Find Academic Supervisors

• Clinical and Health Psychology
• Public Health
• Applied and Developmental Psychology
• +17 more

Professor Matthew Fuller-Tyszkiewicz is Associate Dean, Research in the Faculty of Health at Deakin University and leads the Data Science Unit within the Centre for Research into Social and Early Emotional Development across the lifespan (SEED-Lifespan). With over 300 publications and $20 million in external funding, his work centers on digital health applications for mental health, particularly in body image, eating disorders, and obesity. University: Deakin University School: Faculty of Health Department: Office of the Executive Dean Health Research Centre: SEED-Lifespan He holds a PhD from Deakin University and is a Professor with a strong record in research leadership and teaching excellence. His research leverages machine learning, AI, and smartphone-based technologies to assess, track, and intervene in mental and physical health conditions. Key areas include digital interventions for perinatal mental health, predictive modeling for eating disorders, and improving treatment allocation through data analytics. He has pioneered work in eHealth, risk modeling, and ecological momentary assessment (EMA) to enhance mental health outcomes. The most recent 15 articles highlight a strong trend toward using artificial intelligence in mental health research—particularly in systematic reviews, predictive modeling for eating disorders, and mobile app-based interventions. There is a clear interdisciplinary focus, combining clinical psychology with data science, public health, and human-computer interaction. His scientific awards include: Deakin University Award for Teaching Excellence (2012) Commendation for Excellence in Teaching Awards, Faculty of Health (2008–2013) Professor Fuller-Tyszkiewicz actively supervises PhD and Master’s students across psychology and exercise sciences, with current projects on DBT apps, machine learning in digital interventions, and emotion regulation. He has secured numerous competitive grants from NHMRC, ARC, MRFF, and industry partners, supporting large-scale studies on digital mental health, stigma, and wellbeing. He also serves as Associate Editor for Body Image and on editorial boards for Eating and Weight Disorders and Mental Health & Prevention . He is a key member of the SEED-Lifespan research center, where he directs data science initiatives and collaborates across disciplines to translate research into real-world impact through digital innovation and policy-relevant science.

• Food Drying
• Bio-transport
• Multiphysics Modelling
• +3 more

Dr. Mohammad Joardder is a Postdoctoral Research Fellow at Queensland University of Technology (QUT), affiliated with the School of Mechanical, Medical & Process Engineering. He holds a PhD from QUT (2016) and a BSc from another institution. His research focuses on bio-transport, innovative food drying techniques, computational modeling of food processing, and renewable energy applications. He emphasizes multiphysics-multiscale transport phenomena and porous biomaterials' deformation. His work spans 47+ peer-reviewed articles, 6 book chapters, and 4 authored books with Springer-Nature and CRC Press. Notable achievements include a Field Weighted Citation Impact of 2.2 and a high citation rate, reflecting global leadership in drying and microwave heating research. He actively reviews for top journals like Nature, Springer, and Elsevier. Research interests include food microstructure analysis, renewable energy integration in food processing, and advanced computational methods. His recent articles (2022–2025) explore shrinkage kinetics in plant-based foods, CFD-driven drying models, and microwave-assisted food processing innovations. He is currently accepting PhD/Master’s students in drying technology, thermal systems, and food material science.

• Computer Vision
• Machine Learning
• Neural Networks
• +4 more

Sridharan Sridha is a Professor at the University of Queensland, specializing in advanced AI and computer vision research. His work spans neural networks, robotics, medical informatics, and surveillance systems. He collaborates extensively with institutions like the University of Queensland’s School of Information Technology and Electrical Engineering. Key research focuses include adversarial machine learning, multimodal fusion, and domain adaptation. His contributions to aerial-ground person re-identification (AG-ReID), LiDAR-based place recognition, and medical signal analysis have been widely recognized. Recent projects emphasize self-supervised learning, transformer-based architectures for hyperspectral imaging, and autism severity detection using physics-augmented models. His work bridges theory and practical applications in autonomous systems, healthcare, and robotics.

