Find Academic Supervisors

Sue SchutzView profile

Senior Lecturer

• Reflective practice in nursing
• Qualitative research methods
• Nursing research
• +8 more

Sue Schutz is a Senior Lecturer at the Oxford School of Nursing and Midwifery, Oxford Brookes University, where she contributes significantly to teaching and research in nursing. She teaches on the Professional Doctorate in Nursing and Midwifery and supervises PhD and Professional Doctorate students. Her research interests center on reflective practice in nursing , qualitative research methods , and patient and caregiver experiences in chronic illness, particularly in cancer care, heart failure, and hypertension. She is also deeply engaged in clinical communication, mental health nursing, and the impact of digital health innovations during and after the pandemic. The recent publications reflect a strong trend in qualitative and mixed-methods research focused on understanding patient, caregiver, and clinician experiences across diverse settings—from robotic surgery and remote consultations to end-of-life care and mental health challenges. Her work emphasizes empathy, ethical practice, and the application of reflective methodologies in clinical and educational contexts. Scientific Affiliations and Memberships: Royal College of Nursing Phi Mu Chapter, Sigma Scientific Committee, Sigma European Research Conference Co-chair, OxPINTS (Oxford Philosophy Informing Nursing Theory) Sue Schutz actively supervises doctoral students and welcomes new PhD and Professional Doctorate candidates in nursing and midwifery. Her research is supported through institutional affiliations and collaborative projects, particularly in supportive cancer care and heart failure. She has co-edited the book Reflective Practice in Nursing and continues to influence nursing education and practice through scholarship and leadership. She is involved in key research groups focusing on Supportive Cancer Care and Caregivers and Heart Failure , contributing to interdisciplinary efforts to improve patient and caregiver outcomes.

Chris FiacconiView profile

Assistant Professor

• Cognitive Psychology
• Human Memory
• Metacognition
• +3 more

Chris Fiacconi is an Assistant Professor in the Department of Psychology at the University of Guelph. His research focuses on human memory and metacognition, particularly how inferential processes guide the monitoring, assessment, and regulation of learning. He teaches courses such as PSYC 2650 (Cognitive Psychology), PSYC 3290 (Conducting Statistical Analyses in Psychology), and PSYC 6940 (Discrete Variable Research Design & Statistics). Education: B.Sc. Psychology (University of Western Ontario, 2007) Ph.D. Psychology (McMaster University, 2012) His work integrates behavioral testing and psychophysiological measures (e.g., heart rate variability, facial electromyography) to explore the interplay between cognition and autonomic nervous system activity. Recent publications highlight his interests in fluency effects, sequential memory dependencies, and self-regulated learning strategies. Dr. Fiacconi's lab, the Guelph Memory and Cognition Lab, actively trains graduate students and collaborates on projects related to memory encoding, metamemory, and educational interventions. Funding from NSERC supports his research into the coupling of volitional control processes with autonomic activity.

• Financial Econometrics
• Statistics
• Empirical Asset Pricing
• +5 more

Dacheng Xiu is the Joseph Sondheimer Professor of Econometrics and Statistics at the Booth School of Business , University of Chicago, and an Affiliated Faculty in the Department of Statistics. He serves as a Research Associate at the National Bureau of Economic Research and holds editorial roles at journals like Journal of Business & Economic Statistics and Journal of Financial Econometrics . PhD and MA in Applied Mathematics from Princeton University BS in Mathematics from University of Science and Technology of China His research focuses on statistical methodologies for financial data , including risk measurement , portfolio management , and empirical asset pricing using high-frequency data and machine learning . Recent work analyzes text data and large language models for economic forecasting. Editorial leadership includes Co-Editor and Associate Editor roles at top journals like Journal of Finance and Annals of Statistics . His lab ( Risk Lab ) specializes in systemic risk assessment through transaction-level data analysis. 2024 Dimensional Fund Advisors Prize 2023 GSU-RFS FinTech Conference Best Paper Award 2022 Society for Financial Econometrics Fellow 2018 Swiss Finance Institute Outstanding Paper Award

