Hans Magnus Henrik Lundell is an Associate Professor at the Department of Health Technology, Technical University of Denmark , specializing in Magnetic Resonance research. His work bridges biomedical engineering and neuroscience through advanced imaging techniques. Active in diffusion MRI and neurodegeneration research Current supervisor of two PhD students in multi-modal imaging projects Contributor to 11 publications with international collaborations Focus on tumor microstructure and cerebellar imaging applications His research on Diffusion-weighted MRS and time-dependent diffusion imaging has applications in glioblastoma diagnostics and neurodegenerative disease studies. Recent work explores clinical MRI-Linac integration for radiotherapy monitoring and extracellular diffusion dynamics in human tissue.
Kinan Abbas is a researcher at the University of Strasbourg's College of Science and Engineering, Department of Computer Science, specializing in hyperspectral imaging and machine learning. His work focuses on spectral image processing techniques including unmixing, demosaicing, and low-rank matrix approximation. His research interests center on hyperspectral imaging and machine learning applications, particularly developing novel methods for snapshot spectral image processing. Key contributions include locally-rank-one-based joint unmixing frameworks, diffusion models for texture synthesis, and entropy-weighted spectral deconvolution techniques. His work bridges theoretical signal processing with practical applications in remote sensing and computational photography. Analysis of his publication trend (2021-2025) shows evolution from foundational spectral unmixing techniques toward advanced generative models, with increasing focus on diffusion-based synthesis and multifractal analysis. His research consistently addresses computational challenges in spectral image reconstruction. Abbas actively collaborates with researchers from ICube laboratory (Strasbourg), including Matthieu Puigt, Gilles Delmaire, and Gilles Roussel, evidenced by consistent co-authorship across 14 publications. His work appears in IEEE Transactions, ICASSP, and French GRETSI conferences, indicating strong institutional support for his research program.
Tanja Junkers is a full Professor in the School of Chemistry at Monash University, Australia, where she leads research on continuous flow polymerizations, nanoparticle design, and precision polymers. She also holds a guest professorship at Hasselt University, Belgium. Education: PhD in Physical Chemistry from Georg-August University (Göttingen, Germany, 2006); Diplom (Master) in Chemistry from the same institution (2002). Prior roles include research associate at UNSW Sydney and senior scientist at Karlsruhe Institute of Technology. Research focuses on controlled radical polymerizations, flow chemistry, and applying machine learning to polymer synthesis. Key interests include degradable polymers, self-assembly of block copolymers, and sustainable materials development. Her work contributes to UN Sustainable Development Goals related to sustainable industry and innovation. Current projects include the ARC-funded 'Sustainable Reversible Polymerisation' and 'Data Driven Polymer Synthesis'. She serves as Associate Editor for Polymmer Chemistry (Royal Society of Chemistry). Advising: Actively supervising PhD students in areas like continuous flow reactor polymerization and peptidomimetic synthesis. Her research teams collaborate internationally, with recent projects involving universities in Australia, Germany, and Belgium. Lab/Teams: Leads the Monash group focused on precision polymer design, integrating automation and high-throughput experimentation. Collaborates with interdisciplinary teams on chemical manufacturing and energy materials.
Maria Cristina D'Oca is an Associate Professor in the Department of Physics and Chemistry - Emilio Segrè at the University of Palermo. Her work focuses on radiation physics, dosimetry, and spectroscopy, with applications in medical physics, food safety, and archaeological dating. She has contributed to advancements in EPR dosimetry, FLASH radiotherapy, and radiation detection. Department: Physics and Chemistry Email: mariacristina.doca@unipa.it Her research interests include: Radiation dosimetry for medical applications Electron Spin Resonance (EPR) and Thermoluminescence techniques Food irradiation detection and safety Metal ion adsorption on biological materials Mechanisms of radiation interaction with organic and inorganic compounds Monte Carlo simulations for radiation transport Recent publications highlight her expertise in FLASH radiotherapy dosimetry, diffusion correction in Fricke dosimeters, and gamma irradiation effects on food. She employs machine learning and computational models to enhance dosimetric accuracy and explores historical dating methods using EPR spectroscopy.
Patrick Bolan, PhD is an Associate Professor in the Department of Radiology at the University of Minnesota. He serves as Associate Medical Director of the Center for Clinical Imaging Research and Associate Director of the Center for Radiology Research Resources. He is also faculty in the PhD Program in Medical Physics. His research focuses on advanced MRI and MRS techniques for cancer diagnosis and treatment monitoring, particularly in breast and prostate cancers. Key areas include developing AI-driven imaging protocols, quantitative MRI parameter estimation, and clinical translation of spectroscopic methods. Dr. Bolan leads interdisciplinary efforts in optimizing diffusion-weighted imaging (DWI), multiparametric MRI for treatment response prediction, and automated image analysis using deep learning. His work bridges clinical needs with cutting-edge imaging technologies, aiming to improve diagnostic accuracy and therapeutic decision-making. He has contributed to international standards for proton MRS in neuroimaging and breast cancer assessment through initiatives like the ISMRM and ACRIN trials. He holds leadership roles in radiology research infrastructure, overseeing imaging research resources and fostering collaboration between clinical and technical teams. His lab focuses on translational research, advancing imaging biomarkers for personalized oncology care.
