Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.
Professor Gavan McNally is a distinguished behavioral neuroscientist at the University of New South Wales, where he serves as a Professor in the School of Psychology. He is actively engaged in research on the fundamental behavioral and brain mechanisms for learning and motivation, with applications to clinical conditions such as addictions, anxiety disorders, and mood disorders. McNally holds several prestigious editorial positions, including Editor-in-Chief of Neurobiology of Learning & Memory and Senior Editor of The Journal of Neuroscience. He also serves as President-Elect of the European Behavioral Pharmacology Society and is a Member of the Australian Research Council College of Experts. McNally's research interests span behavioral neuroscience, focusing on how fundamental brain mechanisms apply to clinical conditions. He employs a systems neuroscience approach, combining well-controlled behavioral approaches with optogenetics, chemogenetics, in vivo calcium imaging, and whole brain circuit mapping in both normal and transgenic animals. His work bridges basic science with clinical applications through collaborations with colleagues at University of Sydney, Sydney Local Health District, Monash University, and Turning Point. McNally's research particularly examines the cellular, circuit, and systems level mechanisms underlying learning, motivation, and their dysregulation in disorders like addiction. His laboratory investigates how these mechanisms translate to human conditions, with a strong emphasis on developing new treatments for psychological disorders. His extensive publication record demonstrates a clear trajectory in understanding punishment learning, addiction mechanisms, and the neural circuits underlying motivated behavior. Recent work has increasingly focused on the cognitive pathways to punishment insensitivity, the role of specific neural circuits in addiction, and translational approaches to understanding maladaptive behaviors. McNally's research bridges animal models with human studies, creating a comprehensive understanding of the neural mechanisms that govern learning and motivation, with particular attention to how these processes go awry in addiction and other psychological disorders. 2008 QEII Fellow, Australian Research Council 2009 Association for Psychological Science, International Rising Star 2010 Fellow, Association for Psychological Science 2010 UNSW Faculty of Science Staff Excellence Award for Research and Training 2011 Pavlovian Research Award, The Pavlovian Society 2012 Future Fellow (Level 3), Australian Research Council 2016 D.G. Marquis Behavioral Neuroscience Award, American Psychological Association 2017 Fellow, American Psychological Association 2019 Fellow of the Academy of Social Sciences in Australia 2021 D.G. Marquis Behavioral Neuroscience Award, American Psychological Association 2022 Ross Day Plenary Lecturer, Australasian Brain and Psychological Sciences 2023 European Behavioural Pharmacology Society Plenary Lecturer 2024 Elspeth McLachlan Plenary Lecturer, Australasian Neuroscience Society 2024 D.G. Marquis Behavioral Neuroscience Award, American Psychological Association Professor McNally actively supervises several students including Bixuan Lin, Si Yin Lui, Hannah Machet, Bart Cooley, Kelly Zhuang, and Alexandra Gregory. His current research is supported by significant funding including an Australian Research Council Discovery Project (2024-2026) on "Risky choices: From cells and circuits to computations and behaviour," another Discovery Project (2025-2028) on "Multimodal mapping of punishment learning," and NHMRC grants including a Synergy Grant on "Linking clinical and basic science discovery to find new treatments for alcohol-use disorder" and an Ideas Grant on "Novel pathways to abstinence from alcohol seeking." These projects reflect his commitment to both fundamental neuroscience and translational applications for treating psychological conditions. His teaching responsibilities include PSYC2081 Learning & Physiological Psychology and PSYC3051 Physiological Psychology. McNally's laboratory employs advanced techniques including optogenetics, chemogenetics, in vivo calcium imaging, and whole brain circuit mapping to investigate the neural mechanisms underlying learning, motivation, and their dysregulation in disorders. His team works at the intersection of basic neuroscience and clinical applications, with strong collaborations across multiple institutions to translate fundamental findings into potential treatments for addiction and other psychological disorders. The lab has made significant contributions to understanding the role of brain regions like the ventral pallidum, paraventricular thalamus, and nucleus accumbens in addiction, fear learning, and punishment sensitivity.
