جست‌وجوی استاد و پژوهشگر

Penny Kyburzمشاهده پروفایل

استاد

• Video Games
• Game Design
• AI
• +۴ مورد دیگر

Prof. Penny Kyburz is a Professor and Associate Director (Engagement & Impact) at the School of Computing, Australian National University. She leads the GameFlow Lab and teaches Game Development, focusing on AI, human-AI interaction, and game design. Her work bridges academia and industry, with 20+ award-winning games including four BAFTA nominations. She holds a PhD, B.InfoTech(Hons), G.C.Ed.(Higher Ed.), and G.C.Acad.Prac. Education: Ph.D. B.InfoTech(Hons) Graduate Certificate in Education (Higher Education) Graduate Certificate in Academic Practice Research Interests: Video games, game design, and player experience AI and human-AI collaboration Virtual Reality and Mixed Reality applications Technology policy and digital rights Educational games and accessibility Awards: 4 BAFTA nominations for game contributions High critic scores for usability-tested AAA games Grants/Projects: IDEATE (2024–2028) MEC23: Advanced Biometrics (2023) C2 Sociotechnical Collaboration (2022–2024) Role-Based Deception in Games (2020–2021) Her GameFlow model and book on emergence in games are foundational in player experience research. She advocates for diversity in tech and has advised on digital rights in the Senate.

Giancarlo Pascaliمشاهده پروفایل

دانشیار

• Radiopharmaceutical Sciences
• Radiochemistry
• Automation in Radiopharmaceutical Production
• +۷ مورد دیگر

Dr. Giancarlo Pascali is a Conjoint Associate Professor at the School of Chemistry, UNSW Sydney , and Radiochemistry Team Leader at ANSTO's Camperdown cyclotron site. With a PhD in "Innovative Biomedical Technologies" from the University of Lecce (2004), he has held research positions at IFC-CNR , NIH , and GMP facilities in Milan and Pisa. His expertise spans radiochemical methods , radiopharmaceutical development , and microfluidic automation for nuclear medicine production. Education: PhD in Innovative Biomedical Technologies, University of Lecce (2004) BSc in Chemistry, University of Pisa (2001) Research interests focus on M 3 : Molecules, Methods, Machines . In Molecules , he designs radiopharmaceuticals for cancer , dementia , and inflammatory diseases . For Methods , his work explores photochemistry , electrochemistry , and mechanochemistry to label biomolecules with 18 F and other isotopes. Under Machines , he pioneers microfluidic systems for automated radiochemistry, emphasizing safety and process reliability . Editorial & Leadership Roles: Editorial Board Member of Nuclear Medicine and Biology , Contrast Media & Molecular Imaging , and Current Radiopharmaceuticals Executive Board of ANZSNM , ARTnet , and ASMI Asia-Oceania Director and iSRS2025 Chair for SRS

• Dynamics, Vibration and Vibration Control
• Machine Condition Monitoring and Mechanical Engineering Asset Management
• Renewable Energy and Sustainability
• +۱۰ مورد دیگر

