineering hardware development with data science methodologies. His 2023-2025 publications reveal a clear research trajectory: starting with foundational data mining for traffic patterns (2023), progressing to cloud-based multi-region prediction systems (2024), and culminating in integrated agricultural technology (2025). The work spans agricultural engineering, transportation safety, and embedded systems, consistently applying AI to real-world sensor data. Professional recognition includes: Graduate Engineer, Board of Engineers Malaysia (BEM) Member, Institute of Electrical and Electronics Engineers (IEEE) Dr. Chai actively seeks Master's and PhD candidates for his research areas, with supervision focusing on hands-on IoT system development and AI implementation. His examination-stage PhD status indicates he brings recent technical expertise to student projects, while his industry-aligned research suggests strong practical training opportunities. Current publications indicate active research momentum despite being an early-career academic. Though no formal lab name is specified, his research group develops physical IoT prototypes (like smart incubators) alongside data analytics pipelines, creating an environment where students gain experience from circuit design to cloud deployment.

Michelle Zeibotsمشاهده پروفایل

مدرس ارشد

• Transport Planning
• Sustainable Urban Transport
• Multi-modal Transport Networks
• +۵ مورد دیگر

Dr. Michelle Zeibots is a Senior Lecturer in the School of Civil and Environmental Engineering within the Faculty of Engineering & Information Technology at the University of Technology Sydney (UTS). She also serves as the Co-Leader of Program 5 — Transport Economics, Planning & Service Engineering within the UTS Transport Research Centre, a multi-disciplinary research hub dedicated to applied transport research and teaching. Her academic journey includes a PhD in Sustainable Futures from UTS, a BA(Hons) from Murdoch University, and a BSc(Arch) from the University of Sydney. Zeibots integrates operational, behavioral, and governance aspects of multi-modal urban transport networks in her research, consultancy, and teaching. Her expertise spans sustainable urban passenger transport systems, induced traffic growth, public and active transport models, and Least Cost Planning approaches to reduce road traffic congestion. Zeibots' recent research output demonstrates a strong focus on shared space modeling, pedestrian-vehicle interaction, traffic management optimization, and sustainable transport solutions. Her work bridges computer vision applications for crowd analysis with traditional transportation engineering, creating innovative approaches to urban mobility challenges. She has developed the Integrated Pedestrian-Vehicle Model (IPVM) and conducted significant research on effort-based pedestrian route choice behavior. Engineers Australia Transport Medal (2024) CRC Association Excellence in Innovation (2019) UTS Vice-Chancellor's Award for Research Excellence through Collaboration (2018) Finalist, CILTA 2018 Professional Women of the Year UTS Research Excellence Award for Collaboration (2018) As an educator, Zeibots teaches 48370 Road & Transport Engineering and has led continuing professional development courses in Travel Planning and Integrated Transport & Land-use. She has supervised PhD students through iMOVE CRC scholarships and secured significant research funding from Transport for NSW, Railway Manufacturing Cooperative Research Centre, ARC Linkage Projects, and other sources. Her media presence is notable, with frequent appearances where she translates technical transport concepts into accessible language for public discussion. Michelle Zeibots maintains active professional memberships with Engineers Australia (Transport Australia Society), Planning Institute of Australia, and Chartered Institute of Logistics & Transport Australia Inc. (CILTA), and her work aligns with UN Sustainable Development Goals 9, 11, 12, and 13.

