جست‌وجوی استاد و پژوهشگر

• Neurodegenerative Diseases
• Parkinson Disease
• Frontotemporal Dementia
• +۴ مورد دیگر

Salih Cayir, MD, is a Research Fellow at Yale School of Medicine's Department of Psychiatry. His research focuses on neurodegenerative diseases, particularly Parkinson’s disease and frontotemporal dementia, leveraging advanced neuroimaging techniques like PET and MRI. He investigates environmental factors influencing dopamine systems and opioid receptor signaling in addiction. Cayir completed his MD at Istanbul University in 2024 and is engaged in translational research to advance diagnostic and therapeutic approaches for neuropsychiatric disorders. Education: MD from Istanbul University School of Medicine (2024) Research Interests: Combines clinical neurology with imaging science to explore synaptic density (via SV2A imaging), dopamine transporter availability, and environmental health impacts on neurological conditions. His work bridges basic science and clinical practice, aiming to identify biomarkers for early disease detection. Recent Work: Published studies on CSF biomarkers in dementia, socioenvironmental effects on dopamine in Parkinson’s, and κ-opioid receptor roles in addiction. His 2025 travel award supports presenting on synaptic density differences in Parkinson’s patients at the Brain & Brain PET conference. Awards: Early Career Investigator Travel Award (2025) Techniques: PET imaging (including 18F-SynVesT-1, 11C-UCB-J), FDG-PET, structural MRI, and clinical biomarker analysis.

• Adolescent Development
• Alcoholism
• Marijuana Use
• +۴ مورد دیگر

Alecia Dager, PhD is an Adjunct Professor in the Department of Psychiatry at Yale University School of Medicine. She leads neuroimaging studies at the Olin Neuropsychiatry Research Center, focusing on adolescent neurodevelopment and substance use consequences. Her work integrates multimodal MRI techniques to explore brain changes associated with alcohol and marijuana use. Education: PhD in Experimental Psychology, University of California San Diego (2006) BA, University of California San Diego (2000) Research Interests: Adolescent brain development Neurobiological impacts of substance use Longitudinal MRI analyses of gray matter changes Cognitive and neural correlates of addiction Research Contributions: Pioneered studies linking fMRI responses to marijuana/alcohol use in college students Documented hippocampal atrophy associated with heavy drinking Explored genetic influences on amygdala volumes and alcoholism risk Lab Affiliations: Olin Neuropsychiatry Research Center Formerly directed the Center for the Translational Neuroscience of Alcoholism at Yale

• Schizophrenia Spectrum and Other Psychotic Disorders
• Neuroimaging
• Cognitive Neuroscience
• +۴ مورد دیگر

Dr. Naomi Driesen is a Research Scientist in Psychiatry at Yale School of Medicine, specializing in neuroimaging and the prefrontal cortex’s role in schizophrenia. She holds a PhD from the University of Memphis (1997), MA from the University of Virginia (1989), and BA from Yale University (1984). Her research focuses on schizophrenia, cognitive neuroscience, and the effects of ketamine on brain function, with over 20 years of publications in peer-reviewed journals. Notable studies include investigating ketamine’s impact on psychopathology and functional connectivity differences between schizophrenia and bipolar disorder. She collaborates on clinical trials involving AMPA receptor modulation and cannabinoid receptor imaging. Dr. Driesen’s work bridges neuroimaging, pharmacology, and psychiatric disorders, contributing to understanding cognitive deficits and therapeutic interventions.

Nicole Landiمشاهده پروفایل

استاد

• Reading Development
• Language Development
• Developmental Cognitive Neuroscience
• +۴ مورد دیگر

