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Professor Michael Milford is a robotics and computer vision expert at Queensland University of Technology (QUT), serving as Joint Director of QUT's Centre for Robotics. His research bridges robotics, neuroscience, and computer vision, focusing on biologically inspired navigation systems for autonomous vehicles and drones. He has pioneered projects like SeqSLAM and RatSLAM, emphasizing the synergy between biological intelligence and robotic systems. Research Interests: Milford explores navigation algorithms inspired by animal behavior, energy-efficient neural networks, and autonomous systems. His work aims to create robots capable of operating in dynamic environments through interdisciplinary collaboration with institutions like MIT, Harvard, and NASA's Jet Propulsion Laboratory. Awards & Recognition: Awarded the 2019 Batterham Medal and a $2.7M Australian Laureate Fellowship for his project on GPS-independent positioning systems. His work has produced highly cited papers in robotics and computer vision, including breakthroughs in visual SLAM and place recognition under varying conditions. Teaching & Collaboration: Milford mentors students in robotics and AI, launching initiatives like the STEM Storybook to inspire youth. He collaborates globally, emphasizing cross-disciplinary research to bridge gaps between fundamental and applied sciences. Labs & Projects: Leads QUT's Centre for Robotics, advancing technologies for autonomous systems. His projects explore neuromorphic computing, SLAM systems, and bio-inspired navigation, with applications in defense, transport, and environmental monitoring.

• Robotics
• Neuroscience
• Computer Vision
• +3 more

Dr. Miaoqiang Lyu is a Research Fellow at the School of Chemical Engineering , The University of Queensland . His work focuses on lead-free perovskites , flexible energy storage , and optoelectronic devices . Research Interests : Designing low-toxicity and stable semiconducting lead-free perovskites for solar energy conversion Developing flexible energy storage devices for Internet-of-Things (IoT) sensors Advancing zinc batteries and aqueous electrolyte systems Photocatalytic hydrogen production and CO2 reduction Recent Article Trends : Focus on 2D/3D heterostructures, interstitial metal doping, and solvent-engineered interfaces Applications in indoor photovoltaics, artificial synaptic functions, and wearable electronics Lead-free perovskites for resistive memory and energy storage Scientific Awards : ARC DECRA Fellow Advance Queensland Industry Research Fellow CRC for Polymers grant Supervision & Funding : Principal advisor for two PhD projects on lead-free perovskites and flexible batteries Current grants: Enabling low-toxicity perovskites for indoor photovoltaics (2026-2030), Printable zinc ion batteries (2025-2026) Labs & Collaborations : Affiliated with the Nanomaterials Centre at UQ Collaborations with Professor Lianzhou Wang , Professor Ian Gentle , and Associate Professor Ruth Knibbe

• Solar Energy
• Photocatalysis
• Flexible Electronics
• +3 more

Yongxiang Li is a Professor in the School of Engineering at RMIT University, Australia, specializing in advanced materials and nanotechnology. His research focuses on piezoelectric materials, 2D functional materials, and energy harvesting systems. He is actively involved in supervision of PhD and Master’s projects, including topics like flexible piezoelectric nanogenerators, 2D heterostructures, and low-temperature co-fired ceramic (LTCC) sensors. Research Interests: Materials Engineering, Electrical Engineering, Nanotechnology, Condensed Matter Physics, and Functional Ceramic Design. Key projects include developing lead-free piezoelectric materials, integrating sensors for lithium-ion batteries, and exploring gas sensors using liquid metal-derived oxides. Teaching Interests: Dielectric materials, ferroelectric systems, sensor technologies, and LTCC applications. His interdisciplinary work bridges materials science with optoelectronics and energy storage. Publications span over 400 outputs, emphasizing machine learning-driven materials discovery, defect engineering in 2D materials, and sensor innovation. He leads projects in collaboration with industry, focusing on practical applications of advanced ceramics and nanomaterials.

