Guodong Shi is Associate Professor at the University of Sydney's Australian Centre for Robotics, heading the Centre for Robotics and Intelligent Systems. His research develops theoretical frameworks for multi-agent coordination, distributed optimization, and networked control systems. Current projects investigate collective decision-making under information constraints, privacy-preserving optimization, and game-theoretic formulations for social and robotic networks. His group develops algorithms for distributed solution of linear equations, Boolean networks, and equilibrium seeking. Doctoral supervision includes projects on acrobatic legged robots, reinforcement learning for robotic stability, and safe control under dynamic environments. Laboratory capabilities support theoretical and experimental validation. Research has applications in autonomous swarm robotics, smart grid optimization, and social network analysis. Teaching includes graduate courses on networked systems and optimization.
Professor Eduardo Velloso is an academic staff member at the School of Computer Science , University of Sydney . He is a member of the Centre for AI Trust and Governance and holds a PhD in Computer Science from Lancaster University and a Bachelor of Computer Engineering from Pontifical Catholic University of Rio de Janeiro. Teaches COMP4447/5047 - Pervasive Computing and INFO1111 - Computing Professionalism Research Interests focus on distributed collaboration in mixed reality , human-AI interaction , and HCI theory and methodology . His work integrates Engineering, Design, and Psychology to explore gaze interaction, adaptive agents, and multimodal interfaces. Key projects include Blended Whiteboard for remote MR collaboration and GazeGrip for mobile accessibility. Publication Trends show expertise in Virtual Reality , Mixed Reality , and Human-AI Interaction , with recent work on Algorithmic Recourse and Immersive Educational Tools . Awards include ACM Best Paper Awards at CHI, UIST, TOCHI, and DIS venues. Scientific Awards 2024 ACM CHI & DIS Honorable Mentions 2022 UoM-FEIT Teaching & Learning Award 2019 UoM-CIS Excellence in Research Award 2015 ACM UIST Best Paper Award Advising includes supervision of research students Marvin, Tinghui LI, and Wendi YU in projects on asynchronous MR collaboration , situationally-induced impairments , and physical environment integration . His lab explores AI-assisted interaction and context-aware computing through projects like SpinalLog and LiftSmart .
Dr. Mohamed Khalifa is a Visiting Fellow at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney. He holds a PhD in Health Innovation from Macquarie University (2020) and an MSc in Health Informatics from the University of Edinburgh (2012). His expertise spans health informatics, AI-driven healthcare solutions, and strategic healthcare management. He has led multidisciplinary teams in developing evidence-based frameworks like GRASP for clinical predictive tools. Affiliations: Visiting Fellow, Macquarie University Director of Studies, College of Health Sciences (Education Centre of Australia) Former Digital Health Officer, Australian Digital Health Agency (2020–2021) His research focuses on AI applications in healthcare, clinical decision support systems, and health analytics. Over 20 years, he has published 60+ peer-reviewed papers and holds an innovation patent (2018). He has received awards including the IMIA Best Paper (2020) and ICIMTH Best Paper (2015). Dr. Khalifa’s work emphasizes improving healthcare efficiency through technology, including projects on predictive tools, emergency room performance, and diabetes management. He is a Fellow of the Australasian Institute of Digital Health and certified in healthcare information systems (CPHIMS).
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.
