جست‌وجوی استاد و پژوهشگر

Vladimir Todorovicمشاهده پروفایل

دانشیار

• Generative Art
• Artificial Intelligence
• Immersive Storytelling
• +۷ مورد دیگر

Vladimir Todorovic is an Associate Professor and Chair of Fine Arts at the School of Design, University of Western Australia (UWA), and a Visiting Professor at the University of Arts Belgrade. His work bridges art, technology, and environmental discourse through immersive storytelling, AI-driven generative art, and experimental film. He has exhibited globally at festivals like Annecy, IFFR, and Ars Electronica, winning over a dozen awards for his innovative projects. Research interests include generative art systems, artificial intelligence aesthetics, virtual reality narratives, and the ethical implications of technology in creative practices. He has organized major events such as ISEA2008 and the Environmental Visions conference (2014), emphasizing interdisciplinary collaboration between artists, scientists, and technologists. Current projects explore AI ethics, Indigenous storytelling through extended reality, and procedural modeling in digital media. Grants: 2023: 'Illustrating Nyangumarta' (AUD 57k) from WA's Department of Local Government 2022: 'Cabinet of Algodreams' (AUD 15k) Awards: 1st Prize Experimental, 19th Athens Animfest (2024) Philip K. Dick Science Fiction Festival Award (2024) Early-Career Research Award, UWA (2022) Labs/Teams: Leads the UWA Fine Arts Lab focusing on experimental digital media and collaborates with Indigenous communities on XR storytelling initiatives.

• Precision Medicine
• Bioinformatics
• Proteomics
• +۶ مورد دیگر

Professor Jonathan Arthur is a bioinformatics expert affiliated with the University of Sydney's Charles Perkins Centre. His research focuses on precision medicine, digital health, and computational biology, particularly applying proteomics and genomic data analysis to cancer, neurosciences, and infectious diseases. He collaborates on projects involving telomere biology, cancer genomics, and biomarker discovery for multiple sclerosis. Arthur's work bridges advanced technologies like mass spectrometry and next-generation sequencing with clinical applications. Key grants include a 2014 initiative on real-time healthcare data sharing and a 2013 study on mesenchymal-epithelial transitions in development. His research also addresses cystic fibrosis pathogenesis and HIV resistance modeling. Arthur has contributed to proteomics tools like Harvest and MatCol, and teaches bioinformatics using web applications. His interdisciplinary approach spans molecular biology, computational methods, and clinical translation. Grants and collaborations highlight his role in multi-institutional projects, including NHMRC and ARC-funded studies on cancer genomics, bioinformatics infrastructure, and systems biology. His lab's work often integrates proteomic data with genomic insights to address complex biomedical challenges.

Abishek Santhakumarمشاهده پروفایل

دانشیار

• Cardiovascular Disease
• Metabolic Disorders
• Polyphenols
• +۴ مورد دیگر

Abishek Santhakumar is an Associate Professor in Pathology & Haematology at the Gulbali Institute's School of Dentistry and Medical Sciences. His research focuses on dietary antioxidants' role in reducing cardiovascular and metabolic disease risks, with emphasis on polyphenols' effects on thrombosis and platelet activity. He leads clinical trials exploring natural compounds as therapeutic alternatives and has published over 50 peer-reviewed articles. A member of the University Research Committee and editorial board roles, he actively contributes to academic governance and peer review. His research interests span cereal and pulse bioactive compounds, polyphenol characterization, and translational nutrition science. Key themes include modulation of diabetes/obesity risk factors, haemostasis regulation under oxidative stress, and bioavailability of food-derived antioxidants. Publications highlight work on rice bran antioxidants, pigmented grain polyphenols, and hemp protein hydrolysates' vascular effects. Recent studies investigate pre-analytical errors in diagnostics and the clinical implications of thrombin generation in diagnostic settings. Received 2021 Faculty Research Excellence Award for top research productivity Supervised numerous PhD/Masters/Honours students Active in curriculum development for medical laboratory science programs Labs/Teams: Involved in Gulbali Institute's Food Science and Biosecurity research programs, collaborating on projects related to functional foods and agricultural innovation.