Kavan Modi is a Professor at the School of Physics and Astronomy, Monash University. His research focuses on quantum information theory applied to dynamics, metrology, computation, thermodynamics, and relativity. He leads the Monash Quantum Information Science (MonQIS) group and serves as Director of the Centre for Quantum Technology at Transport for NSW (2022–2024). Education: B.Sc. Engineering Physics (Embry-Riddle Aeronautical University, 2001), M.A. Physics (University of Texas at Austin, 2004), Ph.D. Physics (University of Texas at Austin, 2008). Postdoctoral positions included the Centre for Quantum Technologies (Singapore, 2008–2011) and Clarendon Lab, Oxford (2011–2013). Joined Monash in 2014. Research interests center on quantum dynamics, non-Markovian processes, and their applications in quantum computing and information science. Projects include developing error correction codes, quantum algorithms for network analysis, and mitigating correlated noise in quantum systems. He has authored over 111 publications, with recent work emphasizing non-Markovian characterization, quantum process tomography, and topology-based quantum algorithms. Awards and grants include leadership in multiple Australian Research Council projects. Advising/Grants: Primary Chief Investigator in projects like 'Quantum Software Platform' (2023–2026) and 'Mitigating Correlated Noise in Quantum Machines' (2020–2021). Supervises graduate students and collaborates globally on quantum information science. Labs/Teams: MonQIS group focuses on foundational and applied quantum research, integrating theory and experimental collaborations.
Dr. Pulin Gong is an Associate Professor in the School of Physics at the University of Sydney. His research focuses on understanding the self-organizing mechanisms of neural circuits' spatiotemporal dynamics and their computational principles. He investigates distributed dynamic computation via propagating neural waves, irregular neural activity variability, and coherent spatiotemporal patterns in large-scale neural data. His work combines experimental and computational approaches to unravel neural coding principles. Research interests include: Distributed dynamic computation (e.g., visual feature integration) Irregular neural dynamics and membrane potential fluctuations Coherent spatiotemporal wave patterns (e.g., spiral waves) Recent projects involve analyzing cortical wave patterns in mice and primates, fractional neural sampling, and Lévy walk dynamics in neural systems. Collaborators include institutions like Fudan University and Kyoto University. Current research student: Andrew LY, working on cortico-cortical loop dynamics and AI applications.
David Caldicott is a Clinical Associate Professor at the Australian National University (ANU) School of Medicine and Psychology , where he contributes to interdisciplinary research and education. He also serves as an Emergency Medicine Consultant Physician at North Canberra Public Hospital, integrating clinical practice with academic work. Education: B.Sc.(Hons) MBBS (London) FRCEM (Fellow of the Royal College of Emergency Medicine) Dip.Med.Tox (Diploma in Medical Toxicology) Research Interests: Dr. Caldicott specializes in emergency medicine and clinical toxicology, with a focus on illicit and novel psychotropic substances , medical cannabis , and toxicological crises . His work bridges clinical practice and public health, particularly in mass gathering medicine , disaster medicine , and medical responses to terrorism . He also explores the intersection of music festivals and emergency medical planning. Contact & Location: He can be reached at david.caldicott@act.gov.au or by phone at +61 2 6201 6111. His clinical work is based at the Emergency Department, North Canberra Hospital, 5 Mary Potter Circuit, Bruce ACT 2617.
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).
Niels Quack is an Associate Professor in Micro- and Nanosystems at The University of Sydney's School of Aerospace, Mechanical and Mechatronic Engineering. He joined the university in 2022 after serving as an SNSF Assistant Professor at EPFL (Switzerland). His roles include Academic Director of the Research and Prototype Foundry and membership in the University of Sydney Nano Institute. He holds a Dr.Sc. from ETH Zurich and an M.Sc. from EPFL. His research focuses on micro- and nanosystems engineering, integrating mechanics and photonics at the microscale. Key applications include fiber-optical communication, quantum sensing, and integrated photonics using diamond and silicon materials. Quack has pioneered silicon photonic MEMS and diamond micro-optics, with over 100 publications in journals like ACS Photonics , Optics Letters , and Nanoscale . He leads international collaborations with institutions like Ghent University (Belgium) and EPFL (Switzerland), and serves on editorial boards for IEEE Journal of Microelectromechanical Systems and SPIE Journal of Optical Microsystems . His awards include the Optica Senior Member distinction (2023) and Sydney Research Accelerator Prize (2023). Quack supervises PhD and Master's students in advanced micro- and nanosystems design, offering projects in programmable photonics and diamond-based biosensors. He actively recruits postdoctoral researchers and advises on funded projects like 'Nurturing Commercialization Opportunities for Multipoint Fiber-Optical Pressure Sensors.' His lab develops cutting-edge technologies such as vacuum-sealed silicon photonic MEMS and diamond nanopillar arrays, advancing applications in quantum sensing and optical communication systems.