• Machine Learning
• Evolutionary Algorithms
• Swarm Intelligence
• +۵ مورد دیگر

Mehdi Neshat is a Visiting Scholar at the Data Science Institute within the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He holds a PhD in Engineering from the University of Adelaide (2016-2020) and has extensive experience as a research data scientist specializing in computational optimization methods applied to complex engineering and healthcare problems. His educational background includes: PhD in Engineering, University of Adelaide (2016-2020) Neshat's research focuses on developing and applying advanced computational methods to solve real-world challenges. He specializes in evolutionary algorithms, swarm intelligence, and machine learning techniques for optimizing renewable energy systems, particularly wave and wind energy converters. His work extends to healthcare applications including genomic analysis and medical diagnostics, as well as structural engineering optimization and smart building energy management. His interdisciplinary approach bridges theoretical algorithm development with practical implementation across multiple domains, demonstrating exceptional versatility in computational problem-solving. Analysis of his recent publications reveals a strong trend toward sophisticated ensemble methods and hybrid optimization approaches that combine multiple algorithms to overcome limitations of single-method approaches. His research shows increasing sophistication in handling multi-objective optimization problems, particularly in renewable energy systems where trade-offs between power output, system stability, and cost must be balanced. The geographical focus of his energy research centers on Australian coastal regions, with practical applications for wave and wind farm deployment. Neshat has received significant recognition for his research contributions: Back-to-back Best Paper Prizes at the GECCO conference (2019 and 2020), a CORE A-ranked international optimization and machine learning conference His collaborative research spans multiple institutions and disciplines. Previously, he served as a Postdoctoral Research Associate with the Genomic analysis team at the Australian Centre for Precision Health, Cancer Research Institute, University of South Australia, and as a Senior Research Fellow at the Center for Artificial Intelligence Research and Optimization, Torrens University Australia. His work demonstrates consistent engagement with multidisciplinary teams across engineering, computer science, and healthcare domains, with a strong emphasis on practical implementation of theoretical methods. At UTS, Neshat contributes to the Data Science Institute's research agenda, focusing on applying advanced computational methods to complex real-world problems where traditional analytical approaches fall short. His current work continues to expand the boundaries of optimization techniques for renewable energy systems while exploring new applications in healthcare analytics and structural engineering.

• Pharmacology
• Pharmaceutical Sciences
• Clinical Pharmacology
• +۷ مورد دیگر

Dr Lisa Pont is a Professor in the Discipline of Pharmacy within the Graduate School of Health at the University of Technology Sydney (UTS), where she also serves as Deputy Head of School for Teaching and Learning. She is a registered pharmacist with extensive expertise in clinical pharmacology and medication safety, contributing significantly to research in antimicrobial resistance, pharmacoepidemiology, and quality use of medicines. Dr Pont's educational background includes: PhD in Clinical Pharmacology on Quality Use of Medicines from the University of Groningen, The Netherlands MSc in Epidemiology from the London School of Hygiene & Tropical Medicine Bachelor of Pharmacy from the University of Tasmania Bachelor of Science from the University of Newcastle Australia Her research focuses on improving medication safety and optimizing drug therapy across various healthcare settings. Dr Pont has made significant contributions to understanding antimicrobial resistance patterns, particularly in community and long-term care settings. Her work examines how community pharmacists can enhance antibiotic stewardship and how data systems can track medication utilization to improve access to therapies. She has developed and validated assessment tools for medication safety processes in nursing homes and investigates the relationship between medication safety practices and actual medication use. Dr Pont's expertise extends to pharmacoepidemiology, with particular interest in drug utilization research methods and applications across the Western Pacific Region. Dr Pont's recent publications demonstrate a strong focus on medication safety in aged care, antimicrobial resistance surveillance, and the impact of drug shortages on prescribing practices. Her work spans both clinical and policy-relevant research, often employing mixed-methods approaches including systematic reviews, cross-sectional surveys, and longitudinal data analysis. A notable trend in her research is the application of real-world data to address pressing medication safety issues in community and institutional settings, with increasing attention to geospatial analysis of resistance patterns and nanoparticle drug delivery systems. Dr Pont is actively involved in mentoring research students and has indicated availability for Masters Research or PhD student supervision. Her collaborative research network spans multiple countries and institutions, reflecting the international relevance of her work in pharmaceutical care and medication safety. She is a member of the UTS Ageing Research Collaborative (UARC) and contributes to the UTS Research Centre, demonstrating her commitment to interdisciplinary research approaches.