Ratna Sahaمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Artificial Intelligence
• Image Processing
• +۶ مورد دیگر

Dr. Ratna Saha is a Senior Lecturer at Torrens University Australia, affiliated with the Business and Hospitality Centre for Artificial Intelligence Research and Optimisation (AIRO). She holds a PhD in Computer Science from Flinders University and a BSc in Computer Science and Engineering from Khulna University, Bangladesh. With over 17 years of experience in academia and industry, she focuses on machine learning, medical image analysis, AI-driven healthcare solutions, and generative AI in education. Her research bridges technical innovation with societal impact, particularly in underdeveloped regions. Education: PhD in Computer Science (2020), Flinders University, Australia (Focus: Image Segmentation with Prior Guidance in Cervical Cytology) BSc in Computer Science and Engineering (2007), Khulna University, Bangladesh (Focus: Component-Based Face Detection via SVM) Research Interests: Dr. Saha’s work spans machine learning applications in healthcare diagnostics (e.g., cervical cell segmentation), AI-driven education innovation, and industry 4.0 transformations. She emphasizes interdisciplinary approaches, integrating image processing techniques with medical pathology and leveraging generative AI to enhance learning experiences. Her recent studies explore assembly line optimization in manufacturing and social impacts of business incubation centers in developing economies. Collaborations and Impact: Her research networks span Australia, Bangladesh, and Pakistan, with projects addressing global challenges such as cervical cancer detection and skill development in IT sectors. She actively mentors HDR students in machine learning-based disease prediction and data-driven decision-making frameworks. Current projects include optimizing labor costs in assembly lines using time-study models and fostering entrepreneurial ecosystems through smart educational tools. Professional Experience: Senior Lecturer (Torrens University, 2020–present) Casual Academic (Flinders University, 2016–2020) Lecturer (Khulna University, 2012–present) Senior Software Engineer (Dohatec New Media, 2010–2012) Research Themes: Her publications reflect expertise in medical image segmentation (e.g., cervical nucleus detection), optimization algorithms (e.g., evolutionary harmony search), and socio-economic transformations via technology. Recent trends highlight her shift toward applied AI in education and industry 4.0, complementing her foundational work in computer vision and medical diagnostics. Advising and Grants: Dr. Saha supervises PhD students in machine learning and data-driven healthcare. She has secured research grants focusing on AI applications in education and healthcare, and her work is cited across interdisciplinary fields (h-index: 6, 102 citations).

Shaleeza Sohailمشاهده پروفایل

مدرس

• Artificial Intelligence
• Ethical AI
• Cybersecurity
• +۵ مورد دیگر

Dr. Shaleeza Sohail is a Lecturer in the School of Information and Physical Sciences at the University of Newcastle, serving as Program Convenor for Master of IT and Graduate Certificate of IT programs. Her research focuses on ethical, sustainable AI solutions across precision agriculture, mental health technologies, and cybersecurity. She explores federated learning for rural agriculture, AI-driven mental health support with privacy safeguards, and blockchain-enhanced cybersecurity frameworks. Education Doctor of Philosophy, University of New South Wales Master of Engineering, University of New South Wales Research Interests Her work bridges technical innovation with societal impact, emphasizing ethical AI deployment. In precision agriculture, she designs scalable solutions using federated learning to improve food security. In mental health, she develops non-invasive AI tools for early diagnosis while prioritizing patient privacy. Her cybersecurity research addresses threats in healthcare and agriculture through AI-based detection systems and blockchain integration. Grants & Funding ADVANCE Equity in Research Fellowship ($25K, 2025) RuralAI Kit Seed Grant ($15K, 2023) National Science, Technology and Innovation Plan Grant ($50K, 2014) Awards ADVANCE Equity in Research Fellowship (2025) Labs & Teams Her work involves collaborations in interdisciplinary teams, including the RuralAI project for tomato farming and sensor systems. She actively engages with national stakeholders on educational initiatives like reflective assessment in the age of generative AI.

Weijia Zhangمشاهده پروفایل

مدرس

• Causal Inference
• Machine Learning
• Weakly Supervised Learning
• +۳ مورد دیگر

