جست‌وجوی استاد و پژوهشگر

Maxime Cordeilمشاهده پروفایل

مدرس ارشد

• Data Visualisation
• Immersive Analytics
• Virtual Reality
• +۵ مورد دیگر

Dr. Maxime Cordeil is a Senior Lecturer in Human Centred Computing at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on Virtual and Augmented Reality technologies for data interaction, interactive visualization systems, and AR interfaces for industry applications. He has authored over 60 publications in top-tier venues such as ACM CHI and IEEE VR, and was nominated as Australia's Field Leader in Computer Graphics in 2021 and 2022. Research Interests: Data visualization, immersive analytics, medical imaging, collaborative systems, and human-computer interaction. Current Projects: Includes embedded visualizations for sports performance, interactive machine learning in 3D environments, and mixed-reality applications in forensic science. PhD Supervision: Actively guiding students in topics like immersive gesture exploration, AR for digital health, and collaborative VR systems. His work bridges theory and practice, with tools like IATK (Immersive Analytics Toolkit) and the MADE-Axes hardware system. He collaborates with industry partners like Raytracer and CSIRO, focusing on applications in space exploration, underwater training, and remote operations. Awards: Multiple best paper recognitions at ISS and CHI, plus industry-driven research grants. Labs: Leads the Immersive Analytics research group at UQ, specializing in embodied interaction and spatial computing.

• Sound and Music Computing
• Human-Computer Interaction
• Human-Centered Computing
• +۶ مورد دیگر

Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.

• Computational Biology
• Single-Cell RNA Sequencing
• Virology
• +۴ مورد دیگر

Fabio Zanini is an Associate Professor at the University of New South Wales (UNSW) , leading a research group focused on computational biology , single-cell approaches , and transcriptomic analysis across diseases like severe dengue , neonatal lung disease , cancer , and marine biology . He previously conducted postdoctoral research at Stanford University (2016-2019) and earned a PhD in Bioinformatics from the Max Planck Institute for Developmental Biology and the University of Tuebingen (2015). Current Affiliation: Group leader, UNSW Previous Training: Postdoc (Stanford), PhD (Max Planck/University of Tuebingen) His research spans single-cell RNA sequencing , computational virology , developmental cell biology , and bioinformatics tool development , with recent work on: Severe dengue progression (viral-host interactions, immune signatures) Lung development (endothelial cell diversity, hyperoxia-induced injury) Cancer genomics (mutant HSC clones, AZA therapy response) Marine biology (plankton transcriptomics, evolutionary analysis) Bioinformatics (HTSeq 2.0, northstar algorithm) Recent scientific awards include grants from the Chan Zuckerberg Initiative ($270,000), NIH R01 (multiple), ARC Discovery Grant , and NHMRC Ideas Grant . Notable contributions include: Northstar - Cell classification algorithm SpectralSeq - Hyperspectral-transcriptomic integration Tabula Muris - Mouse aging atlas He has supervised research into hematopoietic stem cell regulation , lung vascular development , and autophagy in viral infections , with collaborations across Stanford , University of Sydney , and Harvard .

• Spatio-temporal Statistics
• Computational Statistics
• Environmental Informatics
• +۳ مورد دیگر

Andrew Zammit Mangion is an Associate Professor at the University of Wollongong , affiliated with the School of Mathematics and Applied Statistics . His research focuses on spatio-temporal statistics, computational methods, and environmental informatics, with applications in climate science and geospatial data analysis. Education : PhD in Statistics (University of Sheffield, 2012), B.Eng. (University of Malta, 2007) Research Themes : Spatio-temporal modeling, Bayesian inversion frameworks (e.g., WOMBAT v2.S), deep learning integration, and statistical software development (e.g., FRK package) Grants & Projects : ARC DECRA Fellow (2018), Chief Investigator on ARC Discovery Project (greenhouse gases), ARC Special Research Initiative (Securing Antarctica's Environmental Future), and ARC Industrial Transformation Hub (TIDE). Collaborations : University of Bristol, University of Edinburgh, ESA CCI, NASA OCO-2 data projects Scientific Awards include the prestigious Australian Research Council Discovery Early Career Researcher Award (DECRA). His work spans Antarctic ice sheet analysis, CO2 flux inversion, and scalable spatial statistical models for environmental monitoring.

