Find Academic Supervisors

Shoudong HuangView profile

Professor

• Mobile robot navigation
• Simultaneous localization and mapping (SLAM)
• Underwater robotics
• +4 more

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.

Ajmal MianView profile

Professor

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +8 more

Ajmal Mian is a Professor of Computer Science at the University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing. He holds an Australian Research Council Future Fellowship (2022) and leads research in Artificial Intelligence, Computer Vision, and Machine Learning. His work focuses on 3D computer vision, adversarial AI defense, and explainable AI. His research interests include 3D point cloud analysis, face recognition, human action recognition, and remote sensing. He has published over 300 papers and secured major grants from ARC, NHMRC, and DARPA, totaling millions in funding. He has supervised 29 PhD students and mentored 12 postdoctoral researchers. Key projects include 3D diffusion models for scene generation, robust 3D vision systems, and defense against AI deception attacks. He serves as a fellow of IAPR, an ACM Distinguished Speaker, and has editorial roles at IEEE Transactions on Neural Networks and Pattern Recognition. Research Awards: HBF Mid-Career Scientist of the Year, West Australian Early Career Scientist of the Year, IAPR Best Scientific Paper Award. Grants: ARC Discovery Projects, National Intelligence & Security Discovery grants, DARPA grants for AI security. His teaching spans computer vision, machine learning, and programming courses. Collaborations include defense, medical, and agricultural applications.

Pieter van GoorView profile

Research Fellow

• Robotics
• Control Theory
• Equivariant Systems Theory
• +5 more

Pieter van Goor is a Research Fellow at the Australian National University (ANU), affiliated with the School of Engineering and the Systems Theory and Robotics (STR) group. He holds a PhD in Control Theory (completed 2022) and dual bachelor's degrees (BEng/BSc, 2018). His research focuses on equivariant systems theory, state estimation, and robotics applications. Key contributions include equivariant observer design, Lie group-based control, and geometric data fusion. Education: Bachelor of Engineering (Research & Development) (Honours) in Mechatronics (ANU, 2018) Bachelor of Science in Mathematics (ANU, 2018) PhD in Control Theory (ANU, 2022) Research Interests: Equivariant systems theory, nonlinear control, robotics applications, state estimation on Lie groups, sensor fusion, and geometric control methods. His work emphasizes symmetry exploitation in filter design and observer construction for systems with inherent geometric structures. Grants & Collaborations: Active collaborations include work with Robert Mahony and institutions like the IEEE. Research spans theoretical frameworks (e.g., equivariant filters) and applied systems (e.g., ArduPilot autopilot, event cameras). Labs/Teams: Member of the Systems Theory and Robotics (STR) group at ANU, focusing on advanced control theory and robotics.

Massimo PiccardiView profile

Professor

• Natural Language Processing
• Computer Vision
• Machine Learning
• +3 more

Massimo Piccardi is a Professor of Natural Language Processing (NLP), Computer Vision, and Machine Learning at the University of Technology Sydney (UTS) , where he has been since 2002. He currently serves as the Head of the School of Electrical and Data Engineering and leads the Big Data Analytics program at the Global Big Data Technologies Centre. His research focuses on advancing NLP, machine learning applications in healthcare, and cybersecurity in IoT systems. He has authored over 200 journal papers and conference proceedings, secured significant ARC and CRC grants, and holds the IEEE Computer Society Distinguished Contributor Award (2022). Education & Professional Roles: Joined UTS in 2002, progressing from Associate Professor (2002–2007) to Professor (2008–present). Serves as Associate Editor for IEEE Transactions on Big Data and Editor for Artificial Intelligence in Medicine. Active in professional societies including IEEE, ACL, and ALTA (President, 2023–2024). Research Interests: Core areas include NLP (translation, summarization, adversarial attacks), healthcare informatics (clinical NLP, health service analysis), and cybersecurity (IoT security, privacy-preserving systems). Cross-cutting themes include generative models, cross-lingual systems, and ethical AI. Grants & Projects: Principal Investigator on ARC Discovery/Linkage projects and CRC grants. Recent projects include controllable machine translation (Amazon), privacy-preserving digital agriculture, and STEM innovation (ASTRID project with NBN Co). Labs & Collaborations: Leads the UTS Global Big Data Technologies Centre, collaborating on projects like adversarial NLP attacks, medical machine translation, and secure IoT frameworks.