Dr. Weijia Zhang is a Lecturer in Data Science and Applied Statistics at the University of Newcastle (Australia), focusing on causal inference and machine learning from ambiguous data. He holds a PhD from the University of South Australia (2018) and has held roles as Associate Professor at Southeast University (China) and Research Fellow at the University of South Australia. His research bridges causal inference and machine learning, addressing challenges in weakly supervised learning (e.g., multi-instance partial-label learning) and survival analysis under dependent censoring. Affiliations: University of Newcastle (current), Southeast University (2021–2023), University of South Australia (2018–2020) Teaching: Courses on predictive analytics, unsupervised methods, statistical decision-making, and time series forecasting Research interests include causal representation learning, weakly supervised learning from noisy/ambiguous labels, and applications in healthcare, telecommunications, and automotive industries. Key projects include developing causal methods for battery lifespan prediction with Chang'an Automobile and models for dependent censoring in survival analysis. Publications (over 30+): Focus on causal inference, weak supervision, and survival analysis. Notable contributions include CausalPLL+, MiplGp, and TEDVAE algorithms. Editor for Data Science and Engineering and reviewer for top conferences (NeurIPS, ICML, AAAI). Grants: $125k from Changan Automobile, $63.5k from National Natural Science Foundation of China, and institutional funding ($132.5k total) Awards: Top Reviewer Awards at AAAI (2021) and UAI (2022) Labs/Teams: Leads research on causal representation learning and survival analysis within the School of Information and Physical Sciences, collaborating internationally with institutions in China, Switzerland, and the US.

Gelareh Mohammadiمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Artificial Intelligence (AI)
• Computational Psychology
• +۵ مورد دیگر

Associate Professor Gelareh Mohammadi leads the Human-Centered Computing Research Group and serves as Associate Head of School (Engagement) at UNSW Sydney's School of Computer Science and Engineering. Her research focuses on accessible technologies that integrate human-computer interaction, AI, and computational psychology to enhance user-centered systems. She specializes in emotion recognition, virtual reality applications, and AI-driven design solutions. Education details are not explicitly provided in the text, but her extensive publication record indicates deep expertise in interdisciplinary fields. Her work bridges technical innovation with psychological principles, addressing challenges in healthcare, education, and interactive systems. Research interests include: Emotion analysis through VR and physiological signals Generative AI for UI/UX and creative applications Human-AI collaboration in design processes Cognitive load measurement in interfaces Alzheimer's disease biomarkers via data mining Her recent publications (2023–2025) highlight advancements in multimodal emotion recognition, stress detection systems, and AI-driven design tools. Notable contributions include the EmoStim database and DesignRepair framework. She has pioneered VR-based emotion elicitation studies and developed GAN models for facial expression synthesis. Current projects emphasize human-centric AI applications, with focus areas in healthcare technology, educational interfaces, and immersive gaming experiences. She collaborates on interdisciplinary initiatives involving psychology, biomedical engineering, and software engineering.

• Artificial Intelligence
• Bioinformatics
• Data Mining
• +۳ مورد دیگر

Professor Phoebe Chen is a Professor and Chair of the Department of Computer Science and Information Technology at La Trobe University, Melbourne, Australia since 2010. Previously, she held roles as Associate Professor at Deakin University (2003–2010) and Senior Lecturer at Queensland University of Technology (1999–2003). She earned her BInfTech (First Class Honours) and PhD in Computer Science from the University of Queensland (2000). Her research focuses on interdisciplinary areas including bioinformatics, artificial intelligence, medical image analysis, deep learning, and data mining. Notable projects include the ARC Centre of Excellence in Bioinformatics and drug design using visualization and machine learning. She has secured over 30 research grants totaling ~$8M, including 13 prestigious ARC grants. Professor Chen chairs international conferences like the Asia-Pacific Bioinformatics Conference and ACM MM, and serves on editorial boards such as IEEE Transactions on Neural Networks and Current Bioinformatics. Her work spans topics like cancer recurrence prediction via multi-omics data, medical image analysis using neural networks, and AI-driven solutions for healthcare challenges. She has published over 300 peer-reviewed papers in top journals/conferences (e.g., Nature Machine Intelligence, IEEE Transactions).