• Materials Engineering
• Electrical and Electronic Engineering
• Nanotechnology
• +7 more

Dr Saeed Afshar serves as a Senior Lecturer at the International Centre for Neuromorphic Systems (ICNS) within Western Sydney University, where he develops advanced sensing and processing systems leveraging neuroscience, machine learning, and circuit design principles for superior performance in dynamic environments. His academic credentials include: BSc (Engineering) from the University of New South Wales (2014) MSc (Engineering) from the University of New South Wales (2016) PhD from Western Sydney University (2020) Research expertise spans: Neuromorphic Systems architecture Machine Learning algorithms for noisy environments Signal Processing innovations Neuroscience-inspired computing Integrated circuit design Computer Vision systems Auditory Processing frameworks His work focuses on creating vision, memory, and auditory systems that outperform conventional computing approaches in real-world conditions. Contact available via s.afshar@westernsydney.edu.au or (02) 9852 5017 at Werrington South campus (Building BA, Room 2.01).

• Neuromorphic Systems
• Machine Learning
• Signal Processing
• +4 more

Paul Hurley serves as Professor of Data Science at Western Sydney University, affiliated with the Centre For Research In Mathematics and Data Science and the International Centre for Neuromorphic Systems. He is based at the Parramatta Campus (Room EN.1.31) and maintains active research across interdisciplinary domains. His research portfolio demonstrates exceptional breadth, integrating theoretical and applied approaches in: Mathematical signal processing Data science Algorithms Information theory Medical imaging applications Radio astronomy interferometry This work bridges computational theory with real-world implementations in healthcare and astronomical observation. While specific publication details are referenced via Google Scholar, his research trajectory shows consistent contributions to mathematical data analysis frameworks across multiple scientific disciplines.

• Mathematical signal processing
• Data science
• Algorithms
• +3 more

Sanjoy Nandi is a Postdoctoral Fellow in the Department of Electronic Materials Engineering at the Australian National University (ANU), specializing in neuromorphic computing and memristor technology. He holds a PhD in Physics from the University of Chittagong (2017). His research focuses on designing novel memristive devices for neuromorphic systems, with particular emphasis on threshold switching, material properties of NbOx and V₃O₅ films, and integrating memristors with CMOS circuits. Nandi has published over 47 peer-reviewed articles, with an h-index of 14 and 161 citations. His work spans memristor-based spiking neural networks, thermosensitive dynamics, and optical tunable oscillators, contributing to advancements in neuromorphic hardware and solid-state electronics. Education: PhD in Physics (University of Chittagong, 2017). Research supervision is registered through ANU's Department of Electronic Materials Engineering. Research interests include memristor engineering, neuromorphic architectures, and nanoelectronics. Key projects involve exploring negative differential resistance in vanadium oxides and developing ternary logic systems using memristor-CMOS hybrids. His contributions also address thermal effects in cross-point devices and material interdiffusion impacts on switching characteristics. Labs/Teams: Collaborates within ANU's Electronic Materials Engineering research groups, focusing on interdisciplinary projects at the intersection of materials science and circuit design. Active in global collaborations through co-authored publications with institutions in Spain, Japan, and the UK.

• Neuromorphic Computing
• Memristor Technology
• Electronic Materials Science
• +3 more

Irfan H. Abidi is a Research Fellow at RMIT University's School of Engineering, specializing in 2D materials and their applications. He previously held a Research Fellowship at the National University of Singapore's Centre for Advanced 2D Materials. His research focuses on engineering atomic structures in materials like graphene and h-BN via CVD techniques, with applications in optoelectronics, quantum technologies, and energy storage. Abidi has authored over 40 publications, holds four US patents, and leads multiple funded projects totaling over $2M, including AEA Ignite and ARC grants. He supervises research in areas like gas sensors and nanogenerators, and teaches Sensors and Measurement Technology courses. Education: Ph.D. in Materials Science from HKUST, Hong Kong. Research highlights include pioneering 'gettering' CVD growth and the first monolayer amorphous carbon synthesis. His work bridges academic research and industry, with collaborations on patents and tech commercialization. Grants include leadership roles in AEA Ignite projects (IG240100400, IG240100041) and ARC Discovery/LIEF grants (DP240100145, LE250100014). Key Awards: Over 2,200 citations (h-index 23), editor of a book. Lab/Teams: Collaborations with global industry partners on nanomaterials and device applications.

