جست‌وجوی استاد و پژوهشگر

Howard Mannsمشاهده پروفایل

مدرس ارشد

• Interactional Sociolinguistics
• Conversation Analysis
• Linguistic Anthropology
• +۱۰ مورد دیگر

Howard Manns is a Senior Lecturer in the Department of Linguistics within the Faculty of Arts at Monash University, Australia. His research lies at the intersection of sociolinguistics, linguistic anthropology, and conversation analysis, with a strong focus on language, identity, and meaning-making in multilingual and multicultural interactions. His academic expertise spans several linguistic contexts, including Persian, Indonesian, sign languages, and Australian/World Englishes. He employs qualitative methodologies such as Conversation Analysis, ethnography, and interviews to explore how language shapes and reflects social identities. Interactional Sociolinguistics Conversation Analysis Linguistic Anthropology Multilingualism Intercultural Communication Language and Identity His recent publications and research projects reveal a consistent trend in understanding communication among Deafblind individuals, tactile signing, Australian vernacular expressions, and the sociocultural dimensions of slang and metaphor. These works highlight his commitment to inclusive, socially impactful linguistics that contributes to the UN Sustainable Development Goals, particularly in reducing inequalities and promoting quality education. His scientific engagement includes significant contributions to public discourse, with over 250 media appearances, especially with the ABC, where he discusses topics such as slang, mnemonics, and chiasmus. Metaphors and identities in the Australian vernacular (ARC-funded, 2021–2025) Deafblind communication: Building professional competencies (2021–2024) Talking through touch: adapting sign languages for Deafblind use (ARC, 2016–2020) Monash Intercultural Lab Summer School (2021–2023) He is an active member of the Monash Intercultural Lab and collaborates with institutions such as the National Institute of Informatics (Japan) and Victoria University of Wellington (New Zealand), reflecting his international research network and interdisciplinary approach.

Kalin Stefanovمشاهده پروفایل

پژوهشگر ارشد

• Affective Computing
• Artificial Intelligence
• Accessible Computing
• +۵ مورد دیگر

Kalin Stefanov is an ARC DECRA Fellow and Research Fellow in the Department of Human Centred Computing at Monash University. He holds a PhD in Computer Science from KTH Royal Institute of Technology and an MSc in Artificial Intelligence from the University of Amsterdam. His research focuses on Affective Computing, exploring systems that recognize and simulate human affects, with applications in social robotics, neurodiverse communication, and multimodal interaction. He has led projects on sign language translation and large-scale deepfake detection datasets. Key collaborations include work at the University of Southern California’s Institute for Creative Technologies and National Institute of Informatics. He has received accolades such as the Discovery Early Career Researcher Award (2023) and Best Paper Awards (2019, 2024). His research also contributes to UN SDG 4 (Quality Education) through accessible technologies for neurodiverse groups and visually impaired learners. Projects include the 'Active Generation of fingerspelling in Australian Sign Language' and 'Research Towards automated Australian Sign Language translation,' funded by the Australian Research Council. Stefanov’s work spans AI ethics, multimodal data platforms (e.g., OpenSense), and systems for social signal processing in human-robot interaction.

Asad Malikمشاهده پروفایل

مدرس

• Multimedia Forensics and Security
• Image Processing
• Deep Learning
• +۴ مورد دیگر

Asad Malik is a Lecturer at the School of Information Technology, Monash University, Malaysia, since December 2023. Previously, he served as an Assistant Professor in the Department of Computer Science at Aligarh Muslim University, India, for two years. He holds a Ph.D. in Information Security from Southwest Jiaotong University, China (2020), an MCA from Jamia Millia Islamia (2015), and a BSc (Hons.) in Computer Application from Aligarh Muslim University (2012). His research focuses on Multimedia Forensics and Security, Deep Learning for Cyber Security, and DeepFake detection. He is a technical member of the Asia-Pacific Signal and Information Processing Association (APSIPA) and actively reviews for top journals and conferences. His work aligns with UN Sustainable Development Goals, particularly in advancing Education and Innovation. Malik’s publications (34+ outputs) emphasize robust watermarking techniques, reversible data hiding in encrypted media, and AI-driven solutions for security and environmental challenges. Recent trends highlight innovations in deepfake detection, transformer-based audio classification, and AI applications in renewable energy modeling. He is currently accepting PhD students and collaborates on projects combining cybersecurity, digital forensics, and machine learning. No notable awards are listed, but his research contributions reflect significant academic engagement in information security domains.