Chuck Herringمشاهده پروفایل

پژوهشگر ارشد

• Bioinformatics
• Epigenetics
• Genetics
• +۵ مورد دیگر

Chuck Herring is a Research Fellow at the University of Western Australia Medical School and the UWA Centre for Medical Research, affiliated with the Harry Perkins Institute of Medical Research. They work as a bioinformatician in Professor Ryan Lister's laboratory, focusing on gene regulatory landscapes and their role in cell development and identity, particularly within the developing prefrontal cortex. Dr. Herring's research expertise spans multiple disciplines: Bioinformatics Epigenetics Genetics Neurogenetics Transcriptomics Single-cell analysis With a particular emphasis on developing analytical tools for mapping dynamic changes in cell states, Dr. Herring employs cutting-edge single-cell resolution techniques to characterize the gene regulatory landscape of the human prefrontal cortex from gestation to adulthood. This research has provided valuable insights into human brain development and potential implications for brain-related disorders. Their work also extends to intestinal microbiome research, pancreatic development, and computational methods for single-cell data analysis. Dr. Herring's recent publications demonstrate a strong focus on: Gene regulation dynamics in brain development Microbiome-host interactions in gut inflammation Epigenetic mechanisms in cell differentiation Computational methods for single-cell data analysis Significant recognition for Dr. Herring's work includes: Harry Perkins Institute of Medical Research Safe Harbour Fellowship (2023) Australian Epigenetics Alliance Emma Whitelaw ECR Publication Award (2023) Ruth L. Kirschstein Predoctoral Individual National Research Service Award NIH F31 Fellowship (2017) As a former United States Marine with a physics background who transitioned into bioinformatics and biomedical research, Dr. Herring brings a unique interdisciplinary perspective to their work. Their research has received substantial media attention, particularly their 2022 Cell paper on prefrontal cortex development, which was covered by multiple news outlets and generated significant social media engagement.

• Wireless Communications
• Signal Processing
• Image Steganography
• +۵ مورد دیگر

Dr. Peter Vial is a Senior Lecturer at the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong. He holds a PhD in Electrical Engineering and has over three decades of experience in academia and industry. His academic journey includes a Bachelor's (1987), Master's (1997), and PhD (2009) from the University of Wollongong. Before academia, he worked at BHP Steel (1981-1991) and transitioned into teaching roles from 1992, becoming a Lecturer in 2004 and Senior Lecturer in 2022. Research Interests: Dr. Vial’s work focuses on wireless communication systems, including MIMO, spread spectrum, and ultra-wideband (UWB) technologies. He also explores signal processing applications in medical imaging (e.g., capsule endoscopy), steganography, energy harvesting, and robotics. His research integrates machine learning and embedded systems for practical solutions in healthcare, telecommunications, and sensor networks. Teaching & Supervision: Dr. Vial teaches courses in telecommunications, digital signal processing, and electronics. He has led laboratory development in embedded systems and supervised over 15 postgraduate students, including current PhD candidates in Delay Tolerant Networks (DTN), 60GHz Ad Hoc networks, and UWB channel measurements. His supervision spans topics like AI-driven sign language recognition, steganography, and energy-efficient generator design. Grants & Funding: He led an internal grant (2008-2009) developing an immersive learning platform for microcontroller education. His research has been supported by institutional funding, with outputs published in journals like Neurocomputing , Signal Processing , and IEEE Sensors . Labs & Teams: Dr. Vial has developed engineering laboratories in embedded Internet systems, telecommunications, and digital signal processing. He collaborates with industry partners and interdisciplinary teams on projects combining hardware/software systems for healthcare, energy, and robotics.

Steve Martinمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Computer Vision
• +۴ مورد دیگر

Steve Martin is a Researcher at the QUT Centre for Robotics, Queensland University of Technology. He holds a Bachelor of Mechatronics (QUT, 2009) and was a former PhD student under Professors Gordon Wyeth and Peter Corke at the QUT Cyphy Lab. Since rejoining QUT in 2016, he has contributed to the Australian Centre for Robotic Vision’s engineering projects, focusing on robotics maintenance, software development, and electrical design. His work spans diverse applications including autonomous agricultural systems for weed control, semi-automated power infrastructure inspection, and robotic coral reef monitoring. Key projects include the 'Mini Autonomous Vehicles' initiative (AOS: Kelpie) and coral reef surveillance systems. Research interests emphasize real-time perception, long-term robot navigation, and energy-efficient robotic systems. He has developed solutions for traversability mapping, proprioceptive sensing, and distributed object tracking. Notable contributions include pandemic-related ventilator design and light field camera adapters. Steve collaborates across disciplines, bridging robotics engineering with environmental and medical applications. Advising and grants: While no current advisees are listed, his PhD supervision experience at QUT and contributions to large-scale robotic projects highlight his mentorship role. He actively engages with industry partnerships, particularly in agricultural and infrastructure robotics. Labs/Teams: Core member of the QUT Centre for Robotics, contributing to cross-disciplinary research in autonomous systems and robotic vision.