Nicole Landi is a Professor and Director of Developmental Psychology in the Department of Psychological Sciences at the University of Connecticut. She holds a Ph.D. in Cognitive Psychology from the University of Pittsburgh (2005). Her research utilizes cognitive neuroscience approaches (ERP, MRI, neuroimaging genetics) to study reading and language development, focusing on disorders like dyslexia and specific reading comprehension disability. Education: Ph.D., Cognitive Psychology, University of Pittsburgh, 2005 Dr. Landi's research investigates neural mechanisms underlying reading disorders through collaborations with schools like AIM Academy and The Windward School. Her work examines predictors of intervention response and includes projects on neurochemistry, genetics, and technology-based interventions such as the HBN-EDUCATE program with the Child Mind Institute. Analysis of her recent publications (2022-2025) reveals consistent themes: neural correlates of reading ability, socioeconomic impacts on literacy, intervention effectiveness during COVID-19, and specialized populations (autism, cochlear implant users). Methodologies predominantly feature fMRI, ERP, and DTI to explore brain-behavior relationships across development. Scientific Awards: James McKeen Cattell Sabbatical Fellowship (2020-2021) Dr. Landi advises multiple graduate and undergraduate students, including recipients of the Isabelle Y. Liberman Award (Meaghan Perdue), Goldwater Scholarship (Katie Mahaffy), and Holster Scholar (Katie Hooker). Her lab secures funding for research projects through partnerships and fellowships, including international collaborations on imaging genetics. The LandiLab operates within the Bousfield Psychology Building, collaborating with the Yale Child Study Center, Language Sciences Consortium, and community schools. These partnerships enable translational research through in-school laboratories and longitudinal studies of reading intervention outcomes.

Ammar Belatrecheمشاهده پروفایل

مدرس ارشد

• bio-inspired intelligent systems
• machine learning
• spiking neural networks
• +۵ مورد دیگر

Dr. Ammar Belatreche is a Senior Lecturer in Computer Science and Programme Leader for the MSc Advanced Computer Science at Northumbria University's Department of Computer and Information Sciences. He joined Northumbria University in May 2016 after previous positions as a Research Associate and Lecturer at Ulster University. He is an active member of the Computational Intelligence and Visual Computing (CIVC) research group. Dr. Belatreche earned his PhD in Computer Science from Ulster University in 2007. His professional qualifications include: Member of the Association of Computing Machinery (ACM) since 2012 Fellow of the Higher Education Academy (FHEA) since 2010 Member of the Institute of Electrical & Electronic Engineers (IEEE) since 2009 His research focuses on bio-inspired intelligent systems, machine learning, spiking neural networks, face detection and recognition, structured and unstructured data analytics, capital markets engineering, and image processing. Dr. Belatreche has extensive experience across academic and R&D in these areas, leading numerous research and consultancy projects. His recent work demonstrates a strong emphasis on neuromorphic computing, particularly spiking neural networks and their applications in computer vision, financial analysis, and biometrics. Analysis of his recent publications shows a clear trend toward advancing spiking neural network architectures, with particular focus on quantization, pruning, and binary implementations to improve efficiency. His research spans multiple domains including computer vision (face recognition, palm-vein recognition), financial technology (stock price manipulation detection), and neuromorphic engineering. Many of his recent papers (2024-2025) appear in top-tier conferences like ICLR and journals like IEEE Transactions on Neural Networks and Learning Systems. Dr. Belatreche has received professional recognition including: Fellowship with the Higher Education Academy (FHEA) Role as Associate Editor for the journal Neurocomputing He has successfully supervised or co-supervised 8 PhD students to completion and serves as a Program Committee Member and reviewer for numerous international conferences and journals. As Programme Leader for the MSc Advanced Computer Science, he plays a significant role in shaping postgraduate education in computer science at Northumbria University. His research group work bridges theoretical advances in neural computation with practical applications across multiple domains. Based in CIS 305 at Northumbria University's Newcastle campus, Dr. Belatreche continues to advance research in neuromorphic computing and its applications while contributing to academic leadership through his programme leadership role.

Michael G. Dwyer, IIIمشاهده پروفایل

دانشیار

• Neuroimaging biomarkers
• Quantitative neuroimaging
• Deep learning for MRI analysis
• +۲ مورد دیگر

