Professor Anton Van Den Hengel is a leading academic at the University of Adelaide, serving as Director of the Centre for Augmented Reasoning and Chief Scientist at the Australian Institute for Machine Learning (AIML). He has held prestigious roles including Chief Investigator at the NHMRC Centre of Research Excellence on Healthy Housing, Fellowships at the Australian Academy of Technology and Engineering and the Royal Society of South Australia, and previously as Director of Applied Science at Amazon Australia. His research focuses on solving complex vision and language problems, image-based modeling, and semantic reconstruction, with significant impacts across computer science and AI. He has secured over $80 million in research funding from global entities like Google, Facebook, and the ARC. Scientific Awards & Honors: 2021 Australasian AI Outstanding Service Award Pearcey Foundation Entrepreneur Award SA Science Excellence Award for Research Collaboration CVPR Best Paper Prize (2010) CORE Academy Election (2025) With over 440 publications and an h-index of 89, Professor van den Hengel has commercialized 8 patents, founded 5 startups, and achieved FDA approval for a medical technology. He plays a pivotal role in advancing Australia’s AI research landscape through the AIML and CAR.
George Cairns is a Senior Lecturer at RMIT University's Centre of Sustainable Organisations and Work, with over two decades of academic contributions at the intersection of scenario analysis , critical management studies , and international business ethics . His work combines design thinking with organizational theory to explore futures in unpredictable environments. Research interests include postdichotomous frameworks for organizational analysis, critical scenario methods for policy and business contexts, and ethical dimensions of globalization . He has authored influential texts on scenario planning and co-developed methodologies like the Augmented Critical Scenario Method with George Wright. His 15 most recent publications (2011-2019) demonstrate sustained engagement with strategic foresight (7 articles), critical international business (5 articles), and design-informed organizational analysis (3 articles), revealing a trajectory from stakeholder behavioral modeling to postnormal epistemologies in management research. Collaborations with scholars like George Wright , Martyna Sliwa , and Ron Bradfield underscore his role in developing critical scenario theory as both academic practice and interventionist methodology.
Steven Allender is a Deakin Distinguished Professor at Deakin University's School of Health and Social Development within the Faculty of Health. He serves as founding Director of the Global Centre for Preventive Health and Nutrition (GLOBE), a World Health Organization Collaborating Centre, and leads the Institute for Health Transformation. His work spans public health, epidemiology, and nutrition with focus on chronic disease prevention through systems thinking approaches. Professor Allender holds a PhD from the University of Ballarat. His research focuses on solving complex public health problems, particularly the burden of chronic disease, malnutrition, and climate change impacts in both developed and developing countries. He pioneers community-based interventions using complex systems approaches, with significant emphasis on obesity prevention, food retail environments, and health equity. His methodology integrates systems thinking, implementation science, and community engagement to address structural determinants of health. His recent publications demonstrate strong trends in applying systems thinking to obesity prevention (12 of 15 recent articles), with growing emphasis on climate change-health interactions (3 articles), food retail policy (5 articles), and health equity measurement (4 articles). The work increasingly employs community co-design, implementation research, and sophisticated evaluation methodologies including RCTs and meta-analyses. Consultant, Prevention, Health Policy and Epidemiology Section, European Association for Cardiac Prevention and Care (2010) Honorary Membership, Faculty of Public Health, Royal College of Physicians, UK (2009) World Heart Federation Fellowship in Cardiovascular Epidemiology (2006) Nominated Future Leader, Deakin University Developing Research Leaders Program (2010) Multiple Merit Awards from University of Oxford for outstanding research contributions Professor Allender actively supervises 5 current doctoral students while having completed 17 PhD supervisions, focusing on community action, climate change health impacts, obesity prevention, and mental wellbeing. He has secured over $10 million in competitive grant funding including major NHMRC Partnership Projects, CREs, and international grants from NIH and EU bodies. His current leadership includes the NHMRC TCR on Commercial Determinants of Aboriginal Health ($1.5M), the RE-FRESHING CRE ($2.5M), and the STAIR obesity prevention trial ($1.4M). He maintains significant community partnerships through VicHealth contracts and local government collaborations across rural Victoria. He leads the Global Obesity Centre (GLOBE) as a WHO Collaborating Centre, directing research teams focused on systems approaches to obesity prevention, food retail environments, and climate change-health interactions. His work engages multiple stakeholders including local governments, health services, and international organizations through the World Heart Federation and European Association for Cardiovascular Prevention.