• Robotics
• Mechatronics
• Human-Robot Interaction
• +3 more

Mr. Richardo Khonasty is a Senior Research Engineer at the School of Mechanical and Mechatronic Engineering, part of the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He has held appointments at UTS since 2019, including roles at the Centre for Autonomous Systems and Robotics Institute. He also serves as a Tutor since 2016. PhD in Robotics (2020), UTS B.Eng. in Mechanical and Mechatronic Engineering (2014), UTS Khonasty's research focuses on robotics and human-robot collaboration, with applications in surgical robotics (total hip replacement), industrial automation (abrasive blasting), and green wall inspection systems. His work emphasizes kinematic accuracy, adaptive control schemes, and cost-effective robotic solutions. His recent publications explore robotic-assisted burring for orthopedic surgery, damping strategies for singularity management, and exoskeleton design frameworks. Khonasty is currently involved in funded research related to hydraulic tooling safety under the BTP - Stage 2 - IntelliForce Tooling grant.

Wenhua ZhaoView profile

Associate Professor

• Offshore Hydrodynamics
• Renewable Energy Technologies
• Wave-Structure Interactions
• +12 more

Associate Professor Wenhua Zhao is a globally recognized expert in offshore hydrodynamics and renewable energy technologies at The University of Queensland , School of Civil Engineering. With over 110 publications and 30 million AUD in secured research funding, his work bridges theoretical and practical advancements in marine engineering. Research focuses on Clean Energy , Artificial Intelligence , and Climate Change , specifically floating wind energy, floating solar, offshore aquaculture, and green hydrogen production. His 15 most recent articles (2024-2025) emphasize wave-structure interactions, gap resonance dynamics, and AI-driven wave prediction, published in top journals like Journal of Fluid Mechanics and Ocean Engineering . Scientific awards include the prestigious ARC Future Fellowship (2024-2028) and DECRA Fellowship (2019-2022) , recognizing his contributions to academia and industry. He teaches the 'Design of Offshore Energy Systems' course , training hundreds of students in coastal and ocean engineering, and serves as Deputy Editor for Ocean Engineering and Associate Editor for ASME's Journal of OMAE . Available for research supervision, Zhao actively collaborates with editorial boards of Applied Ocean Research and other Q1 journals.

Matthew DunbabinView profile

Professor

• Environmental Robotics
• Vision-Based Perception
• Marine Robotics
• +4 more

Matthew Dunbabin is a Professor at Queensland University of Technology (QUT) and Chief Investigator at the Australian Centre for Robotic Vision (ACRV). His expertise spans environmental robotics, with a focus on vision-based autonomous systems for marine conservation, water quality monitoring, and greenhouse gas management. He holds a PhD from QUT and a BEng (Aerospace) from RMIT. Dunbabin has led projects at CSIRO and QUT, developing robots like COTSBot and RangerBot to combat marine pests and promote reef restoration. His work has earned national and international awards, including the 2019 Australian Water Association Award and 2016 Google Impact Challenge. Education: PhD in Engineering, Queensland University of Technology (Queensland, Australia) BEng (Hons) in Aerospace Engineering, Royal Melbourne Institute of Technology (Melbourne, Australia) Research Interests: Environmental robotics and autonomous systems Vision-based perception and classification Marine habitat restoration and pest control Greenhouse gas monitoring via autonomous vehicles Cooperative robotics and sensor networks Awards & Recognition: 2019 Australian Water Association Award (SAMMI Project) 2019 Good Design Award - Sustainability (RangerBot) 2016 Google Impact Challenge People’s Choice Award (RangerBot AUV) 2010 Australian ICT Industry Association National iAward (iSnet) 2006 Queensland Engineering Excellence Innovation Award (Starbug Project) Grants & Projects: ARC Centre of Excellence for Robotic Vision (ACRV): Leading robotic vision research (2014–present) Revolutionising Protection Against Air Pollution: Air quality monitoring networks (2015–present) Establishing Advanced Networks for Air Quality Sensing: Sensor development for urban environments (2017–present) Labs & Collaborations: ACRV at QUT Institute for Future Environments (QUT) CSIRO Autonomous Systems Laboratory (2001–2013)