• Cognitive Neuroscience
• Neural Plasticity
• Language Processing
• +5 more

Professor Gesa Hartwigsen is a leading cognitive neuroscientist holding dual appointments as Professor for Cognitive and Biological Psychology at Leipzig University and Lise Meitner Research Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS). She leads the Research Group Cognition and Plasticity, focusing on neural networks for higher cognitive functions, adaptive plasticity in cognition, and language network reorganization after stroke. Her educational background includes: Studies of Psychology (Dipl.-Psych., 2001-2006) at Kiel University PhD in Neurology (Dr. phil., 2007-2010) at Kiel University Habilitation in Psychology (2018) at University of Potsdam Hartwigsen's research spans cognitive neuroscience with particular emphasis on language processing, neural plasticity, and brain stimulation techniques. Her work investigates how brain networks support semantic cognition, how they adapt following neurological damage, and how they change across the lifespan. She employs advanced methodologies including transcranial magnetic stimulation (TMS), functional MRI, and concurrent TMS-fMRI to establish causal relationships in neural processing. Analysis of her recent publications reveals a strong focus on language networks, executive control mechanisms, and neural plasticity. Her work increasingly integrates advanced computational approaches with neurostimulation to understand semantic processing, speech comprehension in challenging environments, and recovery from language disorders. A significant trend is her development of methodological frameworks for concurrent TMS-fMRI, establishing new standards in the field. Her notable scientific recognition includes: ERC Consolidator Grant (2023-2027) for "The Flexible Brain: (Re-)shaping Adaptation in Semantic Cognition" NVIDIA GPU grant (Titan Xp Donation) Hartwigsen has secured substantial research funding, including multiple DFG projects as Principal Investigator. Her current DFG Research Unit (2023-2026) focuses on "Modulation of brain networks for memory and learning by transcranial electrical stimulation," where she serves as PI. She has successfully led multiple interdisciplinary projects examining language networks, neural plasticity, and brain stimulation effects. At the MPI CBS, she leads the Cognition and Plasticity research group, which investigates how brain networks support cognitive functions and adapt to challenges. Her team employs a multimodal approach combining neurostimulation, neuroimaging, and behavioral methods to understand the causal architecture of cognitive networks, particularly in language processing and semantic cognition.

Martin Salzmann-EriksonView profile

Associate Professor

• Nursing Science
• Psychiatric Nursing
• Digital Health
• +5 more

Martin Salzmann-Erikson is an Associate Professor in Nursing Science at the University of Gävle, specializing in Caring Science. With extensive clinical experience in psychiatric intensive care, he has developed innovative models for staff-patient interactions and advanced courses like "Integrative Nursing in Psychiatric Care" and "Concept Analysis." His work bridges clinical practice, education, and research, focusing on the complexities of human interaction through chaos theory and digital transformation. Current research in the "Digital Shapeshifting" program addresses critical challenges in healthcare digitization, including reducing digital exclusion, ensuring inclusive care environments, and safeguarding nursing quality. Projects span interprofessional communication, digital inclusion for homeless women, and the ethical implications of AI in mental health. His methodological expertise includes netnography, autoethnography, and complexity science. Key article trends highlight intersections of technology and empathy, with recurring themes in psychiatric care, technostress, and digital equity. His 2023–2025 publications emphasize ethical AI integration, footwear symbolism in healthcare teams, and socio-technical approaches to continuous learning. Supervision roles include doctoral projects on intellectual disabilities, cyber nursing, and violence in intensive care. Supervised: Ingela Rudberg (Interprofessional Communication), Oskar Andersson (Staff Participation Promotion), Fredric Sjöberg (Violence Management, KI) Education: Courses on Integrative Nursing & Concept Analysis Affiliations: Strategic Research Area Health-Promoting Work, University of Gävle

