Shoudong Huang is a Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney, and Deputy Director of the UTS Robotics Institute. His research focuses on mobile robot navigation , SLAM , nonlinear state estimation , and surgical robotics . He has published over 200 papers and is recognized as one of the 100 Most Influential Scholars in Robotics (Aminer, 2018). PhD in Automatic Control, Northeastern University (China) Postdoctoral Research Fellow, University of Hong Kong (1998-2000) Research Fellow, Australian National University (2001-2003) Full-time academic roles at UTS since 2004 His work addresses challenges in robot localization across extreme environments (underwater, underground mining, surgical settings) and develops globally optimal SLAM algorithms with guaranteed performance. He has secured over $4 million AUD in external funding, including ARC Discovery grants and industry partnerships. Recent publications emphasize cross-modal calibration (camera-LiDAR), interval analysis for bounded noise , and template-based deformable surface reconstruction . These span applications in autonomous driving, surgical navigation, and UAV guidance. Chancellor’s Medal for Research Excellence (2020) Supervisor of the Year (2023) Best Paper Award (2016 ICARCV) Huang serves as Associate Editor for IEEE Transactions on Robotics and International Journal of Robotics Research , and has held leadership roles in top robotics conferences like IROS and RSS. His collaborations span MIT, USC, Zhejiang University, and industry partners including PMSW Research Pty Ltd and Multiplex Constructions Pty Ltd.
Dr. James McDonald serves as a Lecturer and Research Fellow at the University of New South Wales (UNSW) within the School of Civil and Environmental Engineering's Water Research Centre (WRC). His work at the Vallentine Annexe (H22), Room 102, Kensington Campus focuses on advancing water treatment technologies and understanding contaminant behavior in water systems. His position bridges academic instruction with cutting-edge research in environmental engineering. McDonald's research spans multiple critical areas in water science and engineering, with particular emphasis on trace organic contaminants, membrane technologies, and advanced water treatment processes. His work investigates the fate and removal of pharmaceuticals, personal care products, and industrial chemicals in various water treatment systems. He has made significant contributions to understanding disinfection by-product formation, chiral inversion of pharmaceuticals, and the development of novel membrane technologies for improved water purification. His research combines experimental approaches with computational modeling to address complex water quality challenges. Analysis of McDonald's recent publications reveals a strong focus on emerging contaminants, particularly PFAS compounds and chiral pharmaceuticals, and their behavior in water treatment systems. His work demonstrates expertise in both conventional and advanced water treatment technologies, with increasing emphasis on sustainable approaches including green infrastructure and novel membrane processes. The interdisciplinary nature of his research connects environmental engineering, chemistry, microbiology, and materials science to address contemporary water quality challenges. McDonald actively collaborates with researchers across multiple institutions and has contributed to numerous significant studies on water quality and treatment. His work supports the development of more effective water recycling systems and safer drinking water supplies. While specific grant information isn't detailed in the available text, his extensive publication record suggests sustained research funding in water treatment technologies and contaminant fate studies. As part of UNSW's Water Research Centre, McDonald contributes to one of Australia's leading water research facilities. The WRC provides a collaborative environment for addressing complex water challenges through interdisciplinary research that integrates engineering, chemistry, and environmental science perspectives.
Renjie Feng is a Research Fellow in Mathematics and AI at the School of Mathematics and Statistics and the Sydney Mathematical Research Institute , University of Sydney. His work bridges probability theory, statistics, and applications in machine learning, deep learning, and artificial intelligence. His research interests focus on probability theory and its applications to machine learning , random matrix theory , and statistical physics . He investigates extreme value problems, spectral properties of random matrices, and topological features of random fields over Riemannian manifolds. Recent publications highlight trends in random matrix theory (GUE, GOE, GSE), extreme gap problems , determinantal point processes , and Wiener chaos . Collaborative works with F. Götze, D. Yao, and R. Adler emphasize U-statistics , multivariate linear statistics , and random topology inspired by Poisson point process studies.