Professor JC Ji is a distinguished academic at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he was promoted to Professor on January 3, 2025, after serving as an Associate Professor since January 1, 2016. He serves as the Theme Research Director at the Centre for Audio, Acoustics and Vibration (CAAV) at UTS and is an active member of the Faculty of Engineering and Information Technology. Professor Ji holds a PhD in Mechanical Engineering from Australia and a Graduate Certificate from UTS, along with CPEng NER certification from Engineers Australia since 2018. Professor Ji's research spans multiple interdisciplinary areas with significant practical applications. His primary research interests include Dynamics, Vibration and Vibration Control (focusing on wind turbine dynamics, rotor-bearing systems, and vibration isolation); Machine Condition Monitoring and Asset Management (specializing in fault diagnostics, prognostics, and digital twin-based modeling); Renewable Energy and Sustainability (particularly in vibration-based energy harvesting and battery circular economy); Mechanical and Vehicle Systems; Robotic and Multi-Agent Systems; and Ecological Systems. His work demonstrates a strong integration of theoretical foundations with practical engineering solutions for real-world problems. Analysis of Professor Ji's recent publications reveals a clear research trajectory focused on advanced vibration control systems, condition monitoring techniques, and digital twin applications. His work increasingly integrates machine learning with traditional mechanical engineering approaches, particularly in bearing and gear health management. A significant portion of his recent research focuses on quasi-zero stiffness vibration isolators using innovative structural designs including origami-inspired mechanisms. His publications show strong international impact with numerous high-citation articles in top mechanical engineering journals. Stanford University's World's Top 2% Scientists List for both career-long impact and single-calendar year impact in 2023 and 2024 CPEng NER Chartered Engineers certification from Engineers Australia (2018-present) Professor Ji actively supervises research students and has secured substantial funding for his work, including multiple ARC Discovery and Linkage Projects. He serves as an Associate Editor for Mechanical Systems and Signal Processing (Q1 journal), Journal of Vibration and Control (Q2 journal), and International Journal of Bifurcation and Chaos (Q2 journal). He is also an active assessor for ARC grant applications since 2007 and for international funding bodies including Hong Kong RGC, Belgium FNRS, and New Zealand MBIE. His industry collaborations include projects with Zip Heaters, Alstom Transport, and Coal Services Health and Safety Trust. As Theme Research Director at the Centre for Audio, Acoustics and Vibration (CAAV) at UTS, Professor Ji leads a research team focused on advancing vibration control technologies and their applications. His laboratory work includes developing innovative vibration isolators, condition monitoring systems for industrial machinery, and energy harvesting technologies. The research group maintains strong connections with industry partners to ensure practical implementation of their theoretical advancements.

• Business Intelligence
• Cloud Computing
• Software Engineering
• +۷ مورد دیگر

Professor Farookh Hussain is a distinguished academic at the School of Computer Science , University of Technology Sydney , specializing in Artificial Intelligence , Cloud Computing , and Software Engineering . His research spans diverse sectors including agriculture, manufacturing, healthcare, and transportation. Affiliated with the Australian Artificial Intelligence Institute (AAII) , he leads impactful work in business intelligence and carbon credit systems. Key research areas: AI applications, blockchain for provenance, carbon credit analytics Active in Masters/PhD supervision and cloud computing education Research Highlights : Developed KACINO framework for carbon dynamics modeling Created hybrid cybersecurity frameworks for supply chain risk management Advanced chatbot dialogue breakdown solutions through systematic reviews Proposed hypercomplex knowledge graph recommenders Published extensively on carbon credit price prediction and blockchain storage methods Contributions to water demand forecasting and collaborative robotics adoption Grant Activities : Secured funding from Hampton Capital Asset Management , Innovation Connections , and Science and Industry Endowment Fund Projects include LLM-driven text-to-SQL conversion , blockchain for melanoma data , and AI for storm water management

Matt Garrattمشاهده پروفایل

استاد

• Robotics
• Swarm Robotics
• Unmanned Aerial Vehicles
• +۵ مورد دیگر

Professor Matt Garratt is a faculty member at the University of New South Wales (UNSW Canberra), School of Engineering and IT, serving as AI theme lead for the Defence Trailblazer Universities initiative with over $200 million in funding. His primary research focuses on sensing, guidance, and control for autonomous systems within robotics and unmanned aerial vehicles. Garratt's research spans robotics, swarm intelligence, and autonomous systems with emphasis on bio-inspired navigation techniques and adaptive flight control. His work addresses critical challenges including terrain following using vision systems, landing UAVs on moving platforms, and developing self-organizing swarms. He integrates artificial intelligence, computer vision, and machine learning to advance unmanned systems capabilities in complex environments. Analysis of his recent publications reveals strong trends in bio-inspired UAV navigation (particularly honeybee behavior modeling) and swarm robotics applications. His work increasingly incorporates deep learning for perception tasks while addressing real-world challenges like gas plume detection and adversarial robustness in 3D vision systems. The research demonstrates consistent progression toward practical implementation of autonomous systems in dynamic environments. Professor Garratt has secured over $7.7 million in external research funding as Chief Investigator on 33 grants. He actively mentors graduate students with scholarships available for Masters and PhD research in robotics and AI, focusing on: UAV path planning and adaptive control systems Swarm robotics collective motion optimization Bio-inspired autonomous navigation techniques Computer vision for robotic perception He co-founded the UNSW Canberra AIR (AI and Robotics) Group (AIR Lab), which drives research in trusted autonomy, swarm intelligence, and AI integration for defense applications. The lab develops practical solutions for autonomous systems operating in complex, real-world environments while maintaining ethical AI frameworks.