Justy SiwabessyView profile

Research Fellow

• Marine Geology
• Oceanography
• Acoustic Remote Sensing
• +4 more

Dr. Justy Siwabessy is an Adjunct Research Fellow at Curtin University's School of Earth and Planetary Sciences, affiliated with the Centre for Marine Science and Technology (CMST) within the Faculty of Science and Engineering. His work centers on advanced seafloor mapping techniques, acoustic remote sensing, and marine geoscience applications for environmental and industrial challenges. Research interests include seabed characterization using multibeam sonar, sediment dynamics, benthic habitat modeling, and CO2 storage feasibility analyses. He has contributed to large-scale marine surveys in remote regions, such as the southeast Indian Ocean (MH370 search area) and Australian continental margins. His methodologies integrate machine learning, geostatistics, and acoustic data to predict seabed properties and inform marine spatial planning. Publications highlight advancements in seabed hardness modeling, pockmark field analysis, and habitat mapping for conservation and energy applications. He has authored technical guidelines for multibeam survey practices and led multidisciplinary projects involving habitat classification, sediment transport dynamics, and disaster response data analysis. Key technical skills include multibeam backscatter interpretation, sediment acoustics, and predictive modeling. His work bridges geoscience, engineering, and conservation, addressing both academic and applied challenges in marine environments.

• Particle Physics
• Quantum Field Theory
• Lattice QCD
• +3 more

Dr. Ayse Kizilersu is a Grant-Funded Researcher (B) in the Department of Physics at the University of Adelaide. Her work focuses on theoretical and computational physics, with particular emphasis on lattice Quantum Chromodynamics (QCD), particle physics, and statistical distribution analysis. She is affiliated with the Physics division at the North Terrace campus, office 108A. Her research interests span non-perturbative QCD studies, quark-gluon vertex dynamics, and applications of statistical methods to finance and physics. Dr. Kizilersu's recent contributions include investigations into the Weibull distribution's properties and its applications in censored data analysis, alongside lattice QCD simulations exploring quark-gluon interactions. Her articles reflect interdisciplinary strengths in both high-energy physics and econophysics, addressing topics from particle dynamics to market order analysis. Awards and achievements sections remain unspecified in her profile, though her active grant-funded status indicates ongoing research support. No formal advising roles or student supervision details are documented here. Professional activities include contributions to lattice field theory and statistical modeling communities.

• Adversarial Machine Learning
• Cybersecurity and Privacy
• Artificial Intelligence
• +3 more

Dr. Wei Ni is a Professor at the School of Computer Science and Engineering, UNSW. He holds roles as an editor for multiple IEEE journals and publications, including IEEE Communications Surveys and Tutorials (since 2024) and IEEE Transactions on Information Forensics and Security (since 2024). His research focuses on adversarial machine learning, cybersecurity, AI, and signal processing. He is a Fellow of the IEEE and actively seeks PhD candidates in applied AI/ML, adversarial machine learning, and graph learning. Dr. Ni's qualifications include a Fellowship from IEEE. He has an extensive publication record with 411 journal articles, 145 conference papers, and 3 books. His work spans theoretical and applied domains, emphasizing interdisciplinary collaboration. He supervises research in areas such as information security and privacy, leveraging his expertise in cybersecurity and signal processing. His contributions to cyber-physical systems and vehicular technology are reflected in his editorial roles and research output.

Erick Alfons LisanganView profile

Lecturer

• Intelligent Transportation Systems
• Artificial Intelligence
• Deep Learning
• +5 more