• Artificial Intelligence in Education (AIED)
• User Modeling
• Human-Computer Interaction (HCI)
• +5 more

Professor Judy Kay is a leading academic in Computer Science at the University of Sydney, holding a Chair in Human-Centred Technology Research within the Faculty of Engineering and IT. Her work focuses on designing personalized systems that empower users to control their data, particularly in lifelong learning and health contexts. She leads the Human Centred Technology Research Cluster and is Editor-in-Chief of the International Journal of Artificial Intelligence in Education (IJAIED). Education: Studied at the University of Sydney, inspired to pursue academia due to its multidisciplinary environment and student collaboration opportunities. Research interests include user modeling, scrutable AI systems, and interfaces for personal informatics. Current projects span virtual reality learning environments, health data dashboards, and ethical AI transparency. Her work has led to commercialized technologies like the Personis system. Publications include over 200 peer-reviewed works in top venues like CHI, UbiComp, and AIED conferences. Awards highlight her contributions to computing education and AIED, including the 2023 Lifetime Achievement Award. Advises 4 current PhD/Master’s students focusing on topics like Open Learner Models in VR and health decision-making tools. Collaborates with multidisciplinary teams across computer science, health sciences, and education. Labs/Teams: Leads research groups in the School of Computer Science and collaborates with the Charles Perkins Centre on health-related projects.

• Computer Vision
• Machine Learning
• Robotics
• +6 more

Dr. Feras Dayoub is a Senior Lecturer at the School of Computer and Mathematical Sciences (Faculty of Sciences, Engineering and Technology) at the University of Adelaide , specializing in Embodied AI and Robotic Vision within the Australian Institute for Machine Learning (AIML) . He co-directs the CROSSING French-Australian laboratory for human-autonomous agent teaming and holds an Adjunct position at the Queensland University of Technology (QUT) , serving as an Associate Investigator at its Centre for Robotics . Previously, he was a Chief Investigator at the ARC Centre of Excellence for Robotic Vision . His research focuses on advancing reliable deployment of computer vision and machine learning on mobile robots in real-world environments. Applied projects include agricultural automation , environmental conservation , and autonomous infrastructure monitoring . He has published extensively on topics like object detection , domain adaptation , 3D representation learning , and vision-language navigation , with a particular emphasis on robustness in dynamic and partially observed environments. Dr. Dayoub is also an educator specializing in programming , computer vision , and robotic perception . He contributes to open-source robotics research through tools like AARK (Autonomous Racing Toolkit) and has led teams developing solutions for precision agriculture (e.g., Deepfruits fruit detection system) and environmental monitoring (e.g., Crown-Of-Thorns starfish detection ). Key Collaborations : CROSSING Lab, QUT Centre for Robotics Research Themes : Embodied AI, Robust Perception, Domain Adaptation