• Smart Grids
• Renewable Energy Integration
• Optimization of Power Systems
• +۴ مورد دیگر

Cuo Zhang is a Lecturer of Power Engineering and ARC DECRA Fellow at the University of Sydney's School of Electrical & Computer Engineering. He holds a B.E. (Hons.) from the University of Sydney (2014) and a Ph.D. in Electrical Engineering from UNSW (2018). His research focuses on smart grids, renewable energy integration, voltage control, and optimization of power systems. Key interests include distributed generation planning, energy storage systems, and demand response mechanisms. Dr. Zhang leads research on enhancing distribution network resilience through advanced control strategies and participates in the Net Zero Institute. He has secured grants such as the 2024 ARC DECRA project on renewables hosting capacity. Supervised students include Yunqing Zhang, working on robust renewables integration. His recent publications emphasize data-driven approaches, decentralized energy trading, and adaptive control for unbalanced networks. He explores machine learning applications in energy management and stochastic optimization under uncertainty. Awards include the University Medal for academic excellence. Awards: ARC DECRA Fellow Grants: 2024 Robust Renewables Hosting Capacity Enhancement Labs/Teams: Member of the Net Zero Institute

Tim Lynarمشاهده پروفایل

مدرس ارشد

• Cyber Security
• Computer Science
• Machine Learning
• +۶ مورد دیگر

Dr. Tim Lynar serves as a Senior Lecturer at the University of New South Wales Canberra within the School of Systems & Computing. With a strong background in both academic research and industry practice, he has established himself as a leading figure in cyber security and computer science. His work bridges theoretical research with practical applications, focusing on innovative solutions for complex computing challenges across multiple domains including IoT security, machine learning applications in cyber defense, and high-performance distributed systems. Dr. Lynar's research interests span a wide spectrum of cyber security applications, with particular emphasis on the application of machine learning techniques to security challenges and the innovative use of epidemiological approaches to understand and combat cyber threats. His work in modeling & simulation, statistical & data analysis, network & systems administration, and high-performance distributed computing demonstrates his commitment to developing comprehensive security frameworks that address evolving threats in digital environments. The interdisciplinary nature of his research connects computer science with biological modeling approaches, creating novel methodologies for understanding security vulnerabilities. Analysis of Dr. Lynar's recent publications reveals a strong trend toward applying advanced machine learning techniques to cyber security challenges, particularly in IoT environments. His work increasingly integrates epidemiological models with security frameworks, creating a unique approach to threat detection and mitigation. The research spans practical applications in network security, drone systems, and AI security, demonstrating both theoretical depth and real-world applicability. A notable pattern is the consistent application of cutting-edge deep learning architectures like Vision Transformers and Variational Autoencoders to solve specific security problems across diverse domains. IBM Master Inventor (2016) Multiple IBM Innovation Awards (2011-2018) Client Value Outstanding Technical Achievement Awards (2015-2016) High Value Patent Awards (2014-2016) Best Article Award – International Journal of Information Systems & Social Change (2010) Multiple research scholarships from 2007-2010 Dr. Lynar's extensive patent portfolio demonstrates significant industry impact, with numerous issued US patents spanning diverse applications from energy efficient supercomputing to vehicle collision avoidance and drone-based microbial analysis. His research has attracted substantial industry collaboration, particularly with IBM, where he received multiple prestigious awards including the IBM Master Inventor designation. The practical applications of his work are evident in the wide range of patented technologies addressing real-world security and optimization challenges across multiple industries. Dr. Lynar's work spans multiple research domains simultaneously, with active projects in cyber security, drone systems, AI safety, and maritime traffic analysis. His research methodology consistently combines theoretical modeling with practical implementation, often leveraging simulation environments to test and validate approaches before real-world deployment. The interdisciplinary nature of his work creates connections between traditionally separate fields, enabling innovative solutions to complex problems.