Erick Alfons Lisangan is a Computer Science lecturer at Atma Jaya University of Makassar and a Doctor of Philosophy student at the University of Western Australia's School of Physics, Mathematics and Computing. His research integrates artificial intelligence with transportation infrastructure to address urban mobility challenges. Education Master of Computer Science, Gadjah Mada University (2013-2015) Bachelor of Computer Science, Atma Jaya University of Makassar (2006-2010) Research Interests His core focus lies in Intelligent Transportation Systems , analyzing graph traffic networks and spatiotemporal data collection. He develops algorithms for real-time traffic condition inference using embedded systems and AI-driven simulation. Specialized work includes deep learning architectures (LSTM/BiLSTM) for passenger flow prediction, fuzzy logic systems for dynamic route optimization, and wireless sensor networks for smart city applications like flood detection. His research bridges theoretical AI with practical urban infrastructure solutions. Research Output Trends Publications (2018-2025) reveal a trajectory from foundational smart city sensor networks toward advanced AI-driven transportation modeling. Recent work emphasizes hybrid deep learning for Transjakarta bus system prediction, while earlier contributions established fuzzy ant colony systems for traffic-responsive routing and image-based fake news detection frameworks. Advising and Grants Lisangan serves as a casual tutor for Data Structures & Algorithms and Computational Thinking with Python at UWA during his PhD studies. No formal advisees or research grant details are documented in the provided materials. Labs and Teams His doctoral research operates under supervision of Professor Rachel Cardell-Oliver and Professor Amitava Datta at UWA, contributing to intelligent transportation systems research groups with cross-institutional collaborations in Indonesia and Australia.

Pietro BorghesaniView profile

Associate Professor

• Asset Health Monitoring
• Vibration Sensing
• Signal Processing
• +6 more

Associate Professor Pietro Borghesani is affiliated with the School of Engineering and the Department of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW). He holds an Associate Professor rank and focuses on asset health monitoring, vibration sensing, signal processing, and machine learning applications in mechanical systems. His research spans aerospace and rail industries, emphasizing condition-based maintenance optimization and fault diagnostics. Education: PhD in Mechanical Engineering (2013, Politecnico di Milano), postdoctoral work at Politecnico di Milano, and prior experience at McKinsey & Co. as a business analyst consultant. Research interests include: Health monitoring of rotating machinery Signal processing for diagnostics Machine learning in condition assessment Wear mechanisms in gears and bearings Integration of physics-based models with AI Publications highlight advancements in neural network explainability, vibration-based diagnostics, and cepstral analysis. His work bridges signal processing with tribology and mechanical systems. Grants include projects on railway track geometry monitoring (LP200100382), sugar industry maintenance (LP150100545), and aero-engine bearing health (LP180101161). He is an Editorial Board Member for Mechanical Systems and Signal Processing and a member of the International Society for Engineering Asset Management (ISEAM). Labs/Teams: Collaborations with Australian/international companies in aerospace and rail sectors; involvement in experimental setups for vibration and acoustic emission studies.

Wei Wen WongView profile

Researcher

• Epitaxy
• Semiconductor Materials
• Photonics
• +5 more

Dr. Wei Wen Wong is a Postdoctoral Research Fellow at the Research School of Physics, Australian National University (ANU), affiliated with the ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS). He holds a PhD from ANU (2023) and a Bachelor's degree from Multimedia University, Malaysia (2016). Previously, he worked as a Product and Failure Analysis Engineer at Cypress Semiconductor (2016–2018). His research focuses on epitaxy of low-dimensional semiconductor structures and design/fabrication of photonic, optoelectronic, and metasurface devices. Key areas include quantum dot lasers, microring resonators, parity-time symmetric cavities, and InP-based nanowire structures. He has co-authored over 20 peer-reviewed papers in journals like Nano Letters , Laser & Photonics Reviews , and ACS Nano . Education: Bachelor of Engineering, Multimedia University (2016) PhD in Physics, ANU (2023) Dr. Wong’s work emphasizes Bayesian optimization for laser design, single-photon sources , and metasurface integration . His research bridges semiconductor epitaxy with advanced optical systems, targeting applications in quantum photonics and low-threshold lasers. Notable Awards: Jim Williams Award (ANU, 2023) Global Young Scientists Summit (2023) His lab collaboration focuses on InP nanowire heterostructures and quasi-bound states in micro-cavities . Current projects explore scalability of single-photon sources using droplet epitaxy and AI-driven laser optimization.

