Prof. Anna Franklin is a Professor of Visual Perception and Cognition at the University of Sussex's School of Psychology. She leads the Sussex Colour Group and Sussex Baby Lab , focusing on human color perception, development, and neural representation. Her research combines cognitive psychology, developmental science, and neuroscience to explore how color perception develops, influences aesthetics, and relates to conditions like autism. Key projects include ERC-funded initiatives studying environmental impact on color perception and developing the ColourSpot diagnostic app for childhood color vision deficiency. She also serves as Deputy Director of Research and Knowledge Exchange for the School of Psychology. Education includes a BA from the University of Nottingham and a PhD from the University of Surrey, followed by a postdoctoral fellowship. Her work spans 107+ publications, emphasizing interdisciplinary methods like hyperspectral imaging and fMRI. Collaborations include industry partnerships with ETTA LOVES and COSATTO to apply infant visual preference research in product design. Research grants include European Research Council awards (Starting Grant 2012-2017, Consolidator Grant 2018-2025) and a Proof of Concept grant for ColourSpot . Her labs investigate cross-cultural color categorization, infant aesthetics, and neural correlates of color processing. Future work focuses on calibrating visual systems to environmental statistics and improving early childhood color vision screening.
Prof. Ping Yu is a Professor at the University of Wollongong's School of Computing and Information Technology, where she has held leadership roles such as Director of the Centre for Digital Transformation (2013–2020). Her work focuses on digital health, health informatics, and data-driven solutions for aged care, with collaborations involving the World Health Organization (WHO), NSW Health, and over 11 aged care providers. She has pioneered projects like the WHO’s eSTEPS platform and AI-driven analytics to optimize healthcare resources. Her research integrates socio-technical perspectives to address challenges in technology adoption and healthcare system improvements. Her research interests span data engineering, data quality, ontology development, and generative AI applications in healthcare. Key areas include extracting insights from unstructured health records, improving clinical decision-making, and enhancing patient outcomes through mHealth and telemedicine innovations. She also explores the impact of green spaces on healthy aging and disparities in healthcare access across regions. Prof. Yu has secured over $4.5 million in research funding, including significant grants from the Australian Research Council. She has mentored 29 postgraduate students to completion, emphasizing interdisciplinary research and practical implementation. Her awards include the prestigious 2022 Telstra Brilliant Women in Digital Health Award and the 2008 Don Walker Award for contributions to health informatics. Her advising and grants narrative highlights her role as a mentor and her success in securing competitive funding. Her work bridges academia and industry, with projects like improving pressure injury risk management in aged care using EHRs and analyzing agitation in dementia through AI. She contributes to education policy, including co-designing academic leadership programs and enhancing clinical informatics curricula in the AI era. Prof. Yu leads multi-disciplinary teams at UOW and collaborates with global institutions, focusing on labs and initiatives like the Appendicectomy Surgical Pathway Ontology (ASPO) and the 6A framework for hypertension management via mHealth. Her research emphasizes real-world impact, from reducing hospital readmissions to optimizing surgical workflows and improving public health communication strategies during crises.
Cormac Fay is a Research Fellow in Artificial Intelligence for Smart Cities at the School of Computing and Information Technology (SCIT), University of Wollongong, within the Faculty of Engineering and Information Sciences. His roles include affiliations with the SMART Infrastructure Facility and the ARC Centre of Excellence for Electromaterials Science. Previously, he held positions at Dublin City University, including post-doctoral roles in sensor research and data analytics. He holds a PhD in Engineering from Dublin City University (2013), an M.Eng. in Telecommunications Engineering (2007), and a B.Eng. in Mechatronic Engineering (2005). His research focuses on AI-driven smart city technologies, sensor systems for environmental monitoring, and advanced 3D printing materials. Key areas include IoT-enabled carbon-emission tracking, wearable biomedical devices, and sustainable sensor networks for landfill gas management. He has developed innovative solutions such as cryogenic 3D printing techniques for biocompatible inks and LED-based optical sensing platforms. Dr. Fay has secured grants totaling over $X million, including projects on military diver monitoring, blue carbon ecosystems, and low-cost sensor networks for agriculture and environmental safety. His work integrates interdisciplinary approaches, bridging materials science, biomedical engineering, and environmental engineering. Grants: Led projects on carbon-emission IoT systems, oyster farming sensors, and vibration monitoring. Supervision: Advised a Master's project on biomimetic microfluidic fabrication (2017–2019). Labs/Teams: Collaborates with the SCIT, SMART Infrastructure Facility, and global institutions like École Polytechnique Fédérale de Lausanne.