• 2D Materials
• Materials Engineering
• Energy Storage
• +6 more

Gurpreet Singh Gill is a Research Fellow at The University of Western Australia (UWA), School of Engineering, Department of Electrical, Electronic and Computer Engineering. He holds a Ph.D. from UWA (2022) and prior degrees from Punjab Technical University and Sri Guru Granth Sahib World University, Punjab, India. His research focuses on MEMS/NEMS, thin-film materials, optical MEMS, and infrared sensing/imaging technologies. He previously worked at the Central Electronics Engineering Research Institute, India, and currently leads projects in micro/nano electromechanical systems and their applications in optoelectronics and infrared sensing. **Education**: B.Tech in Electronics & Communication Engineering (2013, Punjab Technical University) M.Tech in Electronics & Communication Engineering (2015, Sri Guru Granth Sahib World University) Ph.D. in Microelectronics (2022, The University of Western Australia) **Research Interests**: MEMS/NEMS device design and applications Thin-film materials for optical and infrared systems Optical MEMS and optoelectronic devices Infrared sensing and imaging technologies **Awards**: Nanoscale Advances Poster Prize (2019) ADHOC Postgraduate Scholarship (2017) Scholarship for International Research Fees (SIRF) (2017) **Grants & Advising**: Gill has received scholarships for international research fees and postgraduate support. He collaborates with interdisciplinary teams and leads research projects funded by UWA and external grants. His work contributes to UN SDGs related to affordable and clean energy, industry innovation, and infrastructure. **Labs & Teams**: Active in UWA’s Microelectronics Research Group and collaborates with global institutions on MEMS-based sensing systems.

• MEMS/NEMS Technology
• Thin-Film Materials
• Optical MEMS
• +3 more

Professor Akram Hourani is a Discipline Leader and Professor in the Department of Electrical & Electronic Engineering at RMIT University's School of Engineering. He holds roles as Program Manager for the Master of Engineering (Telecom & Network Eng.) and Deputy Director of the Centre for Opto-electronic Materials and Sensors (COMAS). Prior to academia, he was an ICT Program Manager in the telecommunications industry, leading projects in satellite and telecommunications infrastructure. His research focuses on advanced signal processing, satellite communications, radar systems (including SAR), neuromorphic hardware, and IoT. He has secured grants from ARC, CRC, government departments, and DSTG, with over 130 publications. His work aligns with UN Sustainable Development Goals 9 (Industry, Innovation & Infrastructure), 11 (Sustainable Cities), and 10 (Reduced Inequalities). Education: PhD in Electronics & Telecommunications (2016, RMIT University) Non-academic roles: R&D Engineering Program Manager at Inteltec Emirates (2006–2013) Key research themes include interference mitigation, 5G/6G networks, neuromorphic sensing, and AI-driven satellite IoT. He is listed in Stanford's top 2% scientists for career-long and single-year impact. His teaching includes courses on satellite communications and wireless sensor networks. Grants & Funding: ARC, CRC, DSTG, and government-funded projects since 2017 Collaborations: CSIRO, industry partners in telecommunications and aerospace His lab focuses on next-generation communication systems, with active projects in mega satellite networks, neuromorphic hardware, and AI for IoT sensing. He supervises PhD/Masters research in areas like satellite connectivity and machine learning applications.

• Satellite Communications
• Signal Processing
• Internet-of-Things (IoT)
• +6 more

Dr. Salim Bouzerdoum is a Senior Professor of Computer Engineering at the University of Wollongong (UOW), affiliated with the School of Electrical, Computer & Telecommunications Engineering. He holds a Ph.D. and M.Sc. in Electrical Engineering from the University of Washington. His roles include former Associate Dean for Research (2007–2013) and Head of School (2004–2006). He has served on the Australian Research Council panels and held visiting professorships globally. Education: Ph.D. in Electrical & Computer Engineering, University of Washington, Seattle, USA M.Sc. in Electrical Engineering, University of Washington, Seattle, USA Research Interests: His work focuses on Artificial Intelligence , Machine Learning , and Signal & Image Processing , with applications in radar imaging, computer vision, and smart sensors. Key areas include neural networks, object detection/tracking, and compressive sensing. Recent projects include assistive navigation tools for vision-impaired individuals and underwater mine detection via sonar imaging. Grants & Funding: He leads or co-leads over 30 funded projects, including: AI-based SAR Satellite Imaging System for Oceanic Waves (AGO, 2024–2025) A portable AI-guided navigation tool for vision-impaired people (KONEKSI, 2024–2026) Deep Learning for Vessel Surveillance using Satellite Imagery (NSW Space Research Network, 2022–2023) Teaching & Supervision: With 30+ years of experience, he has supervised 38 Ph.D. and 22 master’s students, mentored 12 early-career researchers, and delivered courses like Applied Data Analytics and Neural Networks . Current supervision includes projects on deep learning for obstacle detection and semantic segmentation. Awards: Eureka Prize (2011) for Defence Science ARC College of Experts Member (2009–2011) Multiple Vice-Chancellor Research Awards (1998–1999)