Xin Xing is an Assistant Professor at the University of Nebraska at Omaha, College of Information Science & Technology, Department of Computer Science. Their research bridges machine learning, neuroscience, and biomedical applications. Education: Ph.D. in Computer Science (2023), University of Kentucky M.S. in Information Technology (2016), University of Stuttgart B.S. in Communications Engineering (2011), Shandong University Research Interests: Medical Imaging AI: Developing models for Alzheimer's disease diagnosis using 3D PET/MRI and transformers (e.g., ADViT, CAT-XPLAIN) Gut-Brain Axis: Investigating microbiome impacts on neurodegeneration, particularly in APOE4 carriers Computer Vision: Innovating diffusion models, self-supervised learning, and attention mechanisms for biomedical and geospatial applications Publication Trends: Recent work focuses on neuroimaging biomarkers for Alzheimer's, microbiome interventions, and scalable vision-language architectures. They integrate cutting-edge ML techniques with clinical data analysis. Collaborations: Engaged in interdisciplinary projects spanning genetics, nutrition, and traffic safety. Their work appears in journals like Communications Biology and explores real-world applications such as roadway hazard detection via satellite imagery.
Esperanza Rivera de Torre is an Assistant Professor at the Department of Biotechnology and Biomedicine, Technical University of Denmark. Her research focuses on antibody engineering, venomics, and protein design, particularly in neutralizing venom toxins and cancer therapy. Current affiliation: Department of Biotechnology and Biomedicine (DTU) Academic rank: Assistant Professor Research Interests Specializing in antibody engineering to develop synthetic antivenoms using de novo protein design. Investigating snake venom toxins and their neutralization mechanisms via VHH antibodies. Contributing to protemics and peptide sequencing through AI-driven tools like InstaNovo. Studying structural biology of actinoporins and their interactions with lipid membranes. Active in cross-neutralizing antibodies for tropical diseases and allergens. Advising and Collaborations Supervises multiple PhD students including Ruiz Espi, Møller, and Møiniche. Collaborates on projects like AI-driven protein binder design and allergen epitope characterization. Engages in international collaborations across venom and biomedical research fields.
Dr. Alia Alia is an Assistant Professor at Leiden University's Leiden Institute of Chemistry (LIC), part of the Faculty of Science. Her research focuses on advancing MRI and NMR techniques to study neurodegenerative diseases, particularly Alzheimer's, and environmental toxin impacts on organisms like zebrafish. She has held academic positions since 1995, including a JSPS fellowship in Japan and roles at Jamia Millia University, New Delhi. Education: PhD in Bioscience (1992), Jamia Millia University M.Sc. in Biosciences (1989), Jamia Millia University B.Ed. (1988), Jamia Millia University B.Sc. in Life Sciences (1986), University of Delhi Research Interests: Alia's work combines cutting-edge MRI/NMR methodologies with biological systems to explore Alzheimer's biomarkers, neurochemical changes, and toxin effects. She pioneers applications of HR-MAS NMR to study nanoplastics and PFAS toxicity. Her lab uses zebrafish as a versatile model for human disease mechanisms. Publications: Over 50 peer-reviewed articles, including studies on sex-specific GABA alterations in Alzheimer's models, microstructural changes in zebrafish muscles, and nanoplastic-induced amyloid fibrillation. Awards: C.J. Kok Prize for Discovery of the Year (2004) Alzheimer Forschung Initiative Grant (2013) Japan Society for Promotion of Science Fellowship (1996) Labs/Teams: Leads the Alia Group at Leiden University, collaborating internationally on neuroimaging and toxicology projects. Collaborations include Leipzig University and institutions in Japan.