• Clinical Psychology
• Clinical Supervision
• Psychopathology
• +۳ مورد دیگر

Professor Craig Gonsalvez serves as Professor in Clinical Psychology at Western Sydney University's Translational Health Research Institute (THRI), with extensive prior roles including Director of Clinical Psychology Training at the University of Wollongong (1997-1998, 2001-2004, 2008-2010) and senior clinical positions at Westmead Hospital (Senior Clinical Psychologist and Director of Anxiety Disorders Clinic). An experienced clinician-researcher, he specializes in bridging clinical practice with training innovations. His educational foundation includes: PhD in Clinical Psychology, National Institute for Mental Health & Neuro Sciences (NIMHANS), University of Bangalore MA, University of Baroda MA, Bangalore University BA, University of Baroda Gonsalvez's research centers on clinical supervision methodologies, psychology training systems, and anxiety disorder mechanisms using psychophysiological measures. His work examines therapist beliefs about evidence-based treatments, mindfulness applications for trainees, and impostorism phenomena. Methodologically, he integrates quantitative psychophysiology (ERP, skin conductance) with qualitative supervision analysis to address real-world clinical training challenges. Analysis of his 2021-2025 publications reveals consistent focus on competency assessment innovations, supervisor-trainee dynamics, and implementation barriers for evidence-based therapies like exposure treatment. The research demonstrates strong Australian context with multi-site collaborations addressing national training needs. His scientific recognition includes: APS College of Clinical Psychologists Award of Distinction (2009) Citation for Teaching Excellence, Australian Awards for University Teaching (2016) Teaching Excellence Award, Australian Awards for University Teaching (2017) Gonsalvez has secured funding for major initiatives including the Vignette Matching Assessment Tool development and national supervisor training programs. His supervision approach emphasizes reflective dialogue, video feedback, and competency-based assessment, informed by his role as National Chair of Course Approvals for the APS Clinical College (2005-2010). He has developed Australia's accredited supervisor training framework through the APS Institute. Within THRI's Mental Health and Wellbeing research stream, he leads a collaborative team focused on improving clinical training systems through evidence-based supervision practices and assessment innovations, directly impacting Australian psychology training standards.

• Additive Manufacturing
• Crystal Plasticity Modeling
• Microstructure Analysis
• +۷ مورد دیگر

Dylan Agius is a Research Fellow at Deakin University's School of Engineering, part of the Faculty of Science Engineering and Built Environment. Based at the Melbourne Burwood Campus, his research focuses on advanced computational modeling of material behavior with particular emphasis on additive manufacturing processes and crystal plasticity. Dr. Agius's research interests span multiple areas of materials science and mechanical engineering: Additive Manufacturing (particularly electron beam powder bed fusion and selective laser melting) Crystal Plasticity Modeling and Finite Element Analysis Microstructure Evolution and Characterization Residual Stress Analysis in Welded and Additively Manufactured Components Mechanical Behavior of Titanium and Stainless Steel Alloys Creep and Fatigue Deformation Mechanisms His publication record demonstrates a strong focus on integrating experimental characterization with computational modeling to understand and predict material behavior. Recent work has particularly emphasized the relationship between microstructure and mechanical properties in additively manufactured metals, with applications to aerospace and safety-critical components. His research often combines advanced techniques like electron backscatter diffraction with sophisticated modeling approaches to capture material behavior at multiple scales. Dr. Agius has published extensively in high-impact journals such as International Journal of Plasticity, Materials Science and Engineering: A, and Additive Manufacturing. His research has been cited extensively, with several papers exceeding 50 citations. His collaborative research involves working with experts in materials characterization, mechanical testing, and computational modeling. Current projects appear to focus on optimizing additive manufacturing processes through computational prediction of microstructure and properties, as well as developing more accurate models for predicting deformation behavior in complex loading scenarios.