Lexing Xie is a Professor in Computer Science at the Australian National University. He leads the ANU Computational Media Lab ( http://cm.cecs.anu.edu.au ) and the ANU Integrated AI Network. His work focuses on the intersection of machine learning, social media analysis, and multimedia understanding. Dr. Xie's research broadly focuses on innovative design and use of machine learning algorithms, especially on large-scale graph data and collective behaviour. His recent work spans several key areas: Popularity in social media -- understanding, predicting, and optimization Multimedia knowledge graphs, vision and language integration Humanising machine intelligence through better understanding of social dynamics His publications reveal a strong trend toward understanding information diffusion patterns in social media, particularly through visual content. He has made significant contributions to the study of visual memes, popularity prediction using point processes, and multimodal learning that connects vision with language. His work often bridges theoretical machine learning with practical applications in social media analysis. Dr. Xie has received recognition for his research, including an Honourable Mention at CSCW 2019 for his work on attention flow in online video networks. His research has been supported by collaborations with major institutions including IBM Research and Columbia University. As an advisor, Dr. Xie has mentored numerous students who have gone on to contribute significantly to publications in top-tier conferences. His lab, the ANU Computational Media Lab, serves as a hub for interdisciplinary research connecting computer science with social sciences.
Deborah Fox is Associate Professor in Midwifery at the University of Technology Sydney (UTS), Faculty of Health, and a core member of the Centre for Midwifery, Child and Family Health. She serves as Co-lead of the Maridulu Budyari Gumal SPHERE Maternal and Women's Clinical Theme and Chair of the National Publicly Funded Homebirth Consortium. In 2024, she received the Faculty of Health Dean's Academic Excellence Award for Research (Mid Career Researcher), following her 2021 award as Highest Performing Early Career Researcher from the School of Nursing and Midwifery. Her research focuses on optimizing physiological processes and positive experiences for women with complex pregnancies, with particular emphasis on the mediation of technology in midwifery practice. Current projects include evaluation of non-invasive fetal ECG beltless and wireless fetal monitoring in labor and birth, and examining the social, economic and environmental impacts of telemonitoring and telehealth in pregnancy and postpartum care. Dr. Fox's scholarly work demonstrates consistent focus on technology's role in maternity care, women's experiences of monitoring during labor, and innovative approaches to midwifery practice. Her recent publications show increasing emphasis on digital health solutions, AI applications in women's health, and pandemic impacts on maternal care systems globally. Faculty of Health Dean's Academic Excellence Award for Research (Mid Career Researcher) 2024 Highest Performing Early Career Researcher award from School of Nursing and Midwifery 2021 Editorial Board Member, Women and Birth journal Dr. Fox is actively involved in higher degree research supervision and has developed innovative teaching resources, including an Objective Structured Clinical Examination for perinatal mental healthcare. She is scheduled to spend three months as a Visiting Scholar at the University of Oxford in 2025.
Professor Scott Sisson is Director of the UNSW Data Science Hub (uDASH) and Professor of Statistics and Data Science at the University of New South Wales, School of Mathematics and Statistics. His research focuses on computational statistics, particularly solving 'intractable' statistical problems through Bayesian methods, big data techniques, simulation algorithms, and extreme value theory with environmental applications. Education includes a PhD in Statistics from Bristol University (2002), MSc in Environmental Statistics from Lancaster University (1997), and BSc in Mathematics and Statistics from Lancaster University (1996). Research interests span: Bayesian statistics and uncertainty quantification Big data analytics and scalable algorithms Machine learning integration with statistical methods Extreme value modeling for climate/environment Computational techniques for intractable problems Recent publications (2022-2025) demonstrate strong emphasis on Bayesian computation, spatiotemporal modeling, and interdisciplinary applications in materials science, oncology, quantum computing, transportation policy, and ecology. Methodological innovations include likelihood-free inference, modular Bayesian analyses, and symbolic data modeling. Awards and honors: 2020 Service Award (Statistical Society of Australia) 2017 ARC Future Fellowship 2015 G. N. Alexander Medal (Engineers Australia) 2011 Moran Medal (Australian Academy of Science) 2010 J.G. Russell Award (Australian Academy of Science) 2010 Queen Elizabeth II Research Fellowship As Director of uDASH, he leads data science initiatives across UNSW. He maintains sustained ARC funding and supervises students in computational statistics, Bayesian methods, extreme value theory, and machine learning. Professional service includes editorial roles for Statistics and Computing and past presidency of Statistical Society of Australia.