Sanoop Mallisseryمشاهده پروفایل

مدرس

• Cybersecurity
• Dependable Systems Security
• Data Privacy Preservation
• +۵ مورد دیگر

Sanoop Mallissery is a Lecturer at Monash University's Malaysia School of Information Technology. He holds a PhD in Computer Science (Dependable Systems Security) from National Yang Ming Chiao Tung University, Taiwan, and has over eight years of teaching and five years of industry experience in cybersecurity. His research focuses on software security, critical infrastructure protection, AI-driven threat detection, and privacy preservation. Education : PhD in Computer Science (2024) - National Yang Ming Chiao Tung University, Taiwan Master’s in Cyber Security (2010) - An Optimized Alert Correlation Engine for Enhanced Intrusion Detection Bachelor’s in Information Technology (2006) - University of Calicut Research Interests : His work spans dependable software security, cybersecurity for industrial control systems (ICS/OT), next-gen fuzzing for vulnerability detection, and AI-driven threat mitigation. He emphasizes privacy-preserving techniques in data lifecycle management and resilient software design. Collaborations & Experience : Threat Researcher at TXOne Networks (Taiwan) for ICS/OT security Cyber Security Engineer at ITRI (Taiwan) Research Fellow at ESIGELEC—IRSEEM (France) for vehicular network security Former Assistant Professor at Manipal Institute of Technology, India Grants & Labs : Currently integrating research into teaching at Monash Malaysia while exploring emerging cybersecurity challenges. Actively collaborates on UN SDG-related education and infrastructure security projects.

Leibo Liuمشاهده پروفایل

پژوهشگر ارشد

• health data science
• artificial intelligence
• machine learning
• +۳ مورد دیگر

Leibo Liu is a Research Fellow at the Centre for Big Data Research in Health (CBDRH) at the University of New South Wales (UNSW) Sydney and a Data Scientist at The George Institute for Global Health (TGI). Education: PhD in Big Data Research in Health from Centre for Big Data Research in Health (CBDRH), University of New South Wales (UNSW), Australia Research Interests: Liu specializes in applying natural language processing (NLP) and deep learning to extract information from unstructured health data, particularly clinical notes. His key research areas include de-identification and clinical coding of free-text data from electronic medical records (EMRs), and predictive modeling using brain imaging data with convolutional neural networks and transformer-based architectures. He developed an end-to-end deep learning framework for removing personally identifiable information (PII) from health data, implemented in the Cardiac Analytics and Innovation (CardiacAI) project. Current Projects: Next-generation Clinical Registry project at CBDRH Outcome PredicTion in IntraCerebral Hemorrhage Study (OPTICS) at TGI (leads machine learning model development) Professional Background: With expertise spanning machine learning, software engineering, and big data analysis, Liu brings a unique combination of skills to health data science. His publication record includes 1 Book Chapter, 9 Journal articles, 1 Conference Paper, 1 Conference Abstract, and 6 Preprints.

James Kesbyمشاهده پروفایل

مدرس

• Cognitive Neuroscience
• Psychiatry
• Neurobiology
• +۵ مورد دیگر

Dr. James Kesby is a Lecturer at the School of Biomedical Sciences , University of Queensland, with a focus on developmental neurobiology and psychosis research. He is affiliated with the Queensland Centre for Mental Health Research and leads a cross-species research program connecting corticostriatal circuitry to decision-making deficits in schizophrenia. Research Interests: Corticostriatal circuitry in psychosis Decision-making and cognitive flexibility Translational rodent-human models Dopamine and schizophrenia Developmental neurobiology Neurochemical mechanisms of cognitive deficits Article Trends (2025–2023): Recent studies focus on corticostriatal interactions in reversal learning, dopamine modulation in cognitive flexibility, and translational paradigms for psychosis. Articles from 2022–2021 extend findings to clinical schizophrenia subtypes and novel therapeutic targets like GLP-1RAs. Education and Academic History: Dr. Kesby completed his PhD in 2010 at University of Queensland with Prof. Darryl Eyles and A/Prof. Thomas Burne, studying developmental vitamin D deficiency and dopamine systems in schizophrenia models. Research Infrastructure: His work operates within the Developmental Neurobiology Research Stream at the Queensland Centre for Mental Health Research, integrating clinical and preclinical methodologies.