Dr. Thomas M. Ernst is a Professor in the Department of Diagnostic Radiology and Nuclear Medicine at the University of Maryland School of Medicine. He serves as Technical Director of the Center for Advanced Imaging Research (CAIR) and leads multi-institutional research programs in magnetic resonance imaging (MRI) and spectroscopy (MRS), focusing on prospective motion correction and pediatric neuroimaging. His work spans clinical applications in HIV, drug abuse, and post-COVID-19 brain effects. Education : PhD in Physics (University of Freiburg, Germany), Post-Doctoral Fellowship in MR Spectroscopy (HMRI/Caltech) Research Interests : Dr. Ernst specializes in advanced MRI/MRS techniques to study brain development, motion correction in neuroimaging, and neurological impacts of HIV, methamphetamine abuse, and post-COVID-19 conditions. His lab develops real-time adaptive MRI methods to eliminate motion artifacts. Recent Publications highlight trends in genome-wide association studies of visceral fat , neurovirology of long-term COVID-19 effects , and innovations in diffusion-weighted imaging . Scientific Awards : Fellow, International Society for Magnetic Resonance in Medicine (2011); Deputy Editor, Magnetic Resonance in Medicine (2013). Grants : He leads NIH/NIDA-funded projects including the Adolescent Brain Cognitive Development (ABCD) Study and neural correlates of working memory training in HIV patients. Past grants include a Bioengineering Research Partnership (BRP) for motion correction techniques. Labs : Dr. Ernst directs the Center for Advanced Imaging Research (CAIR) at UMB, collaborating with institutions like Johns Hopkins and the University of Freiburg. His lab works on commercializing motion correction technologies via KinetiCor Inc.
Guilherme Maia de Oliveira Wood is a University Professor and head of the Neuropsychology/Neuroimaging department at the University of Graz, where he has been employed since 2011. His research focuses on developing high-tech tools for neuropsychological rehabilitation, clinically testing their efficacy, and understanding the mechanisms influencing neural plasticity. He is actively involved in the interdisciplinary Master's program 'Computational Social Systems' offered jointly by the University of Graz and Graz University of Technology. His educational background includes: Psychology studies at the Federal University of Minas Gerais (1994-1999), Brazil Doctorate in Psychology at RWTH Aachen (2001-2005), Germany Habilitation in Psychology at the University of Salzburg (2005-2011) Wood's research interests center on combining technological innovation with cognitive science, particularly in neuropsychology and neurofeedback applications. He investigates neural plasticity as the brain's ability to organize itself as a dynamic system, with special attention to psychosocial influences on treatments and rehabilitation. His work bridges technical neuroimaging approaches with ethical considerations regarding neurotechnologies. His recent publications demonstrate a strong interdisciplinary approach spanning neuroscience, psychology, data science, and ethics. The articles reveal consistent focus on methodological rigor in neuroimaging, cognitive mechanisms in learning and rehabilitation, and critical examination of psychosocial factors influencing scientific evidence interpretation. His work increasingly addresses the emotional embedding of scientific communication and placebo effects in neurofeedback research. Wood actively supervises master's students through the 'Computational Social Systems' program and offers thesis topics on brain aging, neurofeedback mechanisms, graph theory applications in neuroscience, and the relationship between motor learning and cognitive function. He leads an FWF-funded research project investigating brain plasticity through fMRI-based neurofeedback training. He is affiliated with several research initiatives including COLIBRI (Complexity of Life), Human Factor in Digital Transformation X, and Neurofeedback Research Graz. His laboratory employs multi-sequence MRI techniques including T1-weighted recordings, diffusion-weighted imaging, resting-state fMRI, and GABA spectroscopy to investigate changes in brain structure, function, and chemistry in response to neurofeedback training.
Noam Shemesh is a Principal Investigator at the Champalimaud Foundation , specializing in ultrahigh-field MRI coupled with optogenetics and optical microscopy to study neural circuit dynamics and microstructural changes in neurodegeneration/plasticity models. His work bridges preclinical MRI with clinical translation . Research Interests : His lab focuses on Deciphering neural circuits via advanced fMRI and optogenetics Non-BOLD functional MRI mechanisms Microstructural determinants of behavior and disease Cellular-scale MRI in white/gray matter Longitudinal studies in rodent models Development of novel MRI methodologies Scientific Contributions : Key publications include 2023: Ultrafast macroscale oscillatory modes in rat brains 2022: Extracellular vesicle effects on bone marrow immunity 2019: Susceptibility mapping for tumor infiltration 2018: Microscopic anisotropy and axon diameter analysis 2017: Diffusion-weighted MRS and neuronal-astrocytic differentiation Students : Francisca Fernandes (MSc) Rita Alves (PhD) Ruxanda Lungu (PhD) Sara Pires Monteiro (PhD)
Dr. Richard Telford is a Professor of Analytical Chemistry and Director of the Analytical Centre at the University of Bradford, overseeing specialized analytical equipment and managing industrial collaborations. He joined the university in 2005, delivering over £3 million in commercial research income and leading projects like CAYMAN and SIBLING (totaling £4 million). His expertise spans NMR, vibrational spectroscopy, mass spectrometry, and hyphenated techniques, with a focus on pharmaceuticals and 3D printing. He co-authored a book chapter on thermal analysis and has extensive industry experience at Zeneca/AstraZeneca/Syngenta. Research interests include hyphenated techniques (e.g., DSC-Raman/FTIR/XRD), 3D printing applications in pharmaceuticals, and advanced analytical methodologies. His work bridges academia and industry, addressing challenges in drug delivery, material characterization, and sustainable technologies. Notable achievements include pioneering vat photopolymerization 3D printing for drug formulations and advancing understanding of molecular behavior via spectroscopic and thermal methods. Collaborations span multiple sectors, including agrochemicals and specialty chemicals.