Dr. Ly Fie Sugianto is an Associate Professor in the Department of Accounting at Monash Business School, Monash University. Her research focuses on the integration of data analytics, artificial intelligence, and machine learning in accounting and business systems, with applications in the energy sector and organizational behavior. Monash Business School, Monash University Department of Accounting Specialization: Accounting Information Systems, Data Analytics, AI Her research interests span Accounting Information Systems , Agent-Based Simulation , Decision Support Systems , and Technology Adoption . She applies computational methods to study competitive dynamics in deregulated electricity markets and the impact of digital tools on employee well-being and organizational resilience. The recent publications reflect a strong trend in using AI and simulation to analyze complex socio-technical systems, particularly in energy markets and leadership dynamics. Keywords across her work include agent-based modeling , data analytics , servant leadership , and enterprise social media , indicating interdisciplinary research at the intersection of information systems, management, and public policy. Her scientific awards include competitive grants from the ARC (SPIRT/Linkage) , the Australia Indonesia Governance Research Partnership (AIGRP) , and the Sumitomo Foundation . ARC Grant: Dispatch Optimisation in the Australian National Electricity Market Sumitomo Foundation: Technology Use and Employee Well-Being AIGRP: Governance and MSME Resilience during Pandemic Dr. Sugianto has advised research projects and collaborated with industry partners such as Western Power , Ecogen Energy , and AEMO . She is currently accepting PhD students and leads externally funded research initiatives. Her work contributes to UN Sustainable Development Goals related to industry innovation and responsible consumption. She is affiliated with research teams focusing on intelligent decision support systems and digital transformation in business , with active collaborations in Australia and Indonesia.
Professor Jianhua Guo is a faculty member at The University of Queensland (UQ), holding the position of Professor and UQ Amplify Fellow in the Australian Centre for Water and Environmental Biotechnology (ACWEB). He is also the ACWEB Deputy Director - Research. His research focuses on integrating process engineering, environmental microbiology, and biotechnology to develop sustainable solutions for contaminant removal in water and wastewater systems. He is a pioneer in studying the environmental dimension of antimicrobial resistance (AMR), particularly how non-antibiotic pharmaceuticals and chemicals contribute to AMR spread. His groundbreaking work has been featured in over 100 media outlets and has secured over $14M in research funding. He has published over 200 peer-reviewed articles in journals like Nature Microbiology , Water Research , and Environmental Science & Technology . His accolades include the 2013 DECRA and 2017 ARC Future Fellowship. He serves as an editor for Journal of Hazardous Materials and Water Science & Technology . Research Interests Environmental AMR and microbial ecology Methane-based biotechnology and bioconversion Nitrogen cycling microorganisms Bioremediation and biofilm reactors Microplastics and health risks Wastewater treatment innovations Grants & Funding $14M+ in ARC Discovery/Linkage grants and industry partnerships ARC Training Centre for Environmental and Agricultural Solutions to Antimicrobial Resistance (CEA-StAR) Dual-membrane upgrading and anaerobic alkane oxidation projects Awards 2013 DECRA 2017 ARC Future Fellowship Supervision Prof. Guo actively supervises PhD and master’s students in areas like AMR mitigation, methane-based bioreactors, and microbial ecology. Notable supervised projects include studies on antibiotic resistance in wastewater, novel disinfection processes, and microbial oxidation of gaseous alkanes. Labs & Teams He leads research teams within ACWEB and collaborates with the Queensland Alliance for Environmental Health Science. His lab focuses on cutting-edge technologies like membrane biofilm reactors and gas fermentation systems.