Maryam Ghahramaniمشاهده پروفایل

مدرس ارشد

• Human Motion Analysis
• Machine Learning
• Rehabilitation Engineering
• +۵ مورد دیگر

Dr. Maryam Ghahramani is a Senior Lecturer in AI & Robotics at the Faculty of Science & Technology, University of Canberra, Australia. She holds a BSc in Electrical Engineering from Shiraz University, Iran, and a PhD in Biometric Gait Analysis from the University of Wollongong, Australia. Biomedical Engineering Researcher Machine Learning Specialist Human Motion Analysis Expert Her research focuses on applying machine learning to human motion analysis for rehabilitation purposes, particularly in three key areas: Parkinson's Disease: Using fNIRS and machine learning for disease detection and motor function assessment Fall Prevention: Analyzing postural sway and risk of falls in older adults Spatial Disorientation: Studying balance in hypoxic aviation environments Recent publications demonstrate her work at the intersection of biomedical engineering, machine learning, and clinical rehabilitation. Current projects include: Young Onset Dementia Detection with 12-week Home-Based Exercise Programs Mild Hypoxia Analysis for Aviation Safety Balancing Mat Performance Evaluation

Ashish Sinhaمشاهده پروفایل

استاد

• Marketing Strategy
• Business Analytics
• Digital Transformation
• +۵ مورد دیگر

Professor Ashish Sinha is a leading academic in Marketing at the UQ Business School, holding concurrent roles as Visiting Professor at the Indian School of Business and Research Fellow at the Hong Kong Polytechnic University. His career spans senior leadership in academia (e.g., Academic Dean of Executive Education at ISB, Interim Dean at UTS Business School) and industry (Vice President at IRI, Chicago). His research bridges theory and practice, focusing on digital transformation, AI-driven strategies, ESG impact analysis, and marketing analytics. He has pioneered frameworks for retail optimization, category management, and B2B innovation adoption, with over 30 journal articles in top-tier outlets like Journal of Marketing and Marketing Science . Research Impacts: Sinha’s work has transformed executive education programs (e.g., ISB’s #38-ranked custom programs) and driven research excellence at UTS. He is a serial entrepreneur, having founded two analytics firms acquired for their practical impact. His $240M Food Agility CRC participation highlights his role in agribusiness innovation. Awards include the Davidson Award and twice runner-up for the Gary Lilien Practice Award for applied marketing science. Key Research Themes: AI in Marketing, Digital Transformation, ESG Strategies, Consumer Sentiment Analysis Leadership Roles: Academic Dean (ISB), ADR (UTS), Head of Marketing (UNSW) Industry Experience: Analytics leadership at IRI, strategic consulting across sectors Grants/Partnerships: CI in Food Agility CRC ($240M), multiple ERA-recognized research collaborations. Advises on AI ethics, sustainable marketing, and global business strategy.