• Computational Intelligence
• Cloud Computing
• Big Data Applications
• +۶ مورد دیگر

Jun Shen is a Professor at the School of Computing and Information Technology, University of Wollongong. He specializes in computational intelligence, cloud computing, and big data applications, with a focus on AI-driven solutions for real-world challenges in transport systems, healthcare, education, and environmental management. He has secured over 40 research grants totaling AU$4.5 million and supervised 26 completed PhD projects. His work spans interdisciplinary areas including bioinformatics, smart manufacturing, and digital health. Research interests include bio-inspired algorithmic optimization, AI in arts/media, and edge computing for IoT systems. He has pioneered research centers in applied computing since 2014 and holds editorial roles in top journals like IEEE Transactions. As an IEEE Distinguished Lecturer, he actively promotes AI ethics and interdisciplinary collaboration. Recent publications emphasize adversarial machine learning defenses, UAV systems, and multimodal data fusion. His supervision includes projects in intelligent transport systems, cloud computing, and e-learning. Grants include projects on resilient energy systems and UAV geolocation verification. Leadership roles include leading over 20 researchers and chairing conferences. He advocates for digital transformation in public services and has conducted fieldwork at MIT, UCI, and Georgia Tech.

Neil Cameronمشاهده پروفایل

استاد

• Polymer Chemistry
• Tissue Engineering
• Regenerative Medicine
• +۴ مورد دیگر

Professor Neil Cameron is the Monash Warwick Alliance Professor of Polymer Materials, splitting his time between Monash University's Department of Materials Science and Engineering (Australia) and the University of Warwick's School of Engineering (UK). His research focuses on polymeric biomaterials for applications in tissue engineering, regenerative medicine, and drug delivery. He holds a PhD in Polymer Chemistry and a BSc in Chemistry from the University of Strathclyde. Key research themes include: New Tools for Biology: Scaffolds for 3D cell culture, glycopolymers, and polypeptides. New Tools for Chemistry: Supported catalysts and mass spectrometry methods for polymer sequencing. Materials for Medicine: Drug delivery systems targeting the eye, nanomedicine, and biodegradable scaffolds. Synthetic Biology: Polymersome-based protocells and glycosylated nanoparticles. His projects span interdisciplinary collaborations, including the development of biodegradable ligament scaffolds, functionalized cellulose materials, and novel mass spectrometry techniques. He leads or co-investigates grants such as the SURE-Poly project on recyclable polymers and the NHMRC Equipment Grant for UV lamp adaptors. Labs/Teams: Active in Monash’s Materials Science group and collaborates with Warwick researchers. His lab specializes in biomaterials design, with a focus on scalable production and clinical applications.

• Enzyme Catalysis
• Biocatalysis
• Cytochrome P450 Enzymes
• +۶ مورد دیگر

Associate Professor Stephen Bell is a faculty member in the School of Physics, Chemistry and Earth Sciences at the University of Adelaide, within the Faculty of Sciences, Engineering and Technology. He holds an academic rank of Associate Professor and leads research focused on enzyme catalysis, particularly cytochrome P450 enzymes. His work emphasizes biocatalysis applications in sustainable chemical synthesis and bioremediation, leveraging interdisciplinary methods from biochemistry, synthetic biology, and chemistry. Research Interests: Dr. Bell’s lab studies cytochrome P450 enzymes for their potential in oxidizing organic compounds, including steroids and terpenoids, with a focus on extremophile-derived enzymes for robust biocatalytic processes. Key areas include enzyme engineering, electron transfer partner identification, whole-cell oxidation systems, and structural studies via X-ray crystallography. Collaborative projects involve drug metabolism mechanisms, enzyme structure determination, and immobilization technologies for enhanced stability. Awards and Grants: His research has been supported by Australian Research Council grants, including Discovery Projects and a Future Fellowship. Notable achievements include founding the spin-out company Oxford Biotrans, which commercialized biocatalytic production of high-value compounds like flavor and fragrance ingredients. Teaching: He teaches inorganic, medicinal, and biological chemistry courses, covering reaction mechanisms, electron transfer processes, and transition metal chemistry. Supervision: Currently oversees 7-8 PhD students and has extensive experience mentoring Honours students. His group actively recruits candidates interested in enzyme engineering, biocatalysis, and synthetic biology. Labs and Teams: The lab focuses on interdisciplinary approaches to enzyme-based biocatalysis, with emphasis on scaling up reactions using fermentor technology and bioprocess engineering. Collaborations span structural biology, spectroscopy, and industrial partners for application development.