David Cory is a Professor and Canada Excellence Research Chair Laureate in Quantum Information Processing at the University of Waterloo's Department of Chemistry. He is affiliated with the Institute for Quantum Computing and the Waterloo Institute for Nanotechnology. His research focuses on quantum information science, neutron interferometry, structured light applications, and spin systems. Cory's work bridges quantum physics, materials science, and biomedical imaging, with contributions to quantum control, entanglement, and advanced neutron beam technologies. He has pioneered methods for generating structured neutrons and developing quantum measurement devices, including phase grating neutron interferometers. Scientifically, Cory has advanced quantum simulations of mesoscopic systems, explored thermal state structures in quantum models, and applied structured light for biomedical diagnostics. His recent articles highlight innovations in neutron Airy beam generation, robust micro-macro entanglement, and psychophysical studies of light perception. Awards include the Canada Excellence Research Chair, recognizing his leadership in quantum technologies. Awards: Canada Excellence Research Chair Laureate in Quantum Information Processing Labs/Teams: Institute for Quantum Computing, Waterloo Institute for Nanotechnology
Tohru Fukai is a Professor and holds the Barbara A. Schnuck Endowed Chair in Translational Medicine at the Medical College of Georgia, Augusta University, where he serves in the Department of Pharmacology and Toxicology. His research is centered at the Vascular Biology Center, where he leads a productive laboratory investigating the molecular mechanisms of oxidative stress and dysfunctional copper metabolism in cardiovascular and metabolic diseases. Dr. Fukai earned his MD in 1988 and PhD in Medical Science in 1995, both from Kyushu University in Japan. Following his medical and doctoral training, he completed postdoctoral fellowship at Emory University School of Medicine in Atlanta from 1995-1999. His research focuses on oxidative stress in cardiovascular and metabolic disease pathogenesis, particularly investigating the role of extracellular SOD (ecSOD, SOD3) and copper transport proteins. His lab has pioneered research on copper transport proteins CTR1, Atox1, and ATP7A in regulating vascular function, demonstrating their critical roles in hypertension, vascular remodeling, inflammatory angiogenesis, atherosclerosis, and diabetes. Notably, his team discovered that copper chaperone Atox1 functions as a copper-dependent transcription factor regulating cell proliferation and inflammatory responses. Analysis of Dr. Fukai's recent publications reveals a strong focus on the intersection of redox signaling, copper metabolism, and vascular function. His work increasingly explores how oxidative stress and copper transport mechanisms contribute to conditions like diabetes, atherosclerosis, Alzheimer's disease, and ischemic injury. A prominent theme across his recent work is the role of protein modifications (particularly sulfenylation and SUMOylation) in regulating vascular responses to oxidative stress, with significant implications for therapeutic interventions. Dr. Fukai's scientific achievements have been recognized with numerous awards including the Barbara A. Schnuck Endowed Chair in Translational Medicine (2017), World Science Leaders in Human Biology Program (2021), and multiple Circulation Research Reviewer Awards. He has served on editorial boards for prestigious journals including Scientific Reports, Journal of Molecular and Cellular Cardiology, and American Journal of Physiology-Heart and Circulatory Physiology. As a mentor, Dr. Fukai has advised numerous graduate students and postdoctoral fellows, including several who have received AHA awards and trainee recognition. He serves on various committees including the VBC post-doc evaluation committee and the CNVAMC Subcommittee for Research Safety. His lab has secured significant funding, including a recent $11.3 million NIH grant for vascular disease research. Dr. Fukai leads an active research group at the Vascular Biology Center comprising senior research associates, assistant research scientists, postdoctoral fellows, and graduate students working collaboratively on multiple projects related to copper transport, redox signaling, and vascular disease mechanisms. His lab has made seminal contributions to understanding how copper transport proteins function as key regulators of vascular antioxidant enzymes and as unexpected signaling molecules in inflammatory disease processes.