Lyn Griffithsمشاهده پروفایل

استاد

• Molecular Genetics
• Genetic Analysis
• Chronic Disease
• +۵ مورد دیگر

Distinguished Professor Lyn Griffiths is a molecular geneticist at Queensland University of Technology (QUT), leading the Genomics Research Centre (GRC) and serving as Director of the Centre for Genomics and Personalised Health. She holds a PhD in Medicine from the University of Sydney. Her work focuses on identifying genes linked to chronic diseases like migraine, cardiovascular disorders, and neurological conditions, with a translational emphasis on diagnostics and therapeutics. She directs industry programs like MTP Connect and BridgeTech, promoting commercialization of medical research. Key achievements include diagnostic breakthroughs for neurogenetic disorders, three granted patents, and over $57M in research funding. Awards include a Member of the Order of Australia (2023) and the Greppi Award (2014). Research interests span molecular genetics, chronic disease, and clinical trials. The GRC utilizes genomic resources such as the Norfolk Island isolate to map disease genes and employs NATA/HGSA-accredited diagnostic testing. Recent studies address migraine mechanisms, epilepsy, and genetic variants in glaucoma. Supervised research includes projects on genetic factors in concussion, cardiovascular disease, and neurogenetic disorders. Collaborative grants include NHMRC, ARC, and international foundations. Awards highlight her contributions to genetics and neurological research, including the Sutherland Orator (2017), Queensland Academy Fellowship (2015), and finalist recognitions for leadership and innovation. Her lab’s work bridges basic science with clinical applications, emphasizing personalized health and translational impact.

• Hypersonics
• Aerodynamics
• Fluid Dynamics
• +۴ مورد دیگر

Dr. Andrew Lock is a Research Fellow at the University of Southern Queensland's Institute for Advanced Engineering and Space Sciences, specializing in hypersonics, aerodynamics, and thermal systems. He holds a BEng(Hons) from the University of Tasmania and a PhD from the University of Queensland. His research focuses on hypersonic vehicle design, aerodynamic modeling, and advanced thermal management solutions for energy systems. Key areas include co-design frameworks for hypersonic vehicles, Bayesian state estimation in free-flight measurements, and supercritical CO₂ power cycle optimization. Dr. Lock's work bridges experimental and computational methods, with contributions to optical tracking systems, trajectory analysis, and innovative cooling technologies. His recent studies address challenges in multi-mission vehicle design, shock layer radiation analysis, and nonlinear flight dynamics using the Koopman operator. He has also developed simulation tools like q1dcfd for thermofluid systems and validated low-speed rotating wind tunnel designs. His research portfolio spans over a decade, with publications on hypersonic aerodynamics, thermal engineering, and aerospace system integration. Notable projects include collaborations on Hayabusa2 entry dynamics and the development of dry cooling strategies for sustainable energy applications. While no formal advisees are listed, his interdisciplinary approach influences next-generation aerospace and energy systems.

• Biomedical Engineering
• Medical Biotechnology
• Macromolecular and Materials Chemistry
• +۳ مورد دیگر

Dr. Richard Williams is an Associate Professor in the School of Engineering at RMIT University, specializing in biomedical engineering, materials chemistry, and medical biotechnology. His work bridges engineering and life sciences, focusing on biomaterials, regenerative medicine, and nanotechnology applications. He holds a PhD and has contributed to over 69 research outputs, including peer-reviewed journals and conference papers. Research Interests : Biomedical Engineering Medical Biotechnology Macromolecular Chemistry Materials Engineering Drug Delivery Systems Recent Articles explore topics like energy systems, grid integration, and biomedical diagnostics, reflecting his interdisciplinary approach. Dr. Williams is actively involved in student supervision and industry collaborations, advancing practical solutions in sustainable energy and healthcare technologies.

• Artificial Intelligence
• Image Processing
• Genetic Programming
• +۳ مورد دیگر

Gayan Wijesinghe is a Lecturer (Education Focused) at the School of Computing Technologies, RMIT University, Australia. His research interests include Artificial Intelligence, Image Processing, Genetic Programming, and Algorithmic Reasoning. He focuses on developing educational tools to enhance programming skills and cognitive development in students. His work spans algorithm design, evolutionary computation, and applications in computer vision and medical imaging. Research outputs include contributions to genetic programming, image classification, and optimization techniques. Notable projects explore trajectory creation for code writing and parameter optimization in object detection. Collaborations have involved institutions and researchers in evolutionary algorithms and software engineering. No scientific awards or grants are explicitly mentioned in the provided texts. His academic role emphasizes education-focused research and innovation in computing technologies.