Michael G. Dwyer, III, PhD, is an Associate Professor of Neurology and Biomedical Informatics at the University at Buffalo's Jacobs School of Medicine & Biomedical Sciences. He serves as the Director of the Neuroinformatics Development Lab at the Buffalo Neuroimaging Analysis Center, where his work focuses on advancing quantitative neuroimaging techniques to better understand neurological diseases, particularly multiple sclerosis (MS). Education: PhD, University of Bradford (2013) MS, Computer Science, Nova Southeastern University (2011) BS, Information Technology, Excelsior College (2009) Fellowship, NIH/NLM Research Training in Biomedical Informatics, University at Buffalo (2018) Research Interests: Dr. Dwyer's research expertise lies in developing and applying quantitative image analysis methods to neuroimaging data, aiming to improve the characterization of neurological disease onset, progression, and treatment. His work leverages advanced MRI techniques and modern computer science, particularly deep learning , to extract meaningful clinical metrics from complex neuroimaging data. Key areas include: Translational approaches to measuring brain atrophy in clinical routine MRI. Quantification of longitudinal myelin changes in vivo. Algorithms for tracking gray and white matter changes over time. Connectomics research on functional and structural networks in cognitive changes in MS. Scientific Awards: Publons 97th Percentile Reviewer (2021) Grants and Sponsored Research: Co-Investigator , 'A phase 3 double-blind study to evaluate the efficacy and safety of oral ozanimod compared to oral fingolimod in children and adolescents with relapsing-remitting multiple sclerosis' (Bristol Myers Squibb, $1,649,376, 2023–2032). Co-Investigator , 'Cerebral Protection in Transcatheter Aortic Valve Replacement: The PROTEMBO Trial' (Protembis GmbH, $992,994, 2023–2025). Co-Investigator , 'The effects of working memory training on brain function, structure, and cognition in MS' (National Multiple Sclerosis Society, $622,839, 2017–2020). Principal Investigator , 'NeuroSTREAM - Neurological Software Tool for Reliable Atrophy Measurement' (Novartis, Inc., 2014–2015). Labs and Teams: Dr. Dwyer directs the Neuroinformatics Development Lab at the Buffalo Neuroimaging Analysis Center, fostering interdisciplinary collaboration to advance neuroimaging methodologies and their clinical applications.

• Machine Learning
• Computer Vision
• Image Analysis
• +۳ مورد دیگر

Prof. Jean-Yves RAMEL is a faculty member at Savoie Mont Blanc University's Department of Computer Science (LISTIC laboratory). Previously, he served as a Professor at Polytech’Tours (2007–2023) and held roles at INSA Lyon (1997–2002). His research focuses on machine learning on graphs, medical and document image analysis, and interactive learning systems. He has published extensively in journals like Pattern Recognition and Medical Image Analysis . His work spans medical imaging segmentation, graph-based algorithms, and historical document processing. Notably, he contributed to projects like BVH (Bibliothèques Virtuelles Humanistes) and developed methods for graph edit distance and dynamic classification. He maintains active collaborations in digital humanities and has supervised numerous projects in computer science education. Education: PhD in Computer Science (1996), INSA Lyon: 'Interpretation automatique de documents graphiques' Maitre de conférences positions at INSA Lyon (1997–2002) and Polytech’Tours (2002–2023) Research Interests: Machine Learning on Graphs: Graph neural networks, graph embedding, and graph matching algorithms. Image Analysis: Medical imaging segmentation, historical document processing, and 3D texture analysis. Interactive Learning Systems: Dynamic classification, anytime algorithms, and one-class classifiers. Publications: Over 140 publications, focusing on graph-based methods, medical imaging, and document analysis. Recent work includes advancements in CNN/GNN pipelines for brain imaging and grammar-reinforcement learning for graphs (2025). Grants & Projects: Led the LIFAT lab (2018–2021) and contributed to the BVH digital humanities program. Active in collaborative projects involving medical imaging segmentation and historical document digitization. Labs/Teams: LISTIC laboratory (Savoie Mont Blanc University) and prior roles in LIFAT (Tours) and INSA Lyon's Interaction Collaborative lab.

Ann-Marie G. de Langeمشاهده پروفایل

پژوهشگر ارشد

• Neuroscience
• Cognitive Psychology
• Neuropsychology
• +۶ مورد دیگر

Ann-Marie G. de Lange holds the position of Research Fellow in the Multimodal Imaging group (NORMENT) at the University of Oslo and leads the FemiLab at Lausanne University Hospital (CHUV). She also collaborates with the Department of Psychiatry, University of Oxford. Her work focuses on brain aging, women's brain health, and mental health using large-scale datasets like the UK Biobank. She earned her PhD in Cognitive Psychology from the University of Oslo in 2017. Education: PhD in Psychology, University of Oslo (2017) Cand. Psychology, University of Oslo (2012) Key Research Interests: Neuroimaging analysis, cardiometabolic health, APOE4 gene effects, sex/gender disparities, and longitudinal cohort studies. Recent work emphasizes the interplay between hormonal changes, pregnancy, and brain aging mechanisms. Research Contributions: Over 50 peer-reviewed articles in journals like Biological Psychiatry , Neurology , and Nature Communications . Her studies highlight how cardiometabolic factors and hormonal trajectories influence brain structure and function across the lifespan. Labs/Teams: FemiLab (CHUV), NORMENT (Oslo), and collaborations with the Wellcome Center for Integrative Neuroimaging (Oxford).