Alexandra ZafirogluView profile

Professor

• Cybernetics
• Cultural Anthropology
• Ethics in Technology
• +7 more

Alexandra Zafiroglu is a Professor of Cybernetics at the School of Cybernetics within the ANU College of Systems & Society at Australian National University (ANU), and a Fellow of the ANU Futures scheme. She holds a PhD in Cultural Anthropology from Brown University (2004) and has extensive industry experience at Intel Corporation (2004–2019), where she contributed to R&D and commercialization across Advanced Research, Digital Home, and IoT divisions, co-inventing 11 patents. Her work bridges social sciences, technology ethics, and design, focusing on the role of social scientists in ensuring accountability and data rights in cyber-physical systems deployment. She is also known for her innovative 'crochet-and-felting' figures to foster human connection in remote work environments. Her research interests include ethics in AI, gender-inclusive technology policy, and transdisciplinary research methodologies. Recent publications highlight themes such as complex systems design, AI governance in smart cities, and the future of libraries. She actively contributes to professional communities like the American Anthropological Association and the Ethnographic Praxis in Industry Community. Awards include recognition for her ANU Futures Fellowship. While no formal advisees are listed, her impact spans industry-academia collaboration and policy advocacy. She advocates for human-centered approaches in technology development, emphasizing transparency and equity in emerging systems. Her interdisciplinary work reflects a commitment to merging anthropological insights with cutting-edge technological innovation.

• Acoustics and noise control
• Dynamics, vibration and vibration control
• Signal processing
• +3 more

Dr. Sipei Zhao is a Senior Lecturer at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he has been employed since January 2021. Prior to this, he worked as a Post-doctoral Research Fellow at the Centre for Audio, Acoustics and Vibration of UTS from July 2018 to December 2020. His educational background includes a PhD in Electrical Engineering from RMIT University (2018), a Master's degree in Acoustics from Nanjing University (2015), and a Bachelor's degree in Electronics Engineering from Nanjing University (2012). Dr. Zhao's research focuses on acoustics and noise control, dynamics and vibration control, and signal processing. His work spans theoretical development and practical applications in active noise control, architectural acoustics, and machine learning for acoustic analysis. He has made significant contributions to distributed acoustic systems, neural network applications in sound field reconstruction, and innovative approaches to sound zone control. His recent publications demonstrate a strong trajectory in distributed acoustic systems, neural network applications in acoustics, and innovative approaches to sound field control and reproduction. His work combines theoretical rigor with practical implementations, often resulting in significant reductions in computational complexity while maintaining or improving performance. Best Student Paper at the 22nd International Congress on Sound and Vibration (ICSV22) in 2015 Best Paper Prize at the 21st International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRA2016) in 2016 Best Paper Award at the 23rd International Congress on Acoustics (ICA2019) in 2019 Young Professionals Grant from the International Institute of Noise Control Engineering (I-INCE) Ford Publication Commendation Prize from RMIT University in 2017 ARC Early Career Industry Fellowship in 2024 Dr. Zhao has successfully secured multiple research grants and contracts from organizations including the Australian Research Council, NSW Environment Protection Authority, and industry partners like Noizend Pty Ltd. His research has practical applications in industrial settings, transportation, and building acoustics. He serves as a peer reviewer for prestigious journals including the Journal of Sound and Vibration and IEEE/ACM Transactions on Audio, Speech, and Language Processing.

• Inverse dynamics
• Structural health monitoring
• Linear and nonlinear vibrations
• +5 more