David Henderson is the Director of the Cyclone Testing Station (CTS) in the School of Engineering and Physical Sciences at James Cook University, Australia. He has over two decades of experience as a research engineer specializing in the performance of low-rise buildings under extreme wind conditions. He previously served as the CTS Research Fellow and Manager, and was seconded as a Postdoctoral Researcher at the University of Western Ontario, Canada, working on full-scale house testing under simulated wind loads. His work bridges engineering research, disaster assessment, and policy development. David's research focuses on wind engineering, structural resilience, and disaster mitigation. His key interests include cyclonic wind loading, internal and external pressure dynamics in buildings, fatigue failure of structural connections, and the vulnerability of housing to severe wind events. He has conducted post-disaster surveys across Australia and Canada, assessing damage from cyclones, tornadoes, and earthquakes. His research has direct applications in building codes, retrofitting strategies, and community risk reduction. The recent publications highlight a strong trend in understanding and mitigating wind-induced damage to residential structures, particularly through full-scale testing, modeling of pressure dynamics, and fragility assessment of roofing systems. His work spans experimental, theoretical, and policy-oriented domains, with a growing emphasis on climate change adaptation and community resilience. Topics such as internal pressure design, load sharing in roof frames, and retrofitting for wind resistance are central to his contributions. 14 research awards (specific names not listed) Active member of Standards Australia code committees Invited speaker at national and international conferences Media contributor on storm damage and building safety David has led multiple research projects funded by councils and agencies focused on extreme wind mitigation, data systems (SWIRLnet), and community risk reduction. While formal student supervision is not explicitly listed, he collaborates extensively with researchers such as John Ginger, Korah Parackal, and Daniel Smith. He has contributed to major studies involving wind load testing, housing vulnerability modeling, and climate adaptation planning. David is a key figure in the Cyclone Testing Station, leading its full-scale testing program and contributing to the development of software for controlled load and measurement systems. His team conducts wind risk assessments for communities and large installations, incorporating terrain analysis and retrofitting evaluations. The CTS serves as a national resource for wind engineering research and disaster resilience innovation.
Kwan-Wu Chin is a Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong, where he also serves as Head of Postgraduate Studies (HPS) and co-directs the Wireless Technologies Lab (WTL). His research focuses on resource allocation problems in Internet of Things (IoT) systems, maritime networks, edge computing platforms, and integrated sensing-communication systems. Chin leads an active research group currently supervising five PhD students working on UAV networks, edge computing, maritime systems, and metaverse resource allocation. He has graduated over 20 PhD students who now hold positions in academia and industry. Chin serves as editor for Elsevier Computer Communications and IEEE Internet of Things Journal. His work develops optimization techniques using graph theory, stochastic processes, and machine learning for next-generation wireless systems.
Arianto Patunru is a Research Fellow at the Arndt-Corden Department of Economics within the Crawford School of Public Policy at the Australian National University (ANU). He joined ANU in 2012 and holds a PhD from the University of Illinois at Urbana-Champaign. His roles include coordinating the ANU Indonesia Project, overseeing policy engagements such as the Australia-Indonesia High Level Policy Dialogue, and managing the Indonesia Project on COVID-19 initiatives. Patunru previously headed the Institute for Economic and Social Research (LPEM-FEUI) in Jakarta and taught economics at Universitas Indonesia. His research focuses on international trade, economic development, globalization, and policy analysis. He has published in journals like the American Journal of Agricultural Economics , Journal of Development Studies , and Bulletin of Indonesian Economic Studies , where he serves as an editor. Patunru frequently contributes to policy debates through op-eds in platforms like East Asia Forum and The Conversation , addressing issues such as Indonesia’s economic strategy, trade policies, and climate change. Key research themes include the impact of economic reforms (e.g., Indonesia’s Omnibus Law), trade policy dynamics, and the role of foreign investment. He has explored topics like labor share declines in manufacturing, environmental policy challenges, and vaccination strategies during the pandemic. Patunru’s work bridges academic analysis with practical policy advice, emphasizing Indonesia’s integration into global value chains and the need for balanced economic strategies.
Associate Professor Chengguo Zhang is a researcher at the University of New South Wales (UNSW Sydney) specializing in Mining Engineering and Geomechanics . His work focuses on improving mining safety and sustainability through fundamental and applied research on dynamic rock mass failures , groundwater-mining interactions , and data-driven visualization technologies . He currently serves as the Postgraduate Research Coordinator for the School of Mining Engineering. PhD in Mining Engineering from UNSW Sydney (2015) Coordinates postgraduate research programs Recipient of multiple teaching and research awards Research Interests: Zhang's work addresses critical mining industry challenges through: Quantification of energy sources and dissipation in rock masses for rockburst management Integration of AI data analytics and 3D visualization for geotechnical risk assessment Mine subsidence and coupled hydro-mechanical behavior of rock discontinuities Development of digital ground control management systems Article Trends: His recent publications demonstrate expertise in: Numerical modeling of rock fracturing mechanisms Nonlinear fluid flow analysis in fractured rock masses Shotcrete and ground support system evaluation Hydro-mechanical coupling during shear processes Energy-based coal burst risk classification Scientific Awards: Tim Shaw Award for Innovation in Teaching (2024) International Outstanding Young Scholar Award (2023) UNSW Education Excellence Award (2021) UNSW Research Excellence Award (2018) Research Supervision: Supervises 12 active PhD students (9 as primary/joint supervisor) and has guided 11 PhD completions (7 as primary/joint supervisor), including 3 Dean's Award recipients. Focuses on numerical modeling, data visualization, and machine learning applications in mining geomechanics.