Mehrdad Arashpourمشاهده پروفایل

دانشیار

• Automation and Robotics
• Computer Vision
• Deep Learning
• +۷ مورد دیگر

Summary Associate Professor Mehrdad Arashpour is an internationally recognized researcher and educator in construction and civil infrastructure, focusing on automation and information technologies. He leads the ASCII Lab at Monash University's Department of Civil and Environmental Engineering. His academic roles include Head of Construction Engineering and membership in the CIB's Working Commission on Off-site Construction (W121) and Infrastructure Task Group (TG91). Education: Ph.D., RMIT University, Australia M.Sc., Grenoble University, France B.Sc., IU University, Iran Research Interests: Digital twins, computer vision, robotics, BIM integration, sustainable construction, and automation in construction processes. His work contributes to UN Sustainable Development Goals, particularly in sustainable cities and communities. Grants & Awards: Over $6M in grants from ARC, Austroads, and industry partnerships. Recognitions include Editor's Choice Paper (ASCE, 2019) and Outstanding Reviewer (Elsevier, 2016). Teaching: Courses like Risk Management in Engineering Projects and Infrastructure Research Project. Advises on PhD topics in computer vision, robotics, and BIM. Labs & Collaborations: ASCII Lab focuses on smart, sustainable solutions for construction. Collaborates with global researchers and organizations like SPARC Hub and Building 4.0 CRC.

Katherine Molineمشاهده پروفایل

دانشیار

• Design History & Theory
• Experimental Design
• Critical Design
• +۳ مورد دیگر

Associate Professor Katherine Moline is an art and design scholar at UNSW, specializing in the intersection of technology and society. She holds appointments as Deputy Director of the National Facility for Human Robot Interaction (Research and Engagement) and serves on multiple advisory committees including the Community of Practice Queer, Trans and Intersex (CoPQTI). Her work bridges design research, critical theory, and socially engaged practices, with a focus on menopause, data imaginaries, and experimental methodologies. Education: PhD (Art History and Theory, UNSW, 2012), Master of Design (University of Technology Sydney, 1996), Parsons School of Design (1990), and multiple degrees from Sydney College of Arts (University of Sydney). Research Interests: Design history, critical design, co-design methodologies, socially engaged art, and the ethics of emerging technologies. Recent projects include 'Reimagining Menopause' (2024), 'The Invisible Threshold' soft robot installation (2022-2024), and 'Data Imaginary: Fears and Fantasies' exhibition (2021). Grants & Awards: ACUADS Excellence in Research Award (2024), ARC & NHMRC grants, and funding from Australia Council for the Arts, Alastair Swayn Foundation, and Maridulu Budyari Gumal SPHERE initiative. Supervision highlights include over 20 completed PhD/Master's students with awards like the Dean’s Award for Research Excellence (2009).

• Machine Learning
• Data Mining
• Computer Vision
• +۳ مورد دیگر

Professor Xue Li is a faculty member in the School of Electrical Engineering and Computer Science at the University of Queensland. His research focuses on machine learning, data mining, and their applications in healthcare, materials science, and computer vision. He has authored over 300 publications, including seminal works on knowledge graph completion, video quality enhancement, and alloy design using machine learning. His work bridges theoretical advancements with real-world applications, such as clinical diagnosis andTinyML systems. Key research interests include graph representation learning, medical informatics, and efficient algorithms for multimedia data. Notable contributions include developing commonsense-enhanced relation extraction models and frameworks for compressed video reconstruction. His research also addresses challenges in federated learning and privacy-preserving genomics. Prof. Li has collaborated extensively with industry and academia, contributing to projects in RFID systems, electronic nose pattern recognition, and cybersecurity. His work is published in top-tier venues like IEEE Transactions and ACM conferences. Despite no listed awards, his prolific output underscores academic impact.

Xiaotian Zhengمشاهده پروفایل

استادیار

• Spatial Statistics
• Spatio-Temporal Statistics
• Point Process Modeling
• +۵ مورد دیگر

Xiaotian Zheng is an Assistant Professor of Statistics at the University of Georgia. Previously, they were a Postdoctoral Research Fellow with the Australian Research Council Special Research Initiative Securing Antarctica's Environmental Future at the University of Wollongong, working under Professor Noel Cressie and Associate Professor Andrew Zammit-Mangion. They earned their Ph.D. in Statistical Science from the University of California, Santa Cruz, advised by Professors Athanasios Kottas and Bruno Sansó. Their research focuses on developing statistical and machine learning methods for analyzing complex, dependent data, particularly in ecological and environmental contexts. Key areas include spatial/spatio-temporal statistics, probabilistic downscaling, data integration, transfer learning, and statistical deep learning. Xiaotian's publications reflect their work on mixture transition distribution models, nearest-neighbor mixture models, and geostatistical frameworks for discrete-valued processes. These contributions emphasize Bayesian inference, computational efficiency, and real-world applications in environmental science and biodiversity modeling.