Professor Ernest Foo is a distinguished academic at Griffith University's School of Information and Communication Technology, specializing in cybersecurity with a focus on industrial control systems and cryptographic protocols. With over 15 years of experience in computer networking, he has established himself as a leading expert in SCADA security and smart grid cybersecurity. His research has significant practical applications in critical infrastructure protection, and he has developed hands-on security training programs that have trained professionals from major Australian utilities and government agencies. Professor Foo's educational background includes: Bachelor of Engineering with Honours in Electronic and Computer Engineering from University of Queensland Doctor of Philosophy from Queensland University of Technology Professor Foo's research interests center around secure cryptographic protocols with specific applications in industrial control system security and cyber physical systems. His work spans SCADA security, smart grid protection, wireless sensor network security, and post-quantum cryptography. He has made significant contributions to understanding vulnerabilities in industrial protocols like Modbus and DNP3, and has pioneered the application of process mining and data mining techniques for attack detection in critical infrastructure systems. His research bridges theoretical security concepts with practical implementations in real-world industrial environments. Professor Foo's recent publications demonstrate a clear trajectory toward increasingly sophisticated security frameworks for critical infrastructure. His work shows a progression from foundational SCADA security research to advanced applications of artificial intelligence, machine learning, and formal methods in cybersecurity. A notable trend is the integration of zero trust principles with industrial control systems, alongside growing emphasis on post-quantum cryptographic solutions. His publications span high-impact journals and conferences in cybersecurity, with increasing focus on anomaly detection in cyber-physical systems and the application of graph-based machine learning techniques to network security challenges. Professor Foo's notable scientific achievements include: Best paper award at the 2nd International Cyber Resilience Conference for "Gap analysis of Intrusion Detection in Smart Grids" Professor Foo has secured significant research funding including an ARC Linkage grant with Powerlink Queensland focused on cyber security for electricity sub-stations. He currently leads multiple research projects including Westpac Micro-Credentials in Financial Crime Investigation, Digital Banking Micro-credentials with ANZ, and research on quantum-safe cryptography. As a dedicated educator, he serves as Program Director for multiple cybersecurity programs including the Master of Cyber Security, and has supervised numerous doctoral and masters students. His Cyber Security: Industrial Control System course, conducted annually from 2013-2018, featured innovative hands-on training with real-world participants from major Australian utilities. Professor Foo has been instrumental in establishing the SCADA security research laboratory with multiple vendor system miniatures running industrial PLCs. His work bridges theoretical security concepts with practical implementations, making significant contributions to the security of industrial control systems and critical infrastructure worldwide.
Demetris Christodoulou is an Associate Professor in Accounting, Governance and Regulation at the University of Sydney. He holds a BEcon from Piraeus University, an MSc(Fin) from the University of York (UK), and a PhD from Athens University of Economics and Business (AUEB). His research focuses on applying data analytics, econometrics, and visualization techniques to financial analysis, equity valuation, life insurance, and financial advice. He co-directs the PEMA research group, specializing in productivity and performance measurement analytics, and previously led the MEAFA research group (2007–2022). He has collaborated extensively with industry partners including Deloitte and Australian insurers, and developed training programs for over 1,000 executives. His work includes open-source contributions to Stata software and the Graph Workflow platform, alongside $662k in workshop-generated funds supporting academic programs. He has advised multiple PhD students and taught at leading universities globally. Education: BEcon in Economics (Econometrics), Piraeus University MSc in Finance, University of York (UK) PhD in Accounting and Financial Analysis, Athens University of Economics and Business His research interests span financial reporting models, life insurance underwriting strategies, and behavioral finance. Recent projects address dishonesty mitigation in insurance disclosures and the adviser effect on customer disclosures. He has published widely in top journals like the Review of Accounting Studies and Stata Journal , and his work was featured in The Australian for insights on insurance fraud reduction. He maintains international collaborations, including visiting roles at Columbia Business School and the University of Cyprus, and serves on advisory boards for organizations like Behaviour.ai. Publications highlight methodological innovations in econometrics and visualization, with 2025's upcoming Stata Journal paper advancing time-series analysis techniques. His grants include partnerships with industry on longitudinal studies of insured lives, aiming to improve risk modeling and public policy insights.