• Artificial Intelligence
• Machine Learning
• Signal and Image Processing
• +4 more

Dr. Thomas Chaffey is a Lecturer in the School of Electrical and Computer Engineering at The University of Sydney. His research focuses on nonlinear control theory, convex optimization, and neuromorphic systems. He obtained his PhD from the University of Cambridge (2022) and held the Maudslay-Butler Fellowship at Pembroke College, Cambridge (2022–2025). Education: PhD in Control Theory, University of Cambridge (2022) Maudslay-Butler Fellowship in Engineering, Pembroke College, Cambridge (2022–2025) Master's in Mechanical Engineering, University of Sydney (Australia) Bachelor's in Mathematics and Computer Science, University of Sydney (Australia) Research Interests: Nonlinear control theory and its intersections with optimization and circuit theory Development of neuromorphic systems and analog hardware simulation Monotone operator methods and large-scale optimization algorithms Key Research Trends in Articles: Advances in graphical methods for nonlinear system analysis (e.g., scaled relative graphs) Analysis of neuromorphic circuits using convex optimization frameworks Exploration of symmetry properties in physical systems Awards: Best Student Paper Award, 2021 European Control Conference Outstanding Student Paper Award, 2021 IEEE Conference on Decision and Control Labs/Teams: Leading projects on learning in physical systems and monotone circuits Collaborations with institutions like Lund University and University of British Columbia

• Nonlinear Control Theory
• Convex Optimization
• Circuit Theory
• +3 more

Professor Herbert Ho Ching Iu is a distinguished academic at The University of Western Australia, serving in the School of Engineering within the Department of Electrical, Electronic and Computer Engineering. With an impressive research portfolio of over 500 publications and an h-index of 61, Prof. Iu has established himself as a leading authority in power electronics and nonlinear systems research. Prof. Iu received his BEng(Hons) in Electrical and Electronic Engineering from The University of Hong Kong in 1997, followed by a PhD in Electronic and Information Engineering from The Hong Kong Polytechnic University in 2000. After a brief research fellowship at HKPU, he joined The University of Western Australia in 2002 as a Lecturer and has since risen to the rank of full Professor. His primary research focuses on power electronics , renewable energy systems , nonlinear dynamics and chaos , current sensing techniques , and memristive systems . Prof. Iu's work uniquely bridges theoretical exploration with practical implementations, particularly in energy conversion, secure communications, and neuromorphic computing. His research has significant implications for DC microgrids, advanced encryption techniques, and next-generation computing paradigms. Analysis of Prof. Iu's recent publications reveals a strong interdisciplinary trajectory combining memristive systems with chaotic dynamics for applications in image encryption and secure communications . There's a notable emphasis on machine learning techniques applied to power electronics and energy systems , particularly for DC microgrids and battery management. His work demonstrates consistent progression from fundamental research in nonlinear systems to practical engineering solutions with real-world impact. Prof. Iu's significant contributions have been recognized with several prestigious awards: Vice-Chancellor's Award for HDR Supervision (2024) School of Engineering Award for Research Mentorship (2023) Vice Chancellor's Award in Research Mentorship (2023) With 18 supervised research students and leadership on 16 research grants, Prof. Iu has built a robust research program at the forefront of power systems innovation. His grant portfolio includes major projects like 'Mine Electrification' and 'Microgrid Battery Deployment' through the CRC for Future Battery Industry, as well as collaborations with Western Power on 'Project Symphony.' These initiatives demonstrate his ability to secure substantial funding and translate theoretical concepts into practical engineering solutions for industry. Prof. Iu leads a dynamic research team that specializes in hardware implementation of advanced theoretical concepts, particularly in memristive systems and chaotic circuits. The laboratory maintains strong industry connections, especially with energy and mining sectors, ensuring research has tangible real-world applications. Current work emphasizes DC microgrid technologies, advanced battery systems for electrified transportation, and novel applications of chaotic systems in security contexts, positioning the team at the cutting edge of power electronics research.