Dr. Kasun De Silva Wijayaratna is a Senior Lecturer in the School of Civil and Environmental Engineering at the University of Technology Sydney (UTS), with over 14 years of combined industry and academic experience in transport engineering and research. His work focuses on practical applications across network modeling, traffic management, parking systems, and car-sharing solutions, making significant contributions to understanding transport network reliability and vulnerability. His educational background includes: PhD in Civil Engineering (Transport Modelling) from the University of New South Wales (2016) Bachelor of Engineering (Civil Engineering, Honours 1) from the University of New South Wales (2011) Bachelor of Commerce (Finance with Distinction) from the University of New South Wales (2011) Dr. Wijayaratna's research primarily investigates travel behavior under different information scenarios, with particular emphasis on shared spaces, personalized mobility solutions, and transport network reliability. His recent work demonstrates a strong focus on integrating AI and big data analytics into transport modeling, examining pandemic impacts on mobility patterns, and developing innovative approaches to shared road infrastructure. His publications reveal a consistent trajectory toward more sophisticated modeling techniques and increasingly complex real-world applications. His scientific achievements include the prestigious 2016 SIDRA Solutions Postgraduate Award as the most outstanding transport engineering researcher in Australia and New Zealand, along with multiple research funding successes totaling over $1.5 million from state and local government sources. He has secured significant grants through iMOVE CRC and Transport for NSW for projects examining shared spaces, transport system optimization, and road safety innovations. As an educator, Dr. Wijayaratna serves as subject coordinator for Roads and Transport Engineering and Traffic and Transportation courses at UTS. He has been recognized as an innovator in tertiary education for developing blended learning approaches that effectively engage contemporary student cohorts. His teaching philosophy integrates practical industry experience gained during his time at Cardno with academic rigor, creating a dynamic learning environment that prepares students for real-world transport engineering challenges.
Irene Yang is a Lecturer in Engineering Mathematics at Swinburne University of Technology, Sarawak's Faculty of Engineering, Computing and Science. Holding dual degrees from the University of Science Malaysia (BScEd Mathematics and MSc Teaching of Mathematics), she brings extensive expertise in technological innovation for STEM education. Education: Master of Science (Teaching of Mathematics), University of Science Malaysia Bachelor of Science in Education (Mathematics), University of Science Malaysia Her research pioneers screencast video applications in engineering mathematics education, examining how student-produced content transforms learning engagement. Current investigations focus on blended learning frameworks where learners create explanatory videos for complex optimization problems, turning abstract concepts into tangible digital artifacts that enhance peer-to-peer knowledge construction. Publication trends reveal consistent focus on technology-mediated pedagogy since 2014, with recent work analyzing perception data from video-based interventions. Her scholarship bridges educational theory and classroom practice, emphasizing measurable learning outcomes through innovative assessment methods in mathematics education. Awards and Recognition: Highly Commended, Swinburne Teaching Excellence Award (2020) Best Paper Award, Taylor's Teaching Conference (2016) Dual Shortlistings, Wharton-QS Reimagine Education Awards (2015) Malaysian Mathematical Science Society membership Funded by Swinburne Sarawak Research Grants, her projects involve collaborative classroom research with engineering students as co-investigators. She mentors future educators through hands-on technology integration projects, maintaining active supervision of undergraduate research while developing scalable video pedagogy models for STEM disciplines. Her international conference presentations demonstrate commitment to global educational advancement. Though not leading a formal laboratory, she cultivates dynamic classroom research environments where teaching innovations become publishable scholarly contributions. Her approach transforms traditional mathematics instruction into interactive digital experiences, positioning students as knowledge creators within engineering education ecosystems.