Prof Christina Lim is a Professor at the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. She serves as the Associate Dean of Research for the Faculty of Engineering and Information Technology (FEIT) and manages the Tucker Lab. Previously, she held roles as Research Group Leader of the Electronics and Photonics System group and Deputy Head of Department (Teaching and Operations) Education: PhD and Bachelors from University of Melbourne Research Interests: Radio-over-Fibre, Optical Wireless Communications, Microwave Photonics, Augmented Reality Displays, Reservoir Computing, Optical Crosshaul Networks Recent publications demonstrate expertise in optical waveguide design for AR, underwater optical wireless communications, photonic switching, and network optimization. Her projects focus on next-generation wireless infrastructure, including Photonics Computing Enabled Ultra-Broadband Wireless Communications (2024-2027, $598k ARC grant) and Additive Manufacturing of Optical Elements (2025). She has secured significant funding, including ARC Discovery Projects and Future Fellowships. Scientific Honors IEEE Fellow (2022) Optica Fellow (2018) ARC Future Fellow (2009-2013) ARC Australian Research Fellow (2004-2008) Professional Service Vice-President of Conferences, IEEE Photonics Society Deputy Editor, IEEE/Optica Journal of Lightwave Technology ARC College of Experts (2014-2016)
Dr. Chandranath Adak is an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Patna (IIT Patna), and concurrently serves as a Visiting Fellow at the School of Computer Science, University of Technology Sydney (UTS), Australia. He holds a Ph.D. in Analytics from UTS (2019) and previously served as an Assistant Professor at Indian Institute of Information Technology Lucknow (IIITL) and the Centre for Data Science at JIS Institute of Advanced Studies, Kolkata. Education: Ph.D. (Analytics), University of Technology Sydney (2019) M.Tech., Computer Science and Engineering, University of Kalyani (2014) B.Tech., Computer Science and Engineering, West Bengal University of Technology (2012) Research Interests: His work spans Computer Vision, Deep Learning, Reinforcement Learning, Document Image Analysis, and AI-driven solutions for healthcare, forensics, and industrial automation. He has pioneered methods in biomarker detection using electrochemical sensors combined with ML models, handwriting analysis for educational and forensic applications, and anomaly detection in industrial systems. His research bridges theoretical advances with real-world applications, such as medical diagnostics and quality control systems. Publications: His recent work includes innovations in biosensor-based medical diagnostics, handwriting evaluation systems, and transformer networks for historical document analysis. These contributions reflect a focus on interdisciplinary applications of AI across healthcare, cultural heritage preservation, and industrial automation. Awards: Start-up Research Grant, SERB, India (2022) Dr. Kalam Doctoral Scholarship, UTS (2018) IEEE CIS Graduate Student Research Grant (2017) Senior Member, IEEE (2024) Teaching & Supervision: Taught courses at UTS including 'Introduction to Data Analytics' and supervised research in machine learning and computer vision. His mentorship emphasizes hands-on experience with AI tools and real-world problem-solving. Labs & Teams: Engaged in collaborative projects at UTS's CIBCI Centre and Griffith University's IIIS, focusing on computational intelligence and sensor-driven AI systems.