Professor Jun Huang is a faculty member in the School of Chemical and Biomolecular Engineering at the University of Sydney, where he holds the rank of Professor and is Director of the Laboratory for Catalysis Engineering. He is also a Domain Leader for Materials at the nanoscale at Sydney Nano Institute and a member of several interdisciplinary institutes, including the China Studies Centre and Sydney Institute of Agriculture. His research focuses on catalysis engineering, with an emphasis on developing sustainable processes for renewable fuels, pollutant treatment, and greenhouse gas mitigation. Huang has held prestigious awards such as the Australia Research Council Future Fellowship (2022) and the Sydney Accelerator Fellowship (2018). Education: Huang earned his PhD from the University of Stuttgart (2008) and completed postdoctoral research at Georgia Institute of Technology and ETH Zurich. He joined the University of Sydney in 2010 as a Lecturer, advancing to Senior Lecturer, Associate Professor, and Professor. Research Interests: Huang's work centers on catalyst design for green chemical processes, including biomass conversion to biofuels, wastewater treatment, and CO2 utilization. He emphasizes sustainable manufacturing and environmental impact reduction through innovative catalytic systems. Current Projects: These include catalytic transformation of hydrocarbons/CO2/biomass, nano-catalysts for renewable energy, and advanced NMR spectroscopy for catalysis analysis. Collaborative projects involve anti-cancer therapies and drug pharmacology studies. Awards: Over 15 awards, including the 2021 ACS Sustainable Chemistry & Engineering Lectureship and 2017 Vice-Chancellor’s Research Excellence Award. Teaching: Huang instructs courses such as CHNG2801 (Conservation Processes), CHNG3802 (Industrial Systems), and advanced chemical engineering topics. He supervises PhD/Master students in catalysis and sustainable engineering. Labs/Teams: Leads the Catalysis Engineering Lab and collaborates with Sydney Nano Institute on nanomaterials research.
Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.
Dr. Huadong Mo is a Senior Lecturer at the School of Systems and Computing, University of New South Wales (UNSW) Canberra, Australia. He holds a B.E. degree in automation from the University of Science and Technology of China (2012) and a Ph.D. in systems engineering and engineering management from the City University of Hong Kong (2016). Prior to his current position, he was a research associate at ETH Zurich's Reliability and Risk Engineering Lab (2016-2019) and a Lecturer at UNSW Canberra (2019-2021). Dr. Mo's educational background includes a strong foundation in systems engineering with international experience across China, Switzerland, and Australia. His career trajectory demonstrates a progression from academic research to faculty positions with increasing responsibilities in teaching and research leadership. His research focuses on enhancing the resilience, performance, and security of complex systems using learning-based algorithms, primarily in power and energy systems, cyber-physical systems, and manufacturing systems. He applies data analytics to understand system evolution under uncertainties, with particular emphasis on prognostics and health management, sustainable transportation, robust operation of power systems under extreme events, and reinforcement learning-based asset management. His work bridges theoretical advances with practical applications in critical infrastructure. Analysis of Dr. Mo's recent publications reveals a strong focus on energy systems, particularly in the integration of machine learning with power grid management, battery storage systems, and resilience against cyber threats. His research shows a clear trajectory toward increasingly complex system integration, with growing emphasis on multi-vector energy communities, cross-domain prediction, and uncertainty-aware energy management. The interdisciplinary nature of his work spans electrical engineering, computer science, and operations research. 2024 IEEE SMC Early Career Award 2023 Visiting Research Fellowship (Jean d'Alembert Pour Fellowship) Gold Medal in 2024 China International College Student Innovation Competition (as supervisor) Arc PGC Supervisor Award (2021) IEEE SMC Outstanding Chapter Award (2021) Alumni Achievement Award from City University of Hong Kong (2019) Dr. Mo actively supervises numerous HDR students working on cutting-edge research topics including battery health monitoring, quantum control, reinforcement learning for power systems, and explainable AI for energy management. He leads multiple significant research grants totaling over 3 million AUD, including projects funded by ARC, Energy Innovation Fund, and international collaborations with institutions like ETH Zurich, Cambridge, and Tsinghua University. His research group maintains strong international connections, facilitating student exchanges and collaborative research. As Postgraduate Course Coordinator of Systems Engineering and Chair of IEEE SMC ACT Chapter, Dr. Mo plays a significant role in academic leadership and professional community building. His research team collaborates with industry partners on practical implementations of their theoretical work, particularly in the energy sector.