• Machine Learning
• Biomedical Image Analysis
• Medical Imaging
• +۳ مورد دیگر

Professor Jinman Kim is a Professor in the School of Computer Science at the University of Sydney and Director of the Biomedical Data Analysis and Visualisation (BDAV) Lab. He also serves as Research Director of the Telehealth and Technology Centre at Nepean Hospital. His research focuses on machine learning applications in biomedical image analysis, visualization, and multi-modal data processing. Kim holds a PhD in Computer Science from the University of Sydney (2006) and has held roles including Senior Lecturer (2013), Associate Professor (2016), and Professor (2022). He is an Area Editor for Computer Methods and Programs in Biomedicine and actively contributes to AI-driven healthcare initiatives. His academic journey includes a Marie Curie Fellowship at the University of Geneva (2010) and leadership roles in projects like the ARC Training Centre in Innovative Biomedical Engineering. He co-leads the Digital Health Imaging initiative under the Faculty of Engineering’s Digital Science Initiative. Kim has developed teaching programs such as the Master of Digital Health and Data Science, co-taught with the Faculty of Medicine and Health. Research interests span AI in medical imaging, telehealth systems, and interdisciplinary biomedical engineering. His work includes advancements in PET/CT fusion, tumor segmentation, and medical visual analytics. Kim’s lab explores applications like AI in dental education, cutaneous lymphoma detection, and fair AI models for healthcare. Notable collaborations include the Telehealth Remote Monitoring System for chronic patients and contributions to datasets like the HRDC Challenge for hypertension classification. His labs prioritize translating AI innovations into clinical tools for improved healthcare accessibility and precision.

• Robotics
• Human-Robot Interaction
• Social Robotics
• +۵ مورد دیگر

Associate Professor David Rye is an Honorary Associate Professor in the School of Aerospace, Mechanical and Mechatronic Engineering at the University of Sydney, affiliated with the Australian Centre for Field Robotics. His research focuses on interdisciplinary robotics, blending engineering, social sciences, and art to explore human-robot interaction, tactile sensing, and autonomous systems. Key areas include social robotics, cooperative robot behavior, and creative robotics design. His work spans theoretical and applied robotics, including studies on robot collaboration dynamics, tactile feedback systems, and robotic excavation. Notable contributions include developing EIT-based sensitive skins for robots and analyzing human comfort in multi-agent interactions. He has led projects such as the Fish-Bird art-robotics collaboration and the experimental human-robot interaction facility funded by ARC grants. Publications highlight advancements in human-robot collaboration ethics, motion planning for social robots, and control systems for autonomous machinery. His interdisciplinary approach bridges robotics engineering with creative arts, fostering innovations in both technical and artistic domains.

Jennifer Whyteمشاهده پروفایل

استاد

• Infrastructure Projects
• Project Leadership
• Systems Integration
• +۵ مورد دیگر