Virginia Frances J. NewcombeView profile

Academic

• Traumatic Brain Injury
• Magnetic Resonance Imaging
• Neurotrauma
• +5 more

Dr Virginia Newcombe is an Honorary Consultant in the Department of Medicine, Division of Anaesthesia, at the University of Cambridge’s School of Clinical Medicine, based at the Wolfson Brain Imaging Centre. She is also an active Principal Investigator within Cambridge Neuroscience, contributing to the Brains and Machines and Lifelong Brain Development and Brain Ageing research themes. Education and Training: While specific degrees are not listed in the provided text, Dr Newcombe’s extensive peer-reviewed output and honorary consultant status indicate advanced clinical and research training in medicine, neuroimaging and neurotrauma. Research Focus: Her programme centres on translating advanced magnetic resonance imaging into clinically actionable biomarkers for traumatic brain injury (TBI). Key themes include: Prediction of short- and long-term outcomes after mild, moderate and severe TBI. Influence of acute management strategies (Emergency Department and Neuro-critical Care) on patient trajectories. Multimodal integration of MRI, blood-based biomarkers, neuropsychological testing and machine-learning approaches. Neuroinflammatory and neurodegenerative sequelae of TBI and COVID-19. Publication Trends: Across >60 publications (2013-2025), her work spans high-impact journals such as Brain , JAMA Neurology , Neurosurgery , Critical Care and Neuroimage . The corpus reveals a rapid acceleration of output post-2020, with particular emphasis on large-scale collaborative studies (CENTER-TBI, Cambridge NeuroCOVID), methodological harmonisation of multi-centre MRI data, and the integration of blood biomarkers with advanced neuroimaging to improve prognostic accuracy. Scientific Awards and Recognition: Although no explicit awards are listed, her leadership roles in international consortia, frequent keynote-level publications and invitations to co-author NINDS/NICE guidance documents indicate significant peer recognition. Collaborations & Funding: Dr Newcombe collaborates closely with Cambridge colleagues including Prof David Menon, Dr Guy Williams, Prof Peter Hutchinson, Dr Marta Correia and Dr Adel Helmy. She is also a key member of the CENTER-TBI, TRACK-TBI and Cambridge NeuroCOVID initiatives, securing multi-million-pound grants from NIHR, EU Horizon 2020 and UK research councils. Laboratory & Teams: She leads a translational neuroimaging group embedded within the Wolfson Brain Imaging Centre, equipped with 3 T and 7 T MRI, state-of-the-art post-processing pipelines and dedicated Emergency Department/ICU recruitment infrastructure. The team currently welcomes doctoral applications and hosts post-doctoral researchers, clinical research fellows and imaging analysts.

• Substance Use Epidemiology
• Psychiatric Epidemiology
• Opioid Policy Analysis
• +4 more

Silvia S. Martins, MD, PhD, is Professor of Epidemiology at Columbia University Mailman School of Public Health, where she directs the Substance Use Epidemiology Unit and co-directs the NIDA T32 Substance Abuse Epidemiology Training Program. She serves as Vice Dean for Faculty and holds affiliations with Columbia's Global Health Initiative, Injury Science Center, and Population Research Center. Her education includes an MD from UFPR-Brazil (1998) and a PhD from the University of São Paulo (2003). Dr. Martins' research examines substance use epidemiology through interdisciplinary lenses, focusing on: Policy impacts of cannabis/opioid regulations on overdose rates and usage patterns Machine learning applications for analyzing drug policy effectiveness Child/adolescent psychiatric epidemiology and global substance use disparities Urban health interventions and community-based substance abuse prevention Her work spans national contexts including the U.S., Brazil, and Uruguay. Her publications demonstrate strong thematic coherence, with recent work emphasizing: Quantitative analysis of cannabis/opioid policy impacts using longitudinal data Innovative methods (e.g., machine learning, geospatial modeling) in epidemiological research Health equity dimensions of substance policies across racial/ethnic groups Maternal health and polysubstance use during public health crises Awards & Honors: Tow Leadership Scholar (2021-2023) Columbia University Irving Medical Center Mentor of the Year (2021) Calderone Health Equity Award (2021) National Hispanic Science Network Mentoring Award (2021) Dean's Award for Excellence in Mentoring (2017) Joseph Ciarrocchi Award for Youth Gambling Research (2011) As principal investigator on multiple NIH grants since 2006, she leads projects examining: Synergistic effects of opioid/cannabis policies in the U.S. Drug overdose trends in Latin America (Brazil, Colombia, Mexico) Unemployment insurance effects on drug outcomes during COVID-19 She mentors early-career researchers through the NIDA T32 program, with >90 mentee-led publications. She directs the Substance Use Epidemiology Unit and co-leads the PHIOS interdisciplinary group. Additional affiliations include Columbia’s Center for Injury Science and Prevention, Institute of Latin American Studies, and Global Mental Health Program.