Fabio Zanini is an Associate Professor at the University of New South Wales (UNSW) , leading a research group focused on computational biology , single-cell approaches , and transcriptomic analysis across diseases like severe dengue , neonatal lung disease , cancer , and marine biology . He previously conducted postdoctoral research at Stanford University (2016-2019) and earned a PhD in Bioinformatics from the Max Planck Institute for Developmental Biology and the University of Tuebingen (2015). Current Affiliation: Group leader, UNSW Previous Training: Postdoc (Stanford), PhD (Max Planck/University of Tuebingen) His research spans single-cell RNA sequencing , computational virology , developmental cell biology , and bioinformatics tool development , with recent work on: Severe dengue progression (viral-host interactions, immune signatures) Lung development (endothelial cell diversity, hyperoxia-induced injury) Cancer genomics (mutant HSC clones, AZA therapy response) Marine biology (plankton transcriptomics, evolutionary analysis) Bioinformatics (HTSeq 2.0, northstar algorithm) Recent scientific awards include grants from the Chan Zuckerberg Initiative ($270,000), NIH R01 (multiple), ARC Discovery Grant , and NHMRC Ideas Grant . Notable contributions include: Northstar - Cell classification algorithm SpectralSeq - Hyperspectral-transcriptomic integration Tabula Muris - Mouse aging atlas He has supervised research into hematopoietic stem cell regulation , lung vascular development , and autophagy in viral infections , with collaborations across Stanford , University of Sydney , and Harvard .
Dr. Kosala Gunawardane is an Associate Professor in Renewable Energy Engineering at the University of Technology Sydney (UTS), School of Electrical and Data Engineering. Previously, she held roles as Associate Professor and founding Director of the Centre of Future Power and Energy Research (CFPER) at Auckland University of Technology (AUT), New Zealand. She also served as Deputy Program Leader in the Blue Economy Corporate Research Centre in Australia. Her academic journey includes a PhD in Power Electronics (University of Waikato, 2014) and a BEng in Electronics and Telecommunications Engineering (University of Moratuwa, Sri Lanka, 2005). She is an IEEE Senior Member and former Vice Chair of the IEEE Women in Engineering NZ North Chapter. Dr. Gunawardane’s research focuses on renewable energy systems, hydrogen and fuel cells, DC microgrids, supercapacitor applications, and power electronics. She has secured significant funding from NZ government and Australian CRC grants as a primary investigator. Her work emphasizes sustainable energy solutions, including grid stability, energy storage optimization, and offshore renewable systems. Her research highlights include pioneering hybrid energy storage systems, advanced DC circuit breaker designs, and hydrogen integration in microgrids. She has published over 111 articles and edited sections on hydrogen energy conversion and management. Awards include a 2018 finalist position in the NZ Women of Influence (Science & Innovation category). Dr. Gunawardane leads funded projects such as the Blue Economy CRC’s offshore power systems and UTS’s energy transition initiatives. She actively contributes to IEEE conferences as an organizer and associate editor of the IEEE Transactions on Power Electronics. Her teaching spans circuit analysis, sustainable energy systems, and energy policy.
Professor Aniruddha Desai is a Research Professor and Director of the Centre for Technology Infusion (CTI) at La Trobe University. He holds a Bachelor’s in Industrial Electronics, a Master’s in Micro-electronics, and a PhD in Computer Science. His expertise spans microelectronics, AI, IoT, and sensor networks, with a focus on socially impactful applications like transportation, healthcare, and precision agriculture. Research Interests: Ultra-low power systems Micro-nano electronics AI/ML and edge computing IoT and sensor networks Transportation and logistics Major Projects: Led multi-million-dollar R&D programs in areas such as smart cities, energy management, and smart farming. Notable collaborations include the IIT Kanpur - La Trobe University Research Academy and the Asian Smart Cities Research and Innovation Network. Awards: Recipient of the 2016 Vice-Chancellor’s Award for Research Excellence and the 2020 Victorian Tall Poppy Award for Science. Served on advisory panels for the Australian Research Council and provided expert testimony in parliamentary inquiries. Labs/Teams: Directs the CTI, which delivers technology-based innovations to industry and government. Co-founded the Asian Smart Cities network to advance urban technology solutions.
Dr. Xiaoyi Tian is a Researcher at the School of Electrical and Computer Engineering, University of Sydney. They are affiliated with the University of Sydney Nano Institute and specialize in microwave photonics, sensor technology, and machine learning applications. Their research focuses on integrating machine learning with photonic sensors, particularly using microresonators and optical signal processing for high-resolution sensing. Key areas include microwave-photonic hybrid systems, signal processing algorithms, and sensor optimization. Dr. Tian has contributed to advancements in athermal sensors, subwavelength grating resonators, and recurrent neural networks for sensor performance enhancement. Their work spans conferences like OFC, CLEO-PR, and IEEE journals. No formal awards or student advisees are listed, though their publications reflect active collaboration in interdisciplinary research.