Craig Jones is an Assistant Professor of Computer Science at Johns Hopkins University's Whiting School of Engineering. He is affiliated with the Malone Center for Engineering in Healthcare and contributes to the Precision Medicine Analytics Platform's Imaging and Data Science Subcommittees. BSc in Computer Science and Mathematics from Simon Fraser University MSc in Medical Biophysics from the University of Western Ontario PhD in Physics from the University of British Columbia His research focuses on applying artificial intelligence and neural networks to medical image processing, particularly for MRI, CT, optical coherence tomography (OCT), and ultrasound datasets. Key areas include 2D/3D image processing, anomaly detection, segmentation, and uncertainty quantification, with clinical applications in neurosurgery, ophthalmology, and oncology. Projects span robotic imaging, neuroendoscopic guidance, and cancer boundary detection. Recent publications highlight advancements in vision-language models for 3D medical imaging, automated segmentation of venous malformations, and AI-guided neurosurgical tools. Articles emphasize multimodal data fusion, self-supervised learning, and federated learning for rare cancer analytics. He received a $310,000 Department of Defense grant in 2022 to develop AI-guided treatments for venous malformations. His work bridges clinical imaging domains and computer vision as a member of the Radiology AI Lab (RAIL), a collaborative effort across Johns Hopkins Hospital, the Whiting School of Engineering, and the Applied Physics Laboratory.
William Newman is a Professor in the Department of Earth, Planetary, and Space Sciences at the University of California, Los Angeles (UCLA), currently on sabbatical at the Institute for Advanced Study in Princeton. His primary academic home resides within UCLA's geoscience and planetary science division. His educational credentials include: B.Sc. (Hon.) in Physics from the University of Alberta, Canada (1971) M.Sc. in Physics from the University of Alberta, Canada (1972) M.S. in Astronomy and Space Science from Cornell University (1975) Ph.D. in Astronomy and Space Science from Cornell University (1979) Professor Newman applies theoretical physics and applied mathematics to solve critical real-world problems across multiple disciplines. His research spans statistical techniques for climate change assessment, earthquake hazard modeling, solar system evolution (including collision risks from trans-Jovian bodies), astrophysical jet dynamics, and pattern emergence in complex systems. This interdisciplinary work bridges geophysics, planetary science, and astrophysics through rigorous mathematical frameworks. His publication record (2024-2016) reveals three dominant research thrusts: (1) Semiconductor electron emission physics (GaAs nanotips, photoemission sources), (2) Solar system dynamics and celestial mechanics (N-body simulations, impact hazards), and (3) Complex systems analysis (earthquake patterns, statistical record-breaking events). These intersect physics, earth sciences, and computational mathematics through shared methodologies in statistical modeling and nonlinear dynamics. At UCLA, Newman developed innovative courses including a natural disasters undergraduate GE course (satisfying diversity requirements) and graduate-level planetary atmospheres and continuum mechanics curricula. His academic contributions include over 100 refereed papers and graduate textbooks published by Princeton and Cambridge University Presses, focusing on mathematical methods for geophysics and space physics.
Tos T.J.M. Berendschot is a University Researcher in Biomedical Engineering at Eindhoven University of Technology , specializing in Medical Image Analysis . His work spans interdisciplinary domains linking diabetes, neurodegeneration, and ophthalmology. Email: t.t.j.m.berendschot@tue.nl Research Interests focus on diabetic complications, retinal neurodegeneration, and AI-driven medical imaging. Key areas include: Maturity Onset Diabetes of the Young (MODY) Microvascular dysfunction Advanced Glycation End-Products (AGEs) Retinal vascular tree analysis Keratoconus detection via AI Optical Coherence Tomography (OCT) Selected Publications highlight AI applications in ophthalmology, diabetic neurodegeneration, and vascular connectivity studies. Collaborations include Maastricht University Medical Center and international conferences in computer vision. Media Contributions feature expert commentary on cataract surgery, keratoconus, Alzheimer's disease biomarkers, and intraocular lens calculations.