Professor Jennifer Whyte is a Professor and Director of the John Grill Institute for Project Leadership at the University of Sydney's School of Project Management (Faculty of Engineering). Her research focuses on project leadership, systems integration, digital transformation in construction, and future-making practices. She previously led the School of Project Management (2021-23) and holds a retained Professorship at Imperial College London's Department of Civil and Environmental Engineering. She is a Policy Fellow of the Institution of Civil Engineers, contributing to industry policy and advisory boards such as the UK Construction Leadership Council. Education: Holds a PhD and is a Fellow (FICE) of the Institution of Civil Engineers. Her work bridges academia and industry, emphasizing practical impact through tools like digital twins and visualization technologies. Current projects include the Alan Turing Institute's Data-Centric Engineering Programme (Grand Challenge III) and the EPSRC-funded VENTURA Project's Virtual Decision Room initiative. Research interests span infrastructure projects, innovation ecosystems, and leadership in complex environments. She actively supervises doctoral students exploring areas like risk management in construction and digital transformation in public institutions. Awards include recognition for policy contributions and leadership in project-based organizations. Grants include funding for Big Data-driven stakeholder engagement in mega-projects and collaborations on new energy technologies. Her global links include Imperial College London and ongoing partnerships with institutions in the UK and Australia.

• Semantic technologies
• Ontology engineering
• Internet of Things
• +۱۰ مورد دیگر

Professor Trina Myers serves as the Head of School for the School of Information Technology at Deakin University's Faculty of Science Engineering and Built Environment. With extensive experience in academia and research leadership, she plays a pivotal role in shaping IT education and research directions at Deakin. She is also an active member of the Australian Council of Deans of ICT (ACDICT), having served as its immediate past President. Her educational background includes: Doctor of Philosophy in Computer Science from James Cook University Master of Business Administration from James Cook University Master of Information Technology from James Cook University Professor Myers' research focuses on semantic technologies, ontology engineering, Internet of Things, knowledge management, natural language processing, and human-computer interaction . Her work emphasizes interdisciplinary collaboration, bridging technology with fields such as healthcare, marine science, environmental conservation, and business. She has pioneered approaches in academagogy (academic gamification) to enhance online learning engagement, particularly for adult learners. Her IoT research has significant applications in healthcare space optimization, environmental monitoring, and resource management. Her recent publications demonstrate a strong trajectory in applying AI and IoT technologies to solve real-world problems, particularly in healthcare, education, and resource optimization. There's a clear pattern of interdisciplinary work connecting computer science with healthcare, education, and environmental science. Her research increasingly focuses on human-centered technology design, especially for vulnerable populations like adolescents with autism spectrum disorder. Her notable achievements include: Fellow of the Australian Computer Society (2023) Australian Awards for University Teaching (AAUT) Teaching Award (2020) Women in IT Professional Leadership Award Finalist (2020) Asia-Pacific International Triple E Entrepreneurial Educator of the Year Award (1st runner-up, 2020) Australian Computer Society, National Digital Disruptor ICT Educator of the Year (2019) Professor Myers actively supervises doctoral students across diverse research areas including gamification in language learning, brain tumor analysis using deep learning, AI in higher education, AI for refugee resilience, data integrity in edge environments, and quantum-driven satellite networking. She has secured significant research funding, including a recent grant for "Indiginizing ICT Curriculum: A Starter Framework for the Community of Practice" through the Australian Council of Deans of ICT. Her teaching philosophy emphasizes active learning methodologies, Process Oriented Guided Inquiry Learning (POGIL), blended learning, and collective intelligence approaches.

Howard Bondellمشاهده پروفایل

استاد

• Statistical Data Science
• Model Selection
• Robust Estimation
• +۵ مورد دیگر

Howard Bondell is a Professor of Statistical Data Science at the School of Mathematics and Statistics, University of Melbourne, since 2018. He serves as Head of School since 2021, Co-Director of the Melbourne Centre for Data Science, and holds an ARC Future Fellowship (2020-2024). Ph.D. in Statistics, Rutgers University (2005) Academic Career: North Carolina State University (2005-2018) His research focuses on model selection , robust estimation , regularisation , Bayesian methods , and uncertainty quantification in statistical and machine learning. His publications emphasize applications in regression analysis, quantile modeling, variable selection for high-dimensional data, and genetic data analysis. Scientific awards include: Fellow of the American Statistical Association (2017) ARC Future Fellow (2020-2024)