Dr. Hamed Kalhori is a Lecturer in the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), Faculty of Engineering & Information Technology. As a Casual Academic, he contributes to teaching and research in mechanical engineering with a focus on dynamics, vibrations, and structural health monitoring. His work bridges theoretical and practical applications in civil infrastructure, aerospace systems, and composite materials. Dr. Kalhori earned his PhD in Mechanical Engineering from the University of Sydney between March 2013 and July 2017. Dr. Kalhori's research spans multiple domains within mechanical and structural engineering. His primary expertise lies in inverse dynamics problems , particularly impact force identification, where he develops advanced methodologies combining model-based approaches with machine learning techniques. He extensively investigates linear and nonlinear vibrations in various structures, from micro-plates to large-scale bridges. His work in structural health monitoring focuses on innovative approaches for bridge inspection, including drive-by assessment techniques and sensor network optimization. Additionally, he explores smart materials and structures , particularly carbon nanotube-reinforced composites and their mechanical behavior under dynamic loading conditions. Dr. Kalhori's publication record demonstrates a strong trajectory in mechanical engineering research with increasing focus on interdisciplinary approaches. His recent work shows growing integration of machine learning techniques with traditional mechanical engineering methods, particularly for solving inverse problems in structural dynamics. There's a clear progression from fundamental vibration analysis toward practical applications in infrastructure monitoring and composite material characterization. His research maintains strong connections between theoretical modeling and experimental validation across diverse structural systems. Dr. Kalhori has received notable recognition for his academic contributions: 2019 Dean's Award for Excellence in Teaching and Tutoring Multiple research grants in vibration-related fields Dr. Kalhori has secured research funding for projects related to vibration analysis and structural monitoring, including industry collaborations such as the Alstom DMU traincar crash test project (2025). He has led international research collaborations and conducted numerous workshops and short courses both locally and internationally. While the specific details of his advising relationships aren't provided in the available information, his extensive publication record and research leadership suggest active engagement with graduate students and early-career researchers. His research involves collaboration with the Centre for Autonomous Systems at UTS and Data61-CSIRO, where he previously worked as a research associate and research assistant respectively. These collaborations focus on structural health monitoring projects across New South Wales, leveraging advanced sensing technologies and computational methods for infrastructure assessment.

Badal PokharelView profile

Research Fellow

• Geospatial Engineering
• Disaster Risk Reduction and Management
• Climate Change
• +4 more

Dr. Badal Pokharel is a Research Associate at the Research Centre for Integrated Transport Innovation (rCITI) within the School of Civil and Environmental Engineering at the University of New South Wales (UNSW), Faculty of Engineering. She holds a PhD in Civil and Environmental Engineering from UNSW (2023) and an M.Sc. in Engineering Geology from Tri-Chandra Multiple Campus, Tribhuvan University, Nepal (2018), where she was the university topper. Her research focuses on the assessment of natural and human-induced disasters, particularly earthquake-triggered landslides and climate change-induced floods, using advanced geospatial approaches. Dr. Pokharel has extensive expertise in Geographic Information Systems (GIS), remote sensing (RS), and implementing geospatial systems for geohazards, agriculture, climate change, land administration, and geomorphology projects. Her methodological expertise integrates machine learning techniques with traditional geospatial methods, showing particular focus on the Himalayan region, especially Nepal. Dr. Pokharel's publications demonstrate strong expertise in landslide susceptibility mapping, earthquake-triggered landslides, and geospatial analysis of natural disasters. Her recent work includes innovative approaches using random forest methods, Persistent Scatterer Interferometry, and slope-unit-based assessments for disaster risk management, with a geographical focus on Central Nepal and the Himalayan region. Early Career Academic Social Impact Award 2023, UNSW Early Career Network (ECAN), Sydney Australia Best Talent Award, 2021 Young Generation Forum/Young Professional Forum hosted by the Korean Academy of Scientists and Engineers in Australasia University topper for Master of Science in Engineering Geology, Tri-Chandra Multiple Campus, 2018 Dr. Pokharel has secured multiple research grants including UNSW Seed funding (AUD 25000), Global Partnership Project Grant from Virginia Tech University (AUD 7200), HPC-Europa3 Transnational Access Programme research grant (AUD 3630), and PhD Research Support Grant from UNSW (AUD 3000). She is passionate about interdisciplinary and transdisciplinary research that contributes towards disaster risk reduction and management, bridging engineering, geoscience, and data science to develop practical solutions for natural disaster prediction and management.