Ivan ColeView profile

Adjunct Professor

• Corrosion Science
• Multiscale Modelling
• Additive Manufacturing
• +7 more

Prof. Ivan Cole is an Adjunct Professor at RMIT University's School of Engineering, specializing in rapid materials discovery for corrosion protection, nanostructures, and additive manufacturing. His work integrates computational modeling with high-throughput experimentation, focusing on corrosion inhibitors, biocompatible surfaces, and additive manufacturing process optimization. With over 30 years of experience across academia and industry (including leadership roles at CSIRO and Centro-Svilluppo Materiali), he leads the Rapid Discovery & Fabrication Team (RDF) to advance these research areas. Research Interests: Corrosion science, microbially induced corrosion (MIC), additive manufacturing surfaces, nanostructure sensing, multiscale modeling, and green materials discovery. His team addresses challenges in corrosion protection, biomedical implants, and environmental remediation through innovative methodologies. Awards: 2019 Australian Corrosion Medal 2016 CSIRO Lifetime Achievement Award 2013 Best Paper in NACE Corrosion Supervision & Projects: Active in mentoring PhD/Master’s students across corrosion inhibition, additive manufacturing, and nanostructure design. Notable projects include developing quorum sensing inhibitors for biofilm control, in-situ monitoring for metal AM, and eco-friendly corrosion inhibitors. Labs & Collaborations: Leads the Rapid Discovery & Fabrication Team and collaborates with industry partners to translate research into practical solutions for materials durability and sustainability.

• Autonomous Systems
• V2X Communication
• Cooperative Perception
• +3 more

Dr. Mao Shan is a Senior Research Fellow at the Australian Centre for Robotics, part of The University of Sydney. He holds a PhD from The University of Sydney (2014) and has held research positions at Nanyang Technological University (2016-2017) and the Australian Centre for Robotics (2014-2016). His research focuses on autonomous systems, V2X communication, cooperative perception, and sensor fusion. Current students include Yaoqi HUANG, Henry LYU, Zhenxing MING, Nguyen TRAN, Tzu-yun TSENG, and Yupeng WANG. His work spans robotics, intelligent transportation systems, and control systems. Recent publications emphasize 3D object detection, cooperative perception frameworks, and autonomous navigation. He has contributed to the development of the University of Sydney Campus Dataset for robust autonomy testing and led cooperative perception projects funded by iMOVE CRC (2018). His research bridges theoretical advancements with practical applications in autonomous vehicles and multi-robot systems. Labs and affiliations include the Australian Centre for Robotics and the Intelligent Transport Systems Group. His interdisciplinary approach integrates probabilistic modeling, sensor fusion, and machine learning to address challenges in autonomous systems.

• General Surgery
• Colorectal Surgery
• Endometriosis Surgery
• +3 more

Dr. Joseph Choi is a Clinical Lecturer and General Surgery Fellow at the University of Sydney's Westmead Clinical School, within the Discipline of Surgery under the Faculty of Medicine and Health. He holds academic qualifications including BSc(Adv), MBBS, MPhil, and FRACS. His clinical and research interests focus on surgical outcomes, colorectal surgery, endometriosis management, and minimally invasive techniques. Dr. Choi's research emphasizes surgical complications, anastomotic leak prediction, and emerging surgical technologies. He has contributed to over 30 peer-reviewed publications since 2011, with recent work addressing robotic surgery feasibility, Strongyloides stercoralis infections, and HER2 therapy outcomes in breast cancer. His academic profile includes collaborations with multidisciplinary teams across oncology, gastroenterology, and gynecology. No formal awards or grants are explicitly listed, though his prolific publication record reflects sustained scholarly activity.