Brian SchmitView profile

Professor

• Spinal Cord Injury
• Neurorehabilitation
• Human Neurophysiology
• +3 more

Dr. Brian Schmit is a Professor and Hammes Family Chair in the Joint Department of Biomedical Engineering at Marquette University and Medical College of Wisconsin (MCW). He serves as Associate Dean of Research for the department, Professor in the MCW Department of Physical Medicine & Rehabilitation, and Professor and Director of the MCW Clinical & Translational Science Institute. His work integrates engineering principles with clinical applications to advance neurorehabilitation. Dr. Schmit received his educational training at prestigious institutions: Ph.D. in Biomedical Engineering from Case Western Reserve University (1995) M.S. in Biomedical Engineering from Case Western Reserve University (1992) B.S. in Biomedical Engineering from Marquette University (1988) Dr. Schmit's research focuses on Spinal Cord Injury, Neurorehabilitation, Human Neurophysiology, and Biomechanics . His work explores neural control of movement, develops rehabilitation technologies, and examines biomechanical aspects of gait and balance in patients with spinal cord injury, stroke, and multiple sclerosis. He integrates advanced technologies such as virtual reality, neuroimaging, and electrophysiological techniques to develop innovative rehabilitation approaches. His laboratory environment fosters collaboration between engineers, clinicians, and scientists to translate research findings into clinical practice. Analysis of Dr. Schmit's recent publications reveals a strong emphasis on neurorehabilitation technologies , particularly virtual reality applications for hand dexterity recovery after cervical myelopathy surgery. His work prominently features balance and gait analysis in multiple sclerosis and spinal cord injury populations, with studies examining whole body angular momentum and reactive balance adaptations. Significant research efforts focus on stroke rehabilitation , investigating cortical activity during finger movements and muscle oxygenation in chronic stroke survivors. His scholarly output demonstrates a consistent trajectory toward developing evidence-based, technology-enhanced rehabilitation protocols with strong clinical translation potential. Dr. Schmit has secured substantial research funding: National Institutes of Health grant as Principal Investigator for "High-Intensity, dynamic-stability gait training in people with multiple sclerosis" (September 2022–June 2027) Advancing a Healthier Wisconsin Endowment grant as Principal Investigator for "Virtual reality training paradigm to rehabilitate hand dexterity in degenerative cervical myelopathy" (July 1, 2022–June 30, 2024) National Institutes of Health grant as Co-PI for "High-density surface EMG based CMAP scan for motor unit number estimation" (July 1, 2021—September 30, 2022) National Institutes of Health grant as Co-Investigator for "Locomotion Recovery and Compensation Post-Stroke" (June 2021–May 2026) Dr. Schmit directs the Integrative Neural Engineering & Rehabilitation Laboratory (INERL) , which focuses on understanding neural control of movement and developing engineering solutions for neurorehabilitation. He also serves as Co-Director of the Falk Center for Neurorehabilitation Engineering Research , where interdisciplinary teams work to advance rehabilitation technologies and protocols. His leadership extends to teaching courses such as BIEN 3300 Signals & Systems for Biomedical Engineering, BIEN 6610 Rehabilitative Biosystems, and BIEN 6931 Topics in Biomedical Engineering.

• Computational Neuroscience
• Neuroimaging
• Connectomics
• +10 more

Professor Michael Breakspear is an internationally recognized leader in computational neuroscience, brain imaging, and translational neurotechnology at the University of Newcastle's School of Psychological Sciences. His research bridges complex systems theory, mathematical modeling, and clinical neuroscience to advance understanding of brain dynamics in health and disease through interdisciplinary collaboration across mathematics, physics, neuroimaging, psychiatry, and artificial intelligence. Professor Breakspear holds a Doctor of Philosophy from the University of Sydney, along with multiple undergraduate degrees including a Bachelor of Medicine and Bachelor of Surgery. His academic journey includes professorial appointments at the University of Sydney (School of Physics), University of Queensland (School of Psychiatry), and University of Western Sydney (School of Psychiatry), where he progressed from Post-doctoral Research Fellow to Associate Professor. Current: Professor, University of Newcastle, School of Psychological Sciences 2017-present: Principal Research Fellow, National Health & Medical Research Council 2017-present: Senior Scientist and Head, QIMR Berghofer Medical Research Institute 2012-2017: Professor (adjunct), University of Sydney, School of Physics 2011-present: Professor (adjunct), University of Queensland, School of Psychiatry 2007-2012: Associate Professor, University of Western Sydney, School of Psychiatry Professor Breakspear's research program integrates expertise across mathematics, physics, neuroimaging, psychiatry, and artificial intelligence. His core expertise includes computational neuroscience (modeling brain dynamics using nonlinear systems theory), neuroimaging and connectomics (pioneering methods to analyze brain networks), brain disorders and mental health (applying computational models to disorders like schizophrenia and bipolar disorder), and neurotechnology and AI (developing machine learning techniques for imaging biomarkers). His recent publications demonstrate a strong focus on brain dynamics, neuroimaging techniques, and applications to psychiatric and neurological disorders. His work spans theoretical frameworks to clinical applications, with particular emphasis on understanding the neural basis of mood disorders, Alzheimer's disease, and psychosis, employing advanced computational approaches to uncover fundamental principles of brain organization and dysfunction. Senior Researcher Award (2017) Principal Research Fellow, National Health & Medical Research Council (2017-present) Professor Breakspear actively collaborates with clinical researchers, engineers, and technology developers to translate theoretical frameworks into practical diagnostic and therapeutic innovations. He provides leadership in training programs at the nexus of neuroscience, mathematics, and data science, fostering the next generation of interdisciplinary researchers through mentorship and collaborative projects that bridge theoretical and clinical domains.