Associate Professor Christine Preston at the University of Sydney's Faculty of Education and Social Work specializes in primary science education with a focus on early childhood development. She maintains active classroom experience through her kindergarten science teaching and leads research on science diagrams, toy-based learning, and teacher professional development. Her work integrates embodied learning and representational pedagogies to enhance conceptual understanding in STEM subjects. Dr. Preston's research examines innovative approaches including citizen science integration, digital technologies, and adaptive curriculum design. She currently lectures in primary science and technology education, while supervising doctoral candidates exploring computational thinking and marine biology education. Her scholarly contributions emphasize practical classroom applications and teacher support resources. Award recognition includes multiple Excellence in Teaching awards (2007, 2016) and the 2001 NSW Quality Teaching Award. She maintains active membership in international science education associations including ASTA, ESERA, and NSTA, serving on editorial boards for science education journals.
Dr. Shulin (Stanley) Chen is a Lecturer at the University of Technology Sydney (UTS), specializing in antennas and applied electromagnetics. He holds a PhD from UTS (2019) and has held postdoctoral and visiting scholar positions at UTS and City University of Hong Kong. His research focuses on metasurfaces, reconfigurable antennas, and machine learning-driven design, supported by prestigious awards like the DECRA (2025) and IEEE AP-S Fellowship (2022). He serves as an Associate Editor for IEEE Transactions on Circuits and Systems II and has authored over 75 publications. His work spans advanced beam-forming antennas for 6G, frequency-controlled polarization systems, and intelligent metasurface design. Education: B.S. in Electrical Engineering, Fuzhou University (2012) M.S. in Electromagnetic Field & Microwave Technology, Xiamen University (2015) PhD in Electrical Engineering, UTS (2019) Research Interests: Metasurfaces for electromagnetic wave manipulation Reconfigurable antennas for 6G networks Machine learning in antenna design Joint communication and sensing systems Awards & Grants: DECRA (2025), TICRA-EurAAP Travel Grant (2022) Lead projects on intelligent redirecting surfaces and flood sensing (funded by Telstra, NSW Department of Planning, etc.) Labs & Teams: Active in UTS's Global Big Data Technologies Centre and collaborates with industry partners like XPOWER AI and TPG Telecom.
Dr. Yu Zhang is a Lecturer of Data Science at the School of Business, UNSW Canberra. His academic career focuses on text mining, knowledge and information management, social computing, and bibliometric analysis, with interdisciplinary applications in areas such as sustainable logistics, supply chain management, and net-zero energy solutions. Fields of Interest: Text Mining, Information Management, Social Computing, Bibliometric Analysis, Machine Learning for Information Systems, Heterogeneous Network Analysis, Data Mining for Asset Management, Sustainable Logistics, Supply Chain Management, Net-zero Energy in Green Buildings, and Transportation. Grants: Served as CI in projects like "Online health monitoring in Li-ion batteries via trustworthy AI" (ACT Government, $1.22M) and "Delivering net-zero energy buildings" (TRaCE Lab to Market, $1.05M). Awards: Best Paper Award (Runner-up) at ADMA 2024 and Excellent Paper Award at ICEBE 2024. Teaching: Coordinated courses in Data Analytics, Workforce Planning Research, Business Capstone, and Logistics Intelligence with Big Data Analysis. Supervision: Guided research on topics like federated learning for healthcare fraud detection, blockchain-based carbon offset management, and tier-based supply chain visibility. His publications span materials science and photovoltaic technologies, with a focus on thin-film solar cells and defect passivation methods. For collaboration or supervision inquiries, contact him at m.yuzhang@unsw.edu.au .
Dr. Patrick W. C. Ho is a Lecturer in the Department of Electrical & Computer Systems Engineering (ECSE) at Monash University Malaysia School of Engineering. He holds a PhD in Electronics Engineering from the University of Nottingham Malaysia Campus (2016), with research focusing on non-volatile FPGA architectures using memristors. His academic journey includes roles as a Scholarly Teaching Fellow and unit coordinator for courses like ECE2131 Electrical Circuits and ECE4063 Large Scale Digital Design. He has industry experience with Intel Microelectronics and Altera Corporation, alongside teaching A-level Physics at Methodist College Kuala Lumpur. Education: BEng (First Class Honours) in Engineering (2009) MSc in Science (2012) PhD in Electronics Engineering (2016) Research Interests: Dr. Ho specializes in memristor-based non-volatile memory systems, VLSI design, and FPGA architectures. His work bridges hardware design with emerging materials, as seen in his Q1 journal article on memristive LUTs. Collaborations with CAD-IT expand his focus into AI, image processing, and object recognition. Recent projects include studies on memristor substrate performance (2023–2026) and UAV communication reliability (2021–2024). Teaching and Industry Engagement: As ECSE’s Industrial Training Advisor and IAP representative, he actively connects academic curricula with industry needs. His teaching spans foundational engineering courses and advanced digital design modules. Labs and Collaborations: Active in CAD-IT partnerships for student FYP co-sponsorship. Research groups focus on nanotechnology, machine learning integration in UAV systems, and memristor material analysis.