Ana HortaView profile

Associate Professor

• Spatial Modeling
• Geostatistics
• GIS (Geographic Information Systems)
• +12 more

Ana Horta is Associate Professor and Senior Lecturer in Geospatial Science at Charles Sturt University, where she also serves as Head of Discipline for Geospatial Science. She is affiliated with the School of Agricultural, Environmental and Veterinary Sciences and the Gulbali Research Institute, contributing to the Inland Fisheries Research Group. Her work spans teaching, research, and leadership in spatial sciences, with a strong emphasis on real-world applications in environmental and public health domains. PhD in Environmental Engineering, Instituto Superior Técnico, University of Lisbon (2011) MSc and BSc in Environmental Engineering, Instituto Superior Técnico (1999) Graduate Certificate in Learning and Teaching in Higher Education Fellow of the Higher Education Academy (UK, 2018) Ana Horta’s research centers on spatial modeling, geostatistics, GIS, and machine learning for environmental and health applications. She specializes in spatiotemporal data analysis, uncertainty assessment, and digital soil mapping. Her work addresses pressing issues such as soil-water balance, habitat fragmentation, food environment accessibility, and water resource management. She integrates advanced statistical methodologies with remote sensing and drone-based imagery to deliver actionable insights. Her recent publications reflect a strong trend toward interdisciplinary research, particularly at the intersection of geospatial science and public health. Themes include food retail accessibility in rural Australia, river connectivity in Indonesia, and national-scale soil salinity assessment in Portugal. These works demonstrate her commitment to solving complex environmental and social challenges using geospatial analytics. Charles Sturt Executive Deans Awards for Teaching (2022) John Harper Memorial Award (2022) Fellow, Higher Education Academy (UK, 2018) Geoderma’s Best Review Award (2015) Successful grant recipient: Australian Water Partnership (2022) Keynote speaker and workshop participant in international forums Editorial Board Member, Geoderma Ana has supervised nine Honours and two PhD students to completion and continues to mentor early-career researchers. She has secured competitive research grants, including a major project on capacity development in spatial planning for water resources in Indonesia. Her teaching innovations have been recognized with university-level awards, reflecting her impact on student engagement and job readiness. She actively collaborates with national and international institutions and contributes to policy through public-facing research and media engagement. Ana leads research within the Gulbali Research Institute and collaborates with the Inland Fisheries Research Group. She is involved in multidisciplinary teams focusing on environmental monitoring, water security, and rural health. Her lab activities emphasize applied geospatial modeling, often involving drone data, satellite imagery, and community-based participatory design.

• Geodesy
• Very Long Baseline Interferometry (VLBI)
• Satellite Geodesy
• +3 more

David Schunck serves as a Research Fellow in Geodetic VLBI within the School of Natural Sciences at the University of Tasmania. His position is dedicated to advancing Very Long Baseline Interferometry for geodetic applications, particularly within the VLBI Global Observing System (VGOS) framework and its integration with satellite navigation systems. Dr. Schunck's research centers on geodetic VLBI, satellite geodesy, and reference frame realization techniques. Key focus areas include GNSS signal observation using VGOS arrays, simulation of VLBI observations to navigation satellites (BeiDou/Galileo) for frame ties, and radio telescope deformation analysis. His work directly contributes to improving global geodetic infrastructure and Earth orientation parameter determination accuracy. Analysis of Schunck's publication record (2017-2025) reveals consistent progression in VLBI technology for geodesy. Recent work (2024-2025) prioritizes VGOS operations, including GNSS signal observation and GENESIS mission integration. Earlier publications cover satellite simulation for frame ties and radio telescope metrology. While geodetic VLBI remains his core expertise, interdisciplinary collaborations appear in plant phenotyping (2021) and urban mobility analysis (2018). Mr. Schunck operates within an international geodesy collaboration network involving institutions engaged in VGOS and GENESIS projects. His research leverages global geodetic observing systems and advances space geodesy through multi-institutional partnerships focused on infrastructure development and observational innovation.