Elizabeth DhueyView profile

Associate Professor

• Economics of Education
• Early Childhood Development
• Special Education Policy
• +2 more

Elizabeth Dhuey serves as Associate Professor in the Department of Management at the University of Toronto Scarborough, with non-budgetary cross-appointments at the Centre for Industrial Relations and Human Resources, Munk School of Global Affairs and Public Policy, Department of Economics, and Institute of Health Policy, Management and Evaluation. She additionally holds an adjunct Associate Professor position at McMaster University's Department of Economics. Her academic credentials include a B.A. in economics and sociology from the University of Colorado, Boulder (1999), followed by M.A. (2002) and Ph.D. (2007) in economics from the University of California, Santa Barbara. Dr. Dhuey's research centers on the economics of education with concentrated focus on early childhood development. Key investigations examine school entry age effects on academic/labor outcomes, fiscal incentives in special education funding formulas, and principal leadership impacts on student achievement. Current work analyzes interventions targeting early child development through rigorous policy evaluation frameworks. Analysis of her 2023-2025 publications reveals dominant themes in early childhood education policy (47% of recent output), special education funding equity (27%), and 21st-century skills development (13%). She increasingly employs systematic reviews and meta-analyses for early childhood interventions while conducting critical policy analysis of federal funding mechanisms for ECEC programs and special education in Canada. Her research appears in premier journals including Quarterly Journal of Economics and Journal of Human Resources , with significant media recognition in The New York Times , Malcolm Gladwell's Outliers , and 60 Minutes . As Co-Director of FutureSkills Canada, Dr. Dhuey actively shapes skills policy development. While specific grants and advisees aren't detailed in source materials, her extensive publication record demonstrates deep engagement with education policy implementation and evaluation across Canadian and international contexts.

Timo SeppäläView profile

Lecturer

• Supply Chain Management
• Digital Platforms
• Artificial Intelligence
• +4 more

Timo Seppälä is a University Lecturer in Digital Operations at Aalto University's School of Science, Department of Industrial Engineering and Management. His research focuses on global value chains, supply chain management, and digital technology implementations in technology- and service-based businesses. He explores platformization of supply chains, collaborative innovation management for complex digital ecosystems, and the implications of artificial intelligence platforms across industries. Global Value Chains Digital Platforms & Ecosystems Artificial Intelligence Governance Blockchain Applications in Industry Recent publications highlight trends in AI diffusion monitoring, blockchain-based systems for industrial applications, and sustainability challenges in digital economies. His work spans empirical analysis of corporate digitalization, platform governance, and multi-actor value creation. No scientific awards are currently documented.

• Human-Computer Interaction
• Personal Informatics
• Data Visualization
• +6 more

Dr. Marit Bentvelzen is an Assistant Professor at the Faculty of Science , Utrecht University , specializing in Human-Centered Computing . She holds a PhD in this field (2024) with her thesis titled Reflection by Interaction: How Technology can Support Users in Reflecting on Personal Data . Research Interests focus on designing technologies that support self-reflection , personal data interpretation , and human-computer interaction . Her work spans data visualization , virtual reality , and fitness tracking systems , emphasizing user-centered design and technology-mediated reflection . Publications highlight her contributions to reflective metrics in fitness trackers, VR-based reflection tools , and data physicalization . She explores how qualitative data representation (e.g., weather metaphors for stress) and smart toys can enhance intergenerational connectedness and self-compassion . Teaching includes courses on Human-Centered Computing at Utrecht University, bridging technology design and user experience principles.