Hector Arciniegaمشاهده پروفایل

استادیار

• Neuroimaging
• Brain Injury
• Contact Sports
• +۷ مورد دیگر

Hector Arciniega, PhD, is an Assistant Professor in the Department of Rehabilitation Medicine at New York University Grossman School of Medicine. He holds affiliations with the Vilcek Institute of Graduate Biomedical Sciences and the NYU Langone Concussion Center. His research focuses on understanding the long-term consequences of repetitive head impacts in contact-sport athletes, health disparities in TBI outcomes, and maternal/fetal health after brain injury. Dr. Arciniega earned his PhD in Neuroscience from the University of Nevada, Reno, and completed postdoctoral training at Harvard Medical School/Brigham and Women's Hospital under Drs. Martha Shenton and Sylvain Bouix. Key research areas include neuroimaging (structural, diffusion, functional MRI), neuropsychological assessments, and epidemiological studies. He leads the Arciniega Lab, which emphasizes interdisciplinary collaboration and diversity in neuroscience training. Major grants include NIH/NINDS D-SPAN Awards, NIMHD Loan Repayment Programs, and the Rainwater Charitable Foundation-Tau Leadership Award. Dr. Arciniega has published extensively on traumatic brain injury (TBI) biomarkers, maternal TBI during pregnancy, and neurodegeneration in athletes. He collaborates with institutions like Boston University, Ludwig-Maximilian-University Munich, and Carnegie Mellon University. His lab actively recruits students and researchers across academic levels, emphasizing mentorship in neurotrauma research.

• Neuroimaging
• Neuroinformatics
• MRI-based morphometric analysis
• +۷ مورد دیگر

David N. Kennedy is a Professor at UMass Chan Medical School, affiliated with the T.H. Chan School of Medicine. He holds appointments in the Departments of Psychiatry and Behavioral Sciences, Radiology, NeuroNexus Institute, and Eunice Kennedy Shriver Center. He also contributes to the MD/PhD Program and Neuroscience Department at the Morningside Graduate School of Biomedical Sciences. PhD in Nuclear Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States Dr. Kennedy is a leading expert in neuroimaging and neuroinformatics, with foundational contributions to MRI-based morphometric analysis, functional MRI, and diffusion tensor imaging. His research focuses on developing neuroinformatics tools and resources, including the Internet Brain Volumetric Database and the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). He co-founded the Center for Morphometric Analysis at Massachusetts General Hospital and has been instrumental in advancing data sharing, reproducibility, and standardization in neuroscience. His recent publications emphasize FAIR data principles, neuroimaging data models, open-source tools like DataLad and HeuDiConv, and collaborative frameworks for neuroscience. These works reflect a strong trajectory toward enhancing data interoperability, transparency, and community-driven standards in neuroimaging research. Community liaison for the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) Co-PI of the morphometry Biomedical Informatics Research Network (mBIRN) Founding editor of the journal Neuroinformatics Dr. Kennedy has not listed specific grants or advising roles in the provided text but plays a central role in major neuroinformatics initiatives. He has no listed scientific awards in the provided materials. He is a key figure in the development and dissemination of neuroimaging informatics resources, contributing to national and international efforts to standardize and share neuroscience data through platforms like NITRC and mBIRN.

• Polymer Science
• Nanomaterials
• Block Copolymer Self-Assembly
• +۱۳ مورد دیگر