Professor Sarath Kodagoda is a leading academic and researcher in robotics and mechatronics at the University of Technology Sydney (UTS), where he serves as Acting Director of the UTS Robotics Institute. He specializes in sensor fusion, data processing, and machine learning, with a focus on robotic solutions for infrastructure inspection and assistive technologies. His work includes developing the Robotic Remote Lab teaching facilities and founding the iPipes lab for wastewater infrastructure research. Affiliations: UTS Robotics Institute, Faculty of Engineering & IT Leadership Roles: President of the Australian Robotics & Automation Association, Ambassador for NSW Smart Sensing Network His research interests span robotics, sensor networks, and infrastructure robotics, with notable contributions to pipeline inspection and tactile sensing. He has published over 170 papers, attracted $6M+ in grants, and supervised 12 PhD students now working at Amazon, Google, and ABB. Awards include the UTS Medal for Teaching & Research Integration and multiple national/international innovation awards. Recent work emphasizes robotic systems for wastewater infrastructure, assistive robotics for vision-impaired individuals, and advanced sensor technologies. His articles highlight innovations in tactile sensing skins, 3D object detection (e.g., CaLiJD, LMIINet), and pipeline defect detection (PIPE-CovNet+). Grants: Contracts with Amplitel, NBN Co Ltd, and ARC Linkage Projects Labs/Teams: UTS Robotics Institute, iPipes Lab
Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.
Dr. Farha Sattar is a Lecturer in Education (Mathematics) at the Faculty of Arts and Society, Charles Darwin University. With over thirty years of teaching experience in Mathematics, Science education, GIS, Remote Sensing, and e-Learning technologies at undergraduate and postgraduate levels, Dr. Sattar brings extensive expertise to her academic role. She holds a PhD in Geospatial Science from Charles Darwin University, focusing on Spatial Mathematical Modelling for 3D Gully Mapping and Erosion Quantification. Her educational background includes: PhD in Geospatial Science (Three Dimensional Gully Mapping and Erosion Quantification within a Geoinformatics Framework), Charles Darwin University (2012) Prior academic experience at several Asian and European universities Dr. Sattar's research spans multiple interdisciplinary fields with a strong focus on the intersection of education and technology. Her primary research interests include Mathematics Education, STEM Education, Geoscience Education, Spatial Mathematical Modelling, Drone Technology, Remote Sensing, Geographic Information Systems, and Innovative Pedagogies such as experiential learning and inquiry-based approaches. She has developed expertise in cognitive development, particularly in fostering critical and creative thinking skills through iSTEM approaches. An analysis of Dr. Sattar's recent publications reveals a consistent trajectory toward integrating emerging technologies like drones, augmented reality, and geospatial artificial intelligence into educational contexts. Her work demonstrates a progression from foundational geospatial research on erosion mapping to innovative applications in STEM education. Recent publications increasingly focus on drone technology for educational purposes, spatial data infrastructure for policy development, and computational thinking development through technology-enhanced learning. Dr. Sattar has received numerous accolades for her contributions to education and research: NT Science Week Awards – Inspired NT STEM Hero of the Year award (2021) Long Service Recognition Award (2023) Finalist, CDU Alumni Award (2023) Multiple Best Presentation Awards (2008, 2010, 2017) Australian College of Educators - 2021 College Medal Nominee As a supervisor, Dr. Sattar mentors postgraduate research students including Ayesha Farhan, who is working on "A Framework for Cognitive Development: Fostering Critical and Creative Thinking Skills, Using iSTEM Approach." She actively secures research funding through various projects such as "DBELaSTEM: Drone-Based Experiential Learning and STEM Education," "STEM_D & VR: Youth STEM Learning and Empowerment with Drones and VR," and "CodProg Drone Lab." Her research is supported by grants from NT Government projects and other external funding sources. Dr. Sattar leads the CodProg Drone Lab, an innovative research space exploring drone technology applications in education. She is a certified drone pilot and aeronautical radio operator, which enables her to bridge theoretical knowledge with practical applications. Her work with the "Flying Forward: Drones, STEM Equity, and Indigenous Empowerment" initiative demonstrates her commitment to community engagement and addressing educational disparities through technology.