Eric Howardمشاهده پروفایل

پژوهشگر ارشد

• Quantum Physics
• Machine Learning
• Gravitational Waves
• +۴ مورد دیگر

Dr. Eric Howard is a Research Fellow at Macquarie University , affiliated with the School of Engineering , School of Mathematical and Physical Sciences , and School of Computing . His research spans interdisciplinary domains at the intersection of quantum physics, machine learning, and AI-driven systems. Key research themes include: Quantum cryptography for Industry 4.0 security Machine learning in IoT temperature sensing Adversarial AI in cybersecurity 6G wireless communication optimization Quantum information processing Deep learning for data imputation Recent publications demonstrate a focus on emerging technologies, with articles on quantum Bayesian inference , 6G signal processing , and smart city IoT systems . His collaborative work extends to blockchain-enabled supply chain visibility and generative AI applications in programming. Research collaborations span institutions in India (AIP Publishing) and Australia, with technical contributions to quantum dynamics, neural network applications, and nanosensor development.

Oliver Griffithمشاهده پروفایل

مدرس ارشد

• The Evolutionary Origins of Pregnancy
• Transposons and the Evolution of Complex Organs
• Maternal-Fetal Communication in Reptiles and Mammals
• +۱ مورد دیگر

Dr. Oliver Griffith is an evolutionary biologist and Senior Lecturer at the School of Natural Sciences, Macquarie University, holding an Australian Research Council Future Fellowship. His research bridges genomics, cell biology, and ecological physiology to investigate the evolution of complex traits, particularly pregnancy mechanisms in reptiles and mammals. Education: PhD from University of Sydney, Postdoctoral Fellowship at Yale University, ARC DECRA at University of Melbourne Research Interests: Key areas include the evolutionary origins of pregnancy, transposon-driven organ evolution, maternal-fetal communication, and conservation genomics. His work reveals how inflammatory pathways enabled embryo implantation and how 'junk DNA' drives placental innovation. Scientific Awards: Australasian Evolution Society’s Early Career Researcher Award (2019) Faculty Excellence Award - Teaching (2021) Herpetologists League Graduate Research Prize (2012) Jabez King Heydon Memorial Prize (2016) Grants & Collaborations: Leading national and international genomic initiatives, including a 2025-2029 ARC Future Fellowship project on transposons and placental evolution. Actively contributes to academic committees and public science communication.

Stuart Jamesمشاهده پروفایل

مدرس

• Music Composition
• Immersive Audio and Video
• Electroacoustic Performance Practice
• +۵ مورد دیگر

Dr. Stuart James is a Lecturer in the Composition and Music Technology program at the Western Australian Academy of Performing Arts , part of Edith Cowan University . His career spans composition, sound design, performance, and music technology development, with a focus on integrating acoustic and electronic media. Education: PhD (2015) in Spatial Audio and Synthesis Master of Arts in Creative Arts (2006) Bachelor of Music with First Class Honours (2001) Certificate in Jazz (1995) Research Interests encompass Music Composition with a blend of acoustic and electronic instruments, Immersive Audio-Visual Systems , Wave Terrain and Spectral Synthesis , and Digital Signal Processing for performance. His work explores Electroacoustic Performance Practice and Networked Music Environments . Publication Trends reflect a focus on experimental composition , interactive notation (notably iPad-based systems like the Decibel ScorePlayer), and spatial audio techniques . Collaborative projects with ensembles such as Decibel and artists like Erin Coates and Louise Devenish highlight his interdisciplinary approach. Scientific Awards include the ASME Young Composers' Competition State Finals Winner , the Dorothy Ransom Composition Prize , and nominations for Australian Music Centre Awards . Professional Contributions include founding membership in the Decibel Ensemble , managing a commercial recording studio for artists like ShockOne, and developing networked music notation software . He has supervised PhD projects on topics like meditative sonic praxis and timbre analysis .