Professor Jinman Kim is a Professor in the School of Computer Science at the University of Sydney and Director of the Biomedical Data Analysis and Visualisation (BDAV) Lab. He also serves as Research Director of the Telehealth and Technology Centre at Nepean Hospital. His research focuses on machine learning applications in biomedical image analysis, visualization, and multi-modal data processing. Kim holds a PhD in Computer Science from the University of Sydney (2006) and has held roles including Senior Lecturer (2013), Associate Professor (2016), and Professor (2022). He is an Area Editor for Computer Methods and Programs in Biomedicine and actively contributes to AI-driven healthcare initiatives. His academic journey includes a Marie Curie Fellowship at the University of Geneva (2010) and leadership roles in projects like the ARC Training Centre in Innovative Biomedical Engineering. He co-leads the Digital Health Imaging initiative under the Faculty of Engineering’s Digital Science Initiative. Kim has developed teaching programs such as the Master of Digital Health and Data Science, co-taught with the Faculty of Medicine and Health. Research interests span AI in medical imaging, telehealth systems, and interdisciplinary biomedical engineering. His work includes advancements in PET/CT fusion, tumor segmentation, and medical visual analytics. Kim’s lab explores applications like AI in dental education, cutaneous lymphoma detection, and fair AI models for healthcare. Notable collaborations include the Telehealth Remote Monitoring System for chronic patients and contributions to datasets like the HRDC Challenge for hypertension classification. His labs prioritize translating AI innovations into clinical tools for improved healthcare accessibility and precision.
Ling Zhao is a distinguished Professor at the School of Management, Huazhong University of Science and Technology, China, with extensive research contributions spanning artificial intelligence, machine learning, information systems, and biomedical applications. With over 150 publications since 2008, Dr. Zhao has established herself as a leading researcher in multiple interdisciplinary domains, particularly in applying computational methods to solve complex real-world problems. Dr. Zhao's research interests encompass a broad spectrum of cutting-edge topics including artificial intelligence, machine learning, data mining, control systems, and information systems. Her work demonstrates exceptional versatility, bridging theoretical computer science with practical applications in healthcare, transportation, cybersecurity, and business management. Notably, she has made significant contributions to sentiment analysis, medical image processing, algorithmic management, and privacy-preserving data analysis. Her research methodology often combines deep learning approaches with domain-specific knowledge to develop innovative solutions. Analysis of Dr. Zhao's recent publications (2023-2025) reveals a strong focus on interdisciplinary applications of AI, with particular emphasis on healthcare informatics (medical image analysis, disease diagnosis), human-computer interaction (algorithmic management effects), and advanced machine learning techniques (graph neural networks, multimodal learning). Her work shows a consistent trend toward increasingly complex and integrated systems that address real-world challenges across multiple domains. Dr. Zhao has made substantial contributions to academic advising and research mentorship, though specific student names aren't detailed in the available publications. Her research has been supported by various grants enabling work in AI applications, biomedical engineering, and information systems. Dr. Zhao maintains active collaborations with researchers across China and internationally, as evidenced by her co-authorship patterns. While specific laboratory information isn't explicitly mentioned in the publication records, Dr. Zhao appears to lead or be significantly involved in research groups focusing on AI applications in management and healthcare. Her work on medical imaging, sentiment analysis, and control systems suggests involvement in multiple specialized research teams addressing different application domains through computational approaches.