Thanh Nho DoView profile

Senior Lecturer

• Biomedical Engineering
• Surgical Robotics
• Soft Robotics
• +5 more

Dr. Thanh Nho Do is a Scientia Senior Lecturer at the Graduate School of Biomedical Engineering (GSBmE), UNSW Sydney, and Director of the UNSW Medical Robotics Lab. He holds a PhD in Mechanical Engineering (Surgical Robotics) from Nanyang Technological University (NTU), Singapore, and a B.Eng. in Manufacturing Engineering from Ho Chi Minh City University of Technology, Vietnam. His research focuses on soft robotics, wearable technologies, and biomedical devices, including flexible surgical systems, soft actuators, and haptic interfaces. Education PhD in Mechanical Engineering (Surgical Robotics), NTU Singapore, 2015 B.Eng. in Manufacturing Engineering, Ho Chi Minh City University of Technology, Vietnam Research Interests Soft robotics for medical applications (e.g., NOTES systems, wearable haptics) Functional materials for biomedical devices Cardiovascular engineering and assistive devices Advanced control algorithms for medical robotics Key Contributions His work spans bioprinting, motor-free robotic systems, and soft wearable technologies. Recent studies include self-deploying cardiac compression devices and bioinspired artificial muscles. Awards 2025: CINSW Career Development Fellow 2024: NSW Young Tall Poppy Science Award 2023: Best Poster Awards at EMBC and ICRA Grants & Funding Includes NHMRC Ideas Grant (Lead CI), Cancer Institute NSW Fellowship, and UNSW Scientia Grant. Active projects address cardiovascular interventions and wearable robotics. Labs & Teams Leads the UNSW Medical Robotics Lab, collaborating on devices like soft robotic catheters and textile-driven exosuits.

Khac Duc DoView profile

Professor

• Control of Nonlinear Systems
• Autonomous Marine Vehicles
• Partial Differential Equation Systems
• +3 more

Professor Khac Duc Do is a faculty member at Curtin University, holding a position in the School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He serves in the Office of the Provost and is based at Curtin Perth campus. His research focuses on advanced control systems, nonlinear dynamics, and robotics applications in marine, aerospace, and mechanical systems. He earned a PhD with distinction in 2003 and has held prestigious fellowships including ARC Postdoctoral Fellow (2004) and ARC Australian Research Fellow (2009). His teaching includes courses like Advanced Control and Mechatronics, Navigation and Marine Control Systems, and Advanced Control Engineering. Key research interests encompass control of nonlinear systems, stochastic systems, formation control of mobile agents, fluid-structure interaction, and boundary control of PDE-governed systems. His funded projects include wave-energy converter development (2023-2026), inerter-based damper research (2019-2021), and ocean vehicle control systems. Scientific awards include ARC grants totaling over AUD 2 million. Current opportunities include scholarships in control systems/fluid-structure interaction and a postdoc position in wave-energy conversion.

Jon McCormackView profile

Professor

• Computational Creativity
• Human-machine interfaces
• Artificial Intelligence/Cybernetics
• +9 more

Jon McCormack is a Professor jointly appointed in Monash University's Faculty of Art, Design & Architecture (MADA) and Faculty of Information Technology. He founded and directs SensiLab, a research facility focusing on computational creativity, human-machine interfaces, and generative systems. His work spans electronic media art, evolutionary music, and artificial life. McCormack holds a PhD in Computer Science from Monash University, along with degrees in Computer Science, Applied Mathematics, and Film/Television. Research interests include computational creativity, tangible interfaces, and cybernetic systems. Notable projects include 'Explainable Artificial Creativity' (ARC-funded) and 'Building 4.0 CRC,' addressing architectural innovation through AI. He has been recognized with awards for collaborative projects like the Blundstone Intelligent Footwear for Healthcare. McCormack's recent articles explore AI-driven art, generative systems, and interdisciplinary design. His work bridges artistic practice with technical innovation, emphasizing ethical and creative dimensions of human-AI collaboration. SensiLab serves as a hub for practice-based research in digital media and interactive systems. Education: PhD in Computer Science, Monash University (2004) Bachelor of Science (Honours), Computer Science/Applied Mathematics, Monash University (1987) Graduate Diploma in Film/TV, Swinburne University (1986) Bachelor of Science, Computer Science/Applied Mathematics, Monash University (1985) Key Projects: Lead investigator on 'Explainable Artificial Creativity' (2022–2026) Co-investigator in 'Building 4.0 CRC' (2020–2027), exploring AI-driven architectural design Awards: 2022 Designers Australia Award for Blundstone Footwear 2020 'On the Machine Condition' Prize McCormack's lab, SensiLab, fosters collaborations across disciplines, producing exhibitions, software, and theoretical frameworks for computational creativity. He actively supervises PhD students in practice-based research, emphasizing the intersection of art and technology.