Liz Ratnamمشاهده پروفایل

دانشیار

• Control of Power Systems
• Optimization of Energy Systems
• Secure and Resilient Power Grids
• +۳ مورد دیگر

Associate Professor Liz Ratnam is a leading academic in the Department of Electrical and Computer Systems Engineering at Monash University, serving as Deputy Postgraduate Director of Education ECSE. Her expertise spans power systems control, energy optimization, and resilient grid design. She holds a BEng (Hons I) and PhD in Electrical Engineering from the University of Newcastle (2006 and 2016), with postdoctoral research at UC San Diego and Berkeley. She previously served as Senior Lecturer and Sub-Dean for Educational Programs at ANU's College of Engineering & Computer Science, supported by a Future Engineering Research Leader (FERL) Fellowship. Her current research focuses on advancing transactive energy markets, EV coordination in distribution networks, and secure grid operations. She leads major grants including the National Facility for Electricity Grid Security (ARC LIEF 2023) and projects on EV fast-charging infrastructure. Education Background: - BEng (Hons I) in Electrical Engineering, University of Newcastle (2006) - PhD in Electrical Engineering, University of Newcastle (2016) Research Interests: Resilient, carbon-neutral power grid design Control and optimization of energy systems Synchrophasor-based estimation for grid stability Transactive multi-agent systems for energy markets Electric vehicle integration and coordination in unbalanced grids Grants & Projects: ARC Linkage Infrastructure Grant LE23010058 (2023): National Facility for Electricity Grid Security ARC Discovery Project DP22010135 (2022): Neural Architecture Search for Deep Learning ARC Linkage Project LP21200473 (2022): Building Australia's EV Fast-Charging Infrastructure Awards & Memberships: Fellow of Engineers Australia Senior Member of IEEE FERL Fellowship (ANU)

• Artificial Intelligence
• Knowledge Graphs
• Semantic Technologies
• +۵ مورد دیگر

Dr Zhe Wang is a Senior Lecturer at the School of Information and Communication Technology, Griffith University, focusing on artificial intelligence, knowledge graphs, and semantic technologies. He earned his PhD in Computer Science from Griffith University (2011) and previously worked as a Research Fellow at the University of Oxford (2011-2013) on ontology-based systems. Research: Specializes in knowledge graph construction, rule mining for explainable AI, and integrating machine learning with logical reasoning. Led development of the scalable RLvLR rule-mining system and contributed to the HermiT ontology reasoner. Teaching: Instructs undergraduate and postgraduate courses including Introduction to Artificial Intelligence, Secure Development Operations, and Software Engineering Fundamentals. Grants: Funded by Australia's Economic Accelerator Ignite Grant (2025) for AI-driven marine life survey systems and Office of National Intelligence projects (2021-2022). Publications: Active in top venues like AAAI, ICASSP, and ISWC, with recent work on temporal knowledge graph reasoning, auction design algorithms, and neurosymbolic AI systems.