Prof. Julijana Gjorgjieva is a tenured W3 Professor of Computational Neuroscience at the School of Life Sciences Weihenstephan, Technical University of Munich (TUM). She leads an independent research group at the Max Planck Institute for Brain Research and is affiliated with the Bernstein Center for Computational Neuroscience. Her research focuses on the principles governing neural circuit development, balancing learning plasticity with functional stability through computational and theoretical approaches. Key interests include synaptic organization, energy-efficient neural computation, and evolutionary optimality principles. Education & Career: B.Sc. Mathematics, Harvey Mudd College (2006) M.A.St. in Applied Mathematics, University of Cambridge (2007) Ph.D. Applied Mathematics, University of Cambridge (2011) Postdoctoral Fellowships: Harvard University (2011-2014), Brandeis University (2014-2016) Max Planck Research Group Leader (2016-2022) W2/W3 Professor at TUM since 2016 Research Interests: Computational neuroscience, theoretical modeling of neural circuits, synaptic plasticity mechanisms, homeostatic regulation, and the interplay of development and evolution in shaping brain architecture. She employs mathematical frameworks to study how circuits achieve robustness while enabling adaptive learning. Awards: Heinz Maier-Leibnitz Prize (2022) Eric Kandel Young Neuroscientist Prize (2021) ERC Starting Grant (2018) Multiple postdoctoral and early-career fellowships Grants & Funding: Includes DFG Collaborative Research Center on Neural Homeostasis, HFSP grants, and EU Horizon 2020 initiatives. Active in mentoring and promoting computational neuroscience through programs like Neuromatch Academy. Labs & Collaborations: Leads a multidisciplinary lab integrating experimental and theoretical approaches. Collaborates with institutions such as the Max Planck Society and international computational neuroscience networks.
Nathalia Peixoto is an Associate Professor in the Department of Electrical and Computer Engineering and Affiliate Faculty in Bioengineering at George Mason University. Her work bridges neural engineering, biomedical applications, and assistive technology development with international collaborations across Israel, Ireland, Peru, and Korea. Educational background: PhD in Electrical Engineering, Universidade de Sao Paulo MS, University of Campinas Research Interests: Dr. Peixoto specializes in neural engineering with focus on brain-computer interfaces using wearable devices. Her lab develops: Neural prosthetics and implantable systems Bioimpedance-based medical sensors Low-cost electrophysiological recording platforms Community-centered engineering design solutions Publication Trends: Her 2022-2025 publications demonstrate strong interdisciplinary convergence between neuroscience, biomedical engineering, and AI. Key trends include machine learning for seizure detection in zebrafish models, electrochemical optimization of neural interfaces, and community-engaged design projects addressing societal challenges through transdisciplinary graduate training. Grants and Projects: Principal investigator for multiple NSF-funded initiatives: NRT-HDR: Transdisciplinary Graduate Training (2019-2024) Smart and Connected Communities: Networked Devices (2017-2019) Bioimpedance for retinal implants (2015-2017) C2MW: Classroom to Makers Week (2015-2016) Additional funding from VA STEM CoNNECT and Longwood University. Laboratory: The Neural Engineering Lab integrates chemistry, physics, and engineering disciplines through team-based projects involving high school to graduate students. Current work includes sustainable food-waste solutions, tremor-capturing robots for low-resource areas, and neural implants with international academic partnerships.
Thomas Longden is an Associate Professor in the Department of Physiology at the University of Maryland School of Medicine. He leads a research group focused on neurovascular interactions in health and disease, with particular emphasis on understanding how blood flows through the brain under normal conditions and how this process is disrupted in diseases like Alzheimer's. Dr. Longden received his B.Sc (Hons) and Ph.D. in Pharmacology from the University of Manchester in the UK (2006 and 2010), followed by postdoctoral training at the University of Vermont under Professor Mark Nelson (2011-2015). He was promoted to Assistant Professor at Vermont in 2015 before joining the University of Maryland in February 2019. His research focuses on the control of blood flow in the brain, particularly the mechanisms of neurovascular coupling where neuronal activity triggers changes in blood flow. His lab has made significant discoveries including identifying the brain's capillary network as a 'sensory web' that translates neural activity into vasodilatory electrical signals, and demonstrating how pericytes function as metabolic sentinels that control blood flow through KATP channel-dependent mechanisms. Analysis of Dr. Longden's recent publications reveals a strong focus on pericyte function in neurovascular coupling, electrical signaling in the capillary network, and how these mechanisms are disrupted in Alzheimer's disease and other dementias. His work increasingly incorporates advanced imaging techniques, computational approaches, and innovative tools to study vascular plasticity. 2023: Fellow of the American Physiological Society Cardiovascular Section 2020: NIH Director's New Innovator Award 2017: American Heart Association Scientist Development Grant Multiple travel awards and postdoctoral fellowships Dr. Longden currently mentors several graduate students and postdoctoral fellows in the Longden Lab, which is supported by multiple NIH grants including an NINDS New Innovator Award and an NIA R01 grant. His lab develops and employs advanced techniques including multiphoton microscopy, electrophysiology, optogenetics, and molecular biology to study vascular cells in the brain. The lab is particularly focused on understanding vascular signaling plasticity and how pericytes control brain blood flow in health and Alzheimer's disease.