• Power electronics
• Renewable energy
• Nonlinear dynamics and chaos
• +7 more

Professor Will Browne is the Chair in Manufacturing Robotics at QUT, collaborating with the ARM Hub and CSIRO to advance robotics in manufacturing, healthcare, and industry. He holds a Doctorate in Engineering from the University of Wales and has over 30 years of expertise in AI, robotics, and Learning Classifier Systems (LCS). His research focuses on transparent AI systems like LCS for Explainable AI (XAI), human-robot collaboration, and advanced manufacturing solutions. He co-leads the $5M SfTI Robotics Spearhead project and is internationally recognized for LCS contributions, including co-authoring the first LCS textbook with Ryan Urbanowicz. Publications emphasize emotion recognition, embodied AI, and scalable machine learning. His work bridges academia and industry through the ARM Hub, fostering innovation in robotics and design-led manufacturing. Key roles include co-track chair at GECCO (2011–2025) and editorial board memberships. Research spans evolutionary computation, robotics control, and energy systems optimization.

• Artificial Intelligence
• Robotics
• Manufacturing Systems
• +5 more

Professor Omid Kavehei is a Professor of Intelligent Microsystems in the Faculty of Engineering at the University of Sydney, serving as Deputy Head of the School of Biomedical Engineering. Previously, he held roles as a Research Fellow at the University of Melbourne and Lecturer at RMIT University. His research focuses on biomedical microsystems, nanotechnology, and brain-inspired hardware for healthcare applications, particularly epilepsy monitoring and seizure prediction. Education: PhD (specific institution not explicitly stated) His work bridges nanoelectronics and healthcare, aiming to develop low-power, brain-inspired devices for sensory perception and medical diagnostics. Key interests include neuromorphic engineering, wearable sensors, and AI-driven medical systems. Awards include the Ramaciotti Biomedical Research Award (2021), Microsoft AI for Accessibility Grant (2019), and multiple teaching/research excellence awards from the University of Sydney. His recent work explores neuromorphic cytometry for cell analysis, edge AI for ECG/EEG diagnostics, and closed-loop neurostimulation systems. Collaborations include the Sydney Nano Institute, Brain and Mind Centre, and industry partners like Microsoft. Current research students are advancing topics like bio-inspired algorithms for seizure detection, hardware-friendly machine learning models, and flexible sensor systems for aquatic environments. Grants include funding for neurophysiology platforms, quantum sensors, and semiconductor design. Labs/teams: Involved in the Centre for Drug Discovery Innovation and collaborations across engineering, neuroscience, and clinical domains.

• Biomedical Engineering
• Nanotechnology
• Microelectronics
• +5 more

Ko, Jonghyeon is a researcher affiliated with the Ulsan National Institute of Science and Technology (UNIST) , specifically the Department of Materials Science and Engineering within the College of Natural Science and Engineering. His work spans multiple disciplines including process mining, anomaly detection, blockchain technology, AI computing, and environmental engineering. His research interests include: Anomaly detection in business process event logs Blockchain-based systems for nuclear/radioactive waste management AI computing using neuromorphic devices Statistical leverage and information-theoretic approaches to process mining Optimization of autonomous vehicle safety systems Recent publications demonstrate expertise in developing formal languages for data quality simulation, probabilistic trace alignment methods, and practical tools for anomaly detection like AIR-BAGEL. While no explicit scientific awards are mentioned in the text, his work has been published in venues such as Information Systems , npj Unconventional Computing , and Expert Systems with Applications .

• Process Mining
• Anomaly Detection
• Blockchain
• +3 more