Dr. Tay Fei Siang serves as Senior Lecturer and Head of the Department of Robotics and Mechatronics Engineering at Swinburne University of Technology Sarawak Campus within the Faculty of Engineering, Computing and Science. Joining in 2013 as Associate Lecturer, he earned promotion to Senior Lecturer in 2021 while demonstrating leadership in both academic administration and research innovation. His academic credentials include: BEng (Hons) in Electrical and Computer Systems Engineering from Monash University, Australia (2008) PhD in Engineering from Swinburne University of Technology, Australia (2013) focusing on 'Sliding mode learning control for complex systems with dynamic fuzzy models' Dr. Tay's research bridges theoretical control engineering with practical applications across three interconnected domains: intelligent control systems for complex machinery, smart farming technologies addressing agricultural challenges, and wireless communications solutions for rural infrastructure. His work consistently targets Sarawak-specific problems, such as developing cost-effective internet deployment models for remote communities and creating sensor-based systems for precision agriculture. This applied approach transforms theoretical concepts into tangible community benefits while advancing engineering knowledge. Analysis of his 15 most recent publications reveals a strategic evolution from pure control theory (2014-2017) toward interdisciplinary applications (2018-2022), with 70% focusing on smart farming and rural telecommunications. His collaborative approach is evident in co-authorship patterns spanning agricultural science, healthcare technology, and civil engineering domains. Key recognitions include: Swinburne Vice-Chancellor Award 2019 (Community Engagement – Team) Innovation and Technology Expo 2019 dual awards (Gold/Silver) IEM-UTM InvecMax Competition 2021 First Runner Up (as Main Advisor) Innovate Malaysia Sarawak Edition 2022 First Prize in Electronic and IoT Track Dr. Tay actively mentors postgraduate researchers while managing externally funded projects including the Sarawak Digital Economy Research Grant 2019 ('Feasibility study on rural digital infrastructure') and SRDC 2020 grant ('Treated local marine sand in construction'). His supervision style emphasizes real-world problem solving, with students contributing to publications in IEEE transactions and international conferences. Current research directions focus on IoT-enabled agricultural systems and sustainable rural connectivity solutions. Though no dedicated lab name is specified, Dr. Tay leads research groups developing smart irrigation systems, vertical farming monitors, and light-based pest traps, frequently collaborating with Sarawak-based industry partners to ensure practical applicability of研究成果. His work exemplifies engineering solutions tailored to regional needs while maintaining academic rigor.
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.
Christopher Drovandi is a Professor at Queensland University of Technology and a Chief Investigator in the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). His research spans statistical methodology development and applications across diverse fields including ecology, biomedicine, and environmental science. Dr. Drovandi's primary research interests focus on advancing Bayesian statistical methods, particularly in the areas of: Approximate Bayesian Computation (ABC) and likelihood-free inference Synthetic likelihood methods Sequential Monte Carlo algorithms Bayesian experimental design Statistical computing for complex models His recent work demonstrates a strong emphasis on addressing model misspecification in Bayesian inference, developing robust computational methods for intractable likelihoods, and applying advanced statistical techniques to solve real-world problems in ecology, biomedicine, and environmental science. Drovandi has made significant contributions to both the theoretical foundations and practical applications of modern Bayesian statistics. Dr. Drovandi has received research funding through multiple Australian Research Council grants and collaborates extensively with researchers across disciplines. His work has been published in top-tier statistical and interdisciplinary journals including the Journal of the American Statistical Association, Bayesian Analysis, and PLOS Computational Biology.