Dr. Siqi Ma is a Senior Lecturer at the UNSW Institute for Cyber Security (IFCYBER) within the School of Systems & Computing at the University of New South Wales (UNSW). He previously served as a Lecturer at the University of Queensland's School of Information Technology and Electrical Engineering (ITEE). He holds a Ph.D. in Information Systems from Singapore Management University (2018) and was a Postdoctoral Research Fellow at Data61, CSIRO. He also visited Carnegie Mellon University (CMU) in 2015. Current Role: Senior Lecturer, UNSW Institute for Cyber Security Former Role: Lecturer, University of Queensland Education: Ph.D. (Singapore Management University), Postdoc (Data61, CSIRO) His research spans automated vulnerability detection, mobile security, IoT security, network authentication, and graph-based adversarial robustness. Recent work focuses on drone configuration bugs, Android malware analysis via GNNs, federated learning privacy, and credential leakage in open-source projects. Key trends in his 2024-2025 publications include automated security analysis for embedded systems, deepfake detection in multimedia, and privacy-preserving mechanisms for distributed networks. He collaborates with institutions like Purdue University, Singapore Management University, and CSIRO Data61.
Dr. Daniel Preston is an ARC DECRA Fellow and leader of the Preston Group at the Research School of Chemistry , Australian National University. His research focuses on supramolecular chemistry, designing structurally and functionally complex architectures from metal ions and organic ligands in solution. Education : PhD in Chemistry from the University of Otago, Rutherford Postdoctoral Fellowship at the University of Canterbury (NZ). Key research themes include: Supramolecular self-assembly of metallosupramolecular systems Development of stimuli-responsive foldamers and sensors Photophysical applications in FRET, donor-acceptor systems Anion recognition and gas adsorption studies His recent publications highlight work on: Low-symmetry metal cages (Fe 2+ , Pd 2+ , Pt 2+ ) Dynamic covalent approaches to lantern-shaped architectures Excited state control in bichromophoric photosensitizers Heterometallic and heteroleptic systems with positional/orientational control Scientific Awards : ARC DECRA Fellow ARC Future Fellow Rutherford Postdoctoral Fellowship Dr. Preston supervises PhD candidates Jessica Algar and Zack Avery, with active projects in mixed-metal clusters, self-assembled systems, and molecular machine development.
Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.
Renate Egan is a Professor and Deputy Head of School (Engagement) at the School of Photovoltaics and Renewable Energy Engineering , University of New South Wales (UNSW). She leads UNSW's activities in the Australian Centre for Advanced Photovoltaics , a national research consortium involving multiple Australian institutions. Her research focuses on: Techno-economic analysis of photovoltaic technologies Energy data analytics for decentralized systems Electricity market restructuring Technology transfer and commercialization Recent work examines machine learning applications in energy demand forecasting, thermal storage optimization, and bushfire resilience. She collaborates extensively across academia, industry, and government sectors. Key affiliations include: Co-Founder of Solar Analytics (Australia's largest independent energy monitoring provider) Executive Committee member of the IEA PV Power Systems program