• Wireless Communication
• Information Theory
• Error Correction Coding
• +۳ مورد دیگر

Dr. Min Qiu is a Postdoctoral Research Associate at the University of New South Wales (UNSW), with a research focus on coding theory, information theory, and wireless communication systems. He received his Ph.D. in Electrical Engineering from UNSW in 2019 and a B.E. (Hons.) in Electronics and Telecommunications Engineering from the Australian National University in 2012. His work addresses fundamental limits of communication systems and designs reliable networks and storage solutions under unreliable conditions. Dr. Qiu's research spans bandwidth-efficient coded modulation, delay-Doppler communications, finite blocklength coding, lattice coding for interference management, and joint sensing and communications. He has served as a reviewer for over 15 journals and conferences, including IEEE Transactions on Communications and the IEEE International Symposium on Information Theory. Key scientific contributions include awards for exceptional peer-review service and grants such as the 2021 ECA EDI Seed Grant. He is affiliated with IEEE Communication Society, IEEE Information Theory Society, and Engineers Australia.

Wen Huمشاهده پروفایل

استاد

• Cyber-physical systems
• Internet of Things
• Sensor network systems
• +۳ مورد دیگر

Professor Wen Hu is a distinguished academic at the School of Computer Science and Engineering at the University of New South Wales (UNSW), where he holds a professorship focusing on cutting-edge research in cyber-physical systems and the Internet of Things (IoT). With extensive experience in both academia and industry, Professor Hu has established himself as a leading researcher in sensor network systems, low-power communications, security, and compressive sensing. His work bridges theoretical research with practical applications, as evidenced by his active commercialization efforts through roles as Chief Technology Officer at Parking Spotz and former Chief Scientist at WBS Tech. Professor Hu's research interests span multiple domains within cyber-physical systems and IoT. His work particularly focuses on low-power wireless communications , sensor network security , compressive sensing techniques , and novel applications of IoT technologies . His research group explores how these technologies can be applied to solve real-world problems in areas such as smart buildings, environmental monitoring, and human-computer interaction. The research integrates hardware design, communication protocols, security mechanisms, and data analytics to create efficient and robust IoT systems. Professor Hu's publication record demonstrates a consistent focus on advancing the state-of-the-art in wireless sensor networks and IoT. His recent work shows increasing integration of machine learning techniques with traditional sensor systems, exploring applications in areas ranging from healthcare monitoring to agricultural technology. There's a clear trend toward more sophisticated signal processing approaches, particularly using mmWave technology and visible light communications, while maintaining the core focus on energy efficiency and security that has characterized his earlier work. CSIRO Office of Chief Executive (OCE) Julius Career Award (2012-2015) Professor Hu has successfully secured multiple research grants from the Australian Research Council, CSIRO, and industry partners, enabling his team to pursue ambitious research projects with both theoretical significance and practical applications. His editorial leadership as Editor-in-Chief of ACM TOSN and organizational roles in major conferences like CPS-IoT Week 2020 and ACM/IEEE IPSN 2023 demonstrate his significant contributions to the research community. As a senior member of both ACM and IEEE, he actively mentors students and early-career researchers while fostering collaborations across academia and industry. Professor Hu leads a vibrant research group at UNSW that combines theoretical research with practical implementation. His team works closely with industry partners to ensure research relevance and facilitate technology transfer. The group maintains strong connections with international research communities and participates in collaborative projects that address global challenges in IoT and cyber-physical systems.