Belinda Abbottمشاهده پروفایل

دانشیار مدعو

• Medicinal Chemistry
• Organic Chemistry
• Biological Chemistry
• +۷ مورد دیگر

Dr. Belinda Abbott is an Adjunct Associate Professor at La Trobe University's Department of Chemistry and Physics, affiliated with the La Trobe Institute of Molecular Science. She specializes in medicinal chemistry and synthetic organic chemistry, focusing on small molecule inhibitors for bacterial enzymes, malaria treatment, and neurodegenerative diseases. Current projects: Fragment-based drug design for antibacterial agents, cardiac arrhythmia therapies, and PKA inhibition in malaria Key collaborations: Australian Research Council-funded initiatives Research Focus: Her work spans Medicinal Chemistry , Organic Chemistry , and Biological Chemistry , emphasizing structure-activity relationships and lysine biosynthesis inhibition. Recent publications highlight advances in dual-target herbicides, allosteric enzyme inhibition, and antimalarial compounds. Professional Activities: Member of the Royal Australian Chemical Institute since 2007. Grant recipient for NMR infrastructure and peptide nucleic acid research (2007-2022). Teaching: Coordinates and teaches undergraduate/postgraduate courses in organic chemistry, medicinal chemistry, and honors chemistry programs.

Ong Yong Szeمشاهده پروفایل

مدرس

• Cancer Nanomedicine
• Natural Product-Based Therapeutics
• Environmental Toxicology
• +۴ مورد دیگر

Dr. Ong Yong Sze is a Lecturer at Monash University Malaysia’s School of Pharmacy, specializing in precision oncology and nanomedicine. She holds a PhD in Pharmacology (2019) and a Bachelor of Biomedical Science (2013), both from Universiti Putra Malaysia. Her research focuses on cancer nanomedicine, natural product-based therapeutics, and environmental health risk assessment, with a commitment to developing low-toxicity therapies and addressing environmental pollutants’ health impacts. She has received prestigious awards, including the PeerJ Award for Best Poster (2021) and Oral Presentation Award (2025). Education: PhD in Pharmacology, Universiti Putra Malaysia (2019) Bachelor of Biomedical Science, Universiti Putra Malaysia (2013) Research Interests: Her work bridges nanotechnology, natural pharmacology, and toxicity studies. Key areas include engineering targeted nanoparticle drug delivery systems, exploring plant-derived anticancer compounds, and evaluating environmental pollutants like microplastics. Her interdisciplinary approach aims to enhance therapy precision while ensuring patient safety. Grants & Projects: She leads and collaborates on projects such as Development of a 3D Metastatic Breast Cancer-on-Chip Model (2023–2025) and Engkabang as High-Quality Cosmeceuticals (2023–2026), focusing on drug delivery, gut health, and functional foods. Lab & Teams: Her lab integrates nanomedicine and environmental toxicology, with collaborations spanning Malaysia, Portugal, and Taiwan. She actively organizes workshops on cell culture and drug discovery, furthering academic engagement.

Lizhen Quمشاهده پروفایل

مدرس

• Natural Language Processing (NLP)
• Privacy-Preserving Methods
• Neuro-Symbolic AI
• +۴ مورد دیگر

Dr. Lizhen Qu is a Lecturer at Monash University’s Faculty of Information Technology, part of the AIM Lab. His research focuses on robust and privacy-preserving neuro-symbolic methods for NLP and multimodal applications, including causal reasoning in dialogue systems, legal AI, digital health, and social NLP. Previously, he worked at Data61/CSIRO and completed his PhD at Saarland University and the Max-Planck-Institute for Informatics. Education: PhD in Computer Science from Saarland University and Max-Planck-Institute for Informatics. Research interests include integrating deep learning with logical reasoning, causal discovery, and ethical AI applications. He leads projects like TMLGenAI (Trusted Generative AI) and HARNESS (Neuro-Symbolic Systems), addressing model robustness and societal impact. Projects: TMLGenAI (2024–2026), HARNESS (2023–2027), and Accessible Data Exploration for Blind People (2023–2027) Contributions: Developed benchmarks like LazyReview and ACCESS, and co-organized ACL and IJCNLP workshops Research trends span causal discovery in NLP, federated learning for legal systems (e.g., FedLegal), and multimodal security. His work aligns with UN SDGs for innovation and health.