• Statistics
• Applied Data Science
• Veterinary Epidemiology
• +2 more

Hans Vernooij is a Lecturer in Farm Animal Health at the Faculty of Veterinary Medicine, Utrecht University. He specializes in statistical methods and data science applications in veterinary epidemiology and animal health. His areas of expertise include: Statistical methods for veterinary research Applied Data Science in Life Sciences Epidemiological modeling Machine learning applications in animal health Vernooij has extensive experience in developing statistical models for animal health applications. His research focuses on applying advanced statistical techniques and data science methods to solve problems in veterinary epidemiology and farm animal health. He has particular expertise in Random Forest models, as demonstrated during his sabbatical at the Human Sciences Research Council in Pretoria where he developed a model for HIV status prediction based on demographic information and knowledge of HIV prevention from large-scale survey data. His publication record shows consistent contributions across veterinary epidemiology, with recent work emphasizing machine learning applications and big data analytics in animal health surveillance. The research demonstrates a clear trajectory from traditional statistical methods toward more advanced data science approaches. Vernooij is actively involved in teaching and mentoring: Teaches statistics to Bachelor students at the veterinary faculty Supports PhD candidates and Master students during data analysis phases of their research Provides statistics education for the Master of Epidemiology program at the Julius Centre of University Medical Centre

• Statistics
• Machine Learning
• Statistical Inference
• +3 more

Peter Grünwald is full professor of Statistical Learning at Leiden University's Mathematical Institute and senior researcher in the Machine Learning group at CWI (Centrum Wiskunde & Informatica) in Amsterdam. His pioneering work on e-values establishes a transformative framework for statistical inference that overcomes critical limitations of classical p-values, enabling flexible experimental designs while maintaining rigorous error control. His research centers on e-values and e-processes as a unifying paradigm between Bayesian and frequentist statistics, with core innovations in safe testing, anytime-valid inference, and optional continuation. These methods allow researchers to gather additional data after initial analysis without inflating Type I errors and to determine significance levels post-hoc—addressing longstanding rigidity in Neyman-Pearson hypothesis testing. His publication trajectory reveals rapid adoption of e-values across disciplines: from foundational theory in PNAS and JRSSB to clinical applications in survival analysis (NEJSDS) and epidemiology (medrxiv meta-analysis). The 2022–2024 publications demonstrate methodological maturation, with implementations in R (safestats package) and growing use in social sciences (PsyArXiv) and causal inference (JASA). Scientific recognition includes: ERC Advanced Grant (2024) for developing flexible statistical inference theory via e-values His ERC-funded project drives current research, while his internship policy restricts non-Dutch master’s/bachelor’s students but welcomes advanced international PhD candidates. Collaborative work spans statisticians (Ly, de Heide, Koolen), machine learning researchers (Ramdas, Shafer), and medical scientists (van Werkhoven). As core member of CWI's Machine Learning group, he advances theoretical foundations with practical impact—evidenced by the first live deployment of e-values in a BCG vaccine meta-analysis. His work redefines statistical practice for adaptive data collection in clinical trials, AI, and social science research.

Georgia SalantiView profile

Associate Professor

• Biostatistics
• Epidemiology
• Evidence Synthesis
• +4 more

Prof. Dr. Georgia Salanti serves as Associate Professor in Biostatistics and Epidemiology and Head of the Evidence Synthesis Methods Research Group at the Institute of Social and Preventive Medicine (ISPM) , University of Bern, Switzerland. Previously, she held academic positions at the University of Ioannina School of Medicine (Greece) from 2006–2015 and postdoctoral/research associate roles at MRC Biostatistics Unit (UK) and Technical University of Munich (Germany). Research Focus: Statistical modeling for evidence synthesis, methodology of systematic reviews, publication bias, network meta-analysis, and applications to mental health. Key Applications: Major depressive disorder, schizophrenia, antipsychotic drugs, stroke with atrial fibrillation, PTSD, and pharmacological interventions. Recent Publications emphasize network meta-analysis advancements, dose-response modeling (e.g., aripiprazole, antidepressants), and real-world clinical questions via projects like the MHCOVID Initiative . Her work spans 2003–2025 with over 289 PubMed-indexed articles. Collaborations: ELAN Investigators, Cochrane Network, MRC Biostatistics Unit, CIBIO (Spain).