Ulrich (Uli) Wiesner is the Spencer T. Olin Professor of Engineering in the Department of Materials Science and Engineering at Cornell University's College of Engineering. He has been a faculty member since 1999, starting as a tenured Associate Professor and becoming a Full Professor in 2005. Since 2015, he has co-directed the MSKCC-Cornell Center for Translation of Cancer Nanomedicine (MC2TCN), a National Cancer Institute (NCI)-funded Center for Cancer Nanotechnology Excellence. Ph.D., Physical Chemistry, University of Mainz and Max-Planck-Institute for Polymer Research (1991) Diploma, Chemistry, Johannes Gutenberg University of Mainz (1988) Wiesner’s research lies at the interface of polymer science and inorganic chemistry, focusing on the self-assembly of block copolymers to create multifunctional hybrid nanomaterials. His group pioneers the use of soft matter principles to encode hierarchical structure in inorganic materials, enabling the design of materials with no natural analogues. Key areas include mesoporous oxides and non-oxides for energy applications, and the development of ultrasmall fluorescent core-shell silica and aluminosilicate nanoparticles (C-dots) for bioimaging and nanomedicine. The 15 most recent publications reveal a strong trend toward quantum materials , cancer nanotherapeutics , and super-resolution imaging . His team leverages block copolymer self-assembly to create gyroidal and diamond network nanostructures for superconducting metamaterials, while simultaneously advancing clinical translation of nanoparticles for targeted drug delivery and ferroptosis-based cancer therapy. The integration of soft matter with hard condensed matter is a unifying theme across energy, quantum, and biomedical applications. His scientific awards include: National Academy of Inventors (NAI) Fellow (2024) Ambassadeur pour la Chimie Française, CNRS (2019) Arthur K. Doolittle Award, ACS PMSE (2016) Elected PMSE Fellow, American Chemical Society (2015) National Science Foundation Creativity Award (2008) Mr. & Mrs. Richard F. Tucker’50 Excellence in Teaching Award, Cornell (2005) IBM Faculty Partnership Award (2001) Carl Duisberg Memorial Award, GDCh (1999) Wiesner has secured significant funding from the NCI and other federal agencies to support his interdisciplinary research. His group mentors students across chemistry, materials science, and biomedical engineering, contributing to advances in nanoparticle synthesis , clinical translation , and multifunctional material design . He leads a dynamic research team working at the forefront of cancer nanotechnology and quantum metamaterials , with future work focused on expanding the clinical impact of nanotherapeutics and exploring emergent phenomena in soft-matter-directed quantum systems.

Jessica Marمشاهده پروفایل

استاد

• Bioinformatics
• Single-cell Biology
• Stem Cell Biology
• +۳ مورد دیگر

Professor Jessica Mar is a Professorial Research Fellow at the Australian Institute for Bioengineering and Nanotechnology (AIBN) at the University of Queensland. Her research focuses on developing bioinformatics methods to understand regulatory processes in human diseases, particularly leveraging single-cell RNA-sequencing to analyze cellular heterogeneity in contexts like cancer, aging, and stem cell biology. Key areas include modeling gene expression variability, analyzing transcriptomic data, and developing statistical frameworks for omics integration. She has led projects funded by grants such as the Georgina Sweet Award and ARC Future Fellowships. Her work spans computational approaches to cancer heterogeneity, senescence mechanisms in stem cells, and the impact of senolytic therapies on aging. Recent studies include applications of single-cell technologies to brain organoids and breast cancer metastasis. Awards include recognition for contributions to quantitative biomedical science and stem cell research. She collaborates widely, mentoring students in computational biology, stem cell biology, and systems biology. Publications highlight her contributions to understanding tumor heterogeneity, epigenetic dynamics, and the interplay between mechanics and cell reprogramming. Her lab’s work integrates machine learning with experimental biology, addressing challenges in data analysis for single-cell and spatial omics. Current projects include biomarker discovery for hypoxic-ischemic encephalopathy and developing optimal transport models for cancer progression analysis.

• Medical Imaging
• Neuroimaging
• MRI Reconstruction
• +۲ مورد دیگر

Stefan Sunaert is a Professor at KU Leuven's Faculty of Medicine within the Department of Imaging & Pathology. He serves as Head of Radiology and Head of the Division of Medical Imaging (Divisie Medische Beeldvorming), while also holding membership in the LBI - KU Leuven Brain Institute. His institutional roles include senior academic staff positions on the Council of the Faculty of Medicine, Council of the Department of Imaging & Pathology, and Board of the Department of Imaging & Pathology. His research focuses on advanced neuroimaging applications, particularly in MRI reconstruction, brain connectivity analysis, and clinical translation across neurology, oncology, and psychiatry. Key methodologies include diffusion MRI, functional MRI, and multimodal imaging integration for studying conditions ranging from brain tumors to neurodegenerative diseases and psychiatric disorders. Analysis of his 2025 publications reveals a strong emphasis on translational neuroimaging, with recurring themes in brain network analysis (structural/functional connectivity), radiation therapy effects on neural systems, and advanced MRI techniques for clinical applications. His work spans diverse populations including glioma patients, aging adults, children with cerebral palsy, and early Alzheimer's cases. As active promotor or co-promotor on ten major research projects (2023-2029), he leads investigations into neurosurgical planning with dynamic MRI, epilepsy imaging, diabetes-related brain changes, pediatric brain tumor radiotherapy, and neurocognitive decline prediction. These projects demonstrate significant grant acquisition capacity and interdisciplinary collaboration. He leads the Translational MRI unit at UZ Herestraat 49 (box 7003, Leuven) and teaches medical imaging courses including 'Medical Imaging for Physiotherapists' and multiple problem-solving modules in radiology. His ORCID profile (0000-0002-1177-4680) documents extensive publication output in high-impact journals.