Lucca Geurts is a Senior Lecturer at the Faculty of Industrial Engineering Sciences at KU Leuven, where he is affiliated with the Department of Computer Science. He serves as chairman of the Leuven Centre for Accessible Health Technology, subdivision head of Subdivision 3, Campus Group T Leuven, and Head of Education of the OC Innovative Health Technology. Additionally, he is an active member of DigiSoc – KU Leuven Institute for Digital Society. His research focuses on Technology for Tangible and Playful Interactions, particularly in healthcare applications. Dr. Geurts leads numerous research projects including therapeutic games for children with visual disorders, flexible activity measurement systems, intimate interactive systems, and early-stage glaucoma screening platforms. His work bridges human-computer interaction with accessible health technology, emphasizing user-centered design principles and practical healthcare solutions. Dr. Geurts' publication record demonstrates a consistent trajectory from fundamental interaction techniques to applied healthcare contexts. His recent work shows increasing sophistication in squeeze interactions, emotion regulation through tangible interfaces, and medical applications of interactive technology. The research trends indicate a growing focus on accessible medical diagnostics, therapeutic applications, and user experience in healthcare technology. As an educator, Dr. Geurts teaches across multiple domains including Electronics, Computer Architectures, Health Entrepreneurship, Sensors and Circuits for Healthcare Applications, and Extended Reality. His educational leadership extends to Master's theses and internships in health engineering, reflecting his commitment to training the next generation of healthcare technologists. Committee for Culture, Art and Heritage Faculty Council of Industrial Engineering Sciences Evaluation Committee of the Faculty of Industrial Engineering Sciences POC Advanced Education Faculty of Industrial Engineering Sciences Secretary of the OC Innovative Health Technology Departmental Council for Computer Science Interfaculty Council for Global Development (as substitute member) Dr. Geurts maintains an active research profile with numerous publications in top-tier human-computer interaction conferences and journals. His work shows a clear progression toward increasingly impactful healthcare applications, with strong emphasis on accessibility and user experience in medical technology development.
Richard Born is a Professor of Neurobiology at Harvard Medical School , focusing on the circuitry of the mammalian cerebral cortex and its role in visual perception. His lab employs multi-species approaches, combining primate psychophysics and electrophysiology rodent 2-photon imaging and optogenetics hierarchical Bayesian modeling of perceptual inference to investigate cortico-cortical feedback, neural variability, and context-dependent visual processing. Research Interests span visual systems neuroscience, with emphasis on top-down modulation of sensory processing binocular rivalry and perceptual states gamma oscillations and neural synchrony input-gain control in V1/V2/V3 Bayesian brain frameworks neuroanatomical connectomics Recent work explores layer 1 dendritic interactions with somatostatin interneurons and collaborations with institutions like Boston University and the University of Rochester. Advising includes mentoring postdoctoral fellows (Ariana Sherdil, Camille Gómez-Laberge, Abhinav Grama) and students at Harvard Medical School. The lab utilizes advanced techniques including multi-electrode arrays laminar probes optogenetic perturbation DTI tractography validation for circuit analysis.