• Data Mining
• Data Science
• Data Analytics
• +۴ مورد دیگر

Professor Geoff Webb is a world-leading data scientist at Monash University , serving as Director of the Monash University Centre for Data Science within the Faculty of Information Technology . His research focuses on leveraging data science to enable evidence-based decision making and derive actionable insights through artificial intelligence, machine learning, and big data analytics. Core expertise in data mining , bioinformatics , and computational biology Developed Magnum Opus software and contributed to the Weka machine learning workbench Recipient of the Eureka Prize for Excellence in Data Science and leadership roles in major data mining conferences Research Interests Professor Webb's work spans artificial intelligence , machine learning , and data analytics , with a focus on black-box user modelling , interactive data analytics , and statistically-sound pattern discovery . His recent publications highlight advancements in Bayesian networks , time series analysis , and genomic data interpretation , demonstrating his interdisciplinary impact. Scientific Contributions AI in healthcare : EHR-ML framework for clinical records analysis Biological applications : KcatNet for enzyme prediction, PFresGO for protein function Data mining innovations : OPUS search algorithm, proximity forest techniques As a technical adviser to data science company Froomle , he bridges academic research with real-world applications. His work has been recognized through numerous research awards and leadership as Editor-in-Chief of Data Mining and Knowledge Discovery for a decade.

• Quantum computation
• Quantum information, computation and communication

Professor Zhengfeng Ji is an Adjunct Professor at the Centre for Quantum Software and Information within the Faculty of Engineering and Information Technology at the University of Technology Sydney. His research focuses on quantum computation, quantum information theory, and quantum communication. Quantum complexity theory Quantum algorithms Quantum network optimization Entanglement characterization Recent publications highlight advancements in quantum network routing frameworks and quantum proof systems. He has secured multiple grants including the Sydney Quantum Academy Postdoctoral Fellowship and ARC Discovery Projects. Quantum Exponential Time Hypothesis Quantum PCP Conjecture Post-quantum Cryptographic Protocols Scientific awards include: SQA Scholarship Sydney Quantum Academy Postdoctoral Fellowship SUSTech Scholarship

• Artificial Intelligence
• Machine Learning
• Federated Learning
• +۸ مورد دیگر

Guodong Long is an Associate Professor at the University of Technology Sydney (UTS) in the Faculty of Engineering and Information Technology. He joined UTS in 2010 and earned his PhD there in 2014. His research focuses on federated learning, trustworthy AI, and pre-trained foundation models with applications in healthcare, IoT, and social media. PhD in Artificial Intelligence, University of Technology Sydney (2014) Leading the Foundation Model and Federated Learning research group (https://www.fmfl.group/) His work addresses challenges in frequency transformation for time series, privacy-preserving healthcare analytics, and spatio-temporal traffic forecasting. He has published extensively at top AI conferences like AAAI, ICLR, and NeurIPS, with significant citation impact (4,682 citations in 2022). Collaborations with industry partners have secured over $4M in external funding. Recent publications emphasize federated foundation models (ICLR'25), privacy-preserving recommendation systems (WWW'25), and adaptive time series analysis. His research integrates domain knowledge and graph learning for multivariate time series imputation and traffic prediction. Dr. Long actively contributes to academic leadership as General Co-Chair for WebConf 2025, Program Co-Chair for AI conferences, and reviewer for top venues. He supervises PhD and master's students and welcomes research visitors for extended collaborations.

• Data Science
• Artificial Intelligence
• Healthcare Analytics
• +۳ مورد دیگر

Dr. Andrew Peng is a Lecturer (Research) at the Australian Artificial Intelligence Institute (AAII) within the Faculty of Engineering and Information Technology at University of Technology Sydney (UTS), Australia. With dual PhDs from UTS (2015) and Beijing Institute of Technology (2013), he has published 45 peer-reviewed papers across top venues like IEEE ICDM, COLING, and Frontiers in Molecular Biosciences. Education: Dual PhD (2013-2015) from Beijing Institute of Technology and University of Technology Sydney His research focuses on Data Science , Artificial Intelligence , and Healthcare Analytics , addressing challenges in medical data analysis, unstructured clinical text processing, and federated learning frameworks. Recent publications explore: Deep graph clustering for community detection Privacy-preserving medicine shortage detection via social media Time-aware medication recommendation using dynamic treatment regimes Knowledge tracing enhancements for online education Contrastive learning approaches for ICD coding Hypergraph-based sequential diagnosis prediction Dr. Peng has secured over AUD $1M in external research grants and serves as Subject Coordinator for undergraduate/postgraduate courses. He contributes to professional leadership through roles as Web Chair at AJCAI 2021 and ADMA 2021, PC member for major conferences, and reviewer for journals like NeurIPS and AAAI. His work spans collaborations with universities, industry, and government agencies.