Gail A. Cornwallمشاهده پروفایل

استاد

• Biological Amyloids
• Reproductive Biology
• Neurodegeneration
• +۴ مورد دیگر

Gail A. Cornwall, Ph.D., is a Professor in the Department of Cell Biology and Biochemistry at the Texas Tech University Health Sciences Center School of Medicine. Her research bridges reproductive biology, neuroscience, and structural biochemistry, focusing on the dual roles of biological amyloids in physiological functions and disease mechanisms. Education: Ph.D. in Reproductive Biology, Johns Hopkins Bloomberg School of Public Health Dr. Cornwall's pioneering work centers on functional amyloids—protein aggregates that perform critical biological roles rather than causing pathology. Her lab investigates three interconnected research pillars: the host defense functions of amyloid matrices in the reproductive tract, the structural mechanisms of functional amyloid assembly, and the potential role of sperm amyloids as epigenetic carriers of transgenerational disease. She discovered that the epididymal lumen contains a functional amyloid matrix that traps or kills bacteria depending on pathogen virulence, functioning as a mammalian counterpart to bacterial biofilms. Concurrently, her team explores how similar amyloid structures in the brain may regulate synaptic plasticity, and how environmental toxins induce transmissible amyloid formations in sperm that correlate with inherited disease phenotypes. Analysis of Dr. Cornwall's 15 most recent publications (2023-2012) reveals a cohesive trajectory examining amyloid plasticity across biological systems. Her work consistently integrates structural biology (X-ray crystallography, NMR spectroscopy), transgenic models, and translational approaches to demonstrate how functional amyloids provide evolutionary advantages in host defense while maintaining the structural versatility to contribute to neurodegenerative diseases when dysregulated. Dr. Cornwall leads a multidisciplinary laboratory employing biochemical, cell biological, and biophysical methodologies—including recombinant protein systems, gene knockout mouse models, and advanced imaging—to study amyloid dynamics. Her team maintains active collaborations with structural biologists (R. Bryan Sutton), NMR spectroscopists (Michael P. Latham, Benjamin J. Wylie), and reproductive physiologists to dissect amyloid assembly mechanisms at atomic resolution. Information regarding Dr. Cornwall's student advising roles and specific research grants was not provided in the source materials.

Melissa K. Passarelliمشاهده پروفایل

استادیار

• Imaging Mass Spectrometry
• Spatial 'omics
• Secondary Ion Mass Spectrometry (SIMS)
• +۳ مورد دیگر

Melissa K. Passarelli is an Assistant Professor in the Department of Chemistry and Biochemistry at Concordia University, specializing in advanced imaging mass spectrometry techniques. Her work bridges analytical chemistry, biochemistry, and pharmaceutical sciences. Ph.D., The Pennsylvania State University B.Sc., Union College Her research focuses on Imaging Mass Spectrometry (IMS) , including Spatial 'omics , SIMS , and MALDI , for applications in intracellular drug measurement, subcellular chemical imaging, and neurodegenerative disease studies. Recent publications highlight her innovations in 3D OrbiSIMS , correlative imaging methodologies, and single-cell analysis. Key trends include molecular mapping in Alzheimer’s pathology, drug delivery systems, and lipidomics. Her lab collaborates on multi-modal approaches integrating atomic force microscopy (AFM) with single-cell mass spectrometry to evaluate drug uptake and biochemical effects. Funded by a FRQNT grant , this work addresses therapeutic and toxicological challenges. Melissa teaches courses in Analytical Chemistry for Biologists and Imaging Mass Spectrometry , and maintains an active research group with expertise in mass spectrometry-based intracellular analysis.