Prof. Samiul Amin is a Professor in the CHEMICAL, ENVIRONMENTAL, & MATERIALS ENGINEERING Department at the University of Miami's College of Engineering. His research focuses on stimuli-responsive materials, sustainable cosmetic formulations, and smart biomaterials for biomedical applications. He leads interdisciplinary projects combining polymer science, nanotechnology, and AI-driven material optimization. Key research areas include: Design of hydrogels for wound healing and tissue engineering Development of eco-friendly surfactants and sustainable emulsions Smart hair care products using thermoresponsive polymers Nanoplasmonic sensing for surface activity analysis Machine learning applications in cosmetic formulation Recent work emphasizes translational research bridging material science with consumer product needs, particularly in the beauty and biomedical sectors. His lab innovates in emulsion stability assessment techniques (e.g., Diffusing Wave Spectroscopy) and biopolymer composite systems. Prof. Amin actively collaborates across disciplines, publishing in high-impact journals like Current Opinion in Colloid & Interface Science and Colloids and Surfaces A . His research has been presented at major conferences including the AOCS Annual Meeting.
Daniel Kido, MD, is a Professor and Vice Chair in the Department of Radiology at the School of Medicine. His expertise lies in advanced magnetic resonance imaging techniques, particularly susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM), with applications in pediatric and adult neurological conditions including stroke, dementia, traumatic brain injury, and neonatal brain disorders. His research interests center on neuroradiology , brain iron metabolism , cerebral microbleeds , hypoxic-ischemic injury , and MR spectroscopy . He has extensively studied the role of SWI in detecting microhemorrhages in dementia and trauma, visualizing deep medullary veins in infants, and assessing cerebral oxygenation using QSM. His work bridges clinical imaging with neuropathological validation, especially in neurodegenerative diseases. The trend in his recent publications shows a strong focus on quantitative neuroimaging biomarkers for predicting outcomes in stroke, dementia, and pediatric trauma. His work increasingly integrates preclinical models (e.g., neonatal piglets) with human studies to validate imaging findings. Collaborations with experts like E. M. Haacke and J. P. Jacobson highlight his role in advancing SWI as a clinical and research tool. No scientific awards were mentioned in the provided text. Dr. Kido has contributed to numerous peer-reviewed articles, book chapters, and conference presentations, often in collaboration with multidisciplinary teams. While no formal advising or grant information is listed, his long-standing research output suggests significant involvement in academic mentorship and funded research. He has played a key role in developing and validating high-resolution MRI techniques for detecting occult vascular lesions and brain injury. He is part of a prominent neuroimaging research group focused on SWI development and clinical translation , working closely with physicists and neurologists to expand the diagnostic utility of MRI in neurological disorders.
Maurizio Marrale serves as Associate Professor in the Department of Physics and Chemistry at the University of Palermo (Unipa), holding position PHYS-06/A. His office is located at the Department of Physics and Chemistry "Emilio Segre" (DIFC), Viale delle Scienze, Building 18, with regular office hours on Thursdays from 3:00 PM to 5:00 PM. His research spans radiation dosimetry, medical physics, and advanced imaging techniques. Key focus areas include FLASH radiotherapy verification using alanine/EPR dosimetry and silicon carbide detectors, transcranial magnetic resonance-guided focused ultrasound for neurological disorders (particularly essential tremor), and MRI-based dosimetry with Fricke gels. His work bridges physics principles with clinical applications in radiation oncology and diagnostic imaging. Analysis of his 15 most recent publications reveals strong emphasis on Ultra-high dose rate (UHDR) beam characterization for FLASH radiotherapy Development of novel dosimetry systems (SiC detectors, ionoacoustic sensors) Advanced neuroimaging techniques for thalamic targeting Diffusion correction methodologies in 3D dosimeters Clinical MRI applications for neurological disorders His research demonstrates consistent integration of computational modeling (Geant4, deep learning) with experimental validation. As principal supervisor, he has guided over 35 master's theses at Unipa between 2009-2024, primarily in Physics and Medical Radiology Techniques programs. His supervisory work focuses on radiation dosimetry applications, MRI physics, and radiotherapy technology validation.
