Prof. Raffaello D'Andrea is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, affiliated with the Institute for Dynamic Systems and Control. His research focuses on bridging digital and physical worlds through robotics, control systems, and autonomous systems. He has pioneered work in aerial robotics, swarm systems, tactile sensing, and soft robotics. His philosophy emphasizes solving 'easy' problems with scalable, robust solutions, prioritizing simplicity and replicability. Key research areas include UAV navigation, distributed control, tactile sensor design, and fault-tolerant systems. He has founded multiple organizations and led roles as CTO/CEO, emphasizing cross-disciplinary innovation. His work has commercial applications in logistics, healthcare, and automation, driven by a belief in technology's role in improving human life. Notable projects include the Cubli robotic cube, aerial vehicle swarms, and optical tactile sensors for robotics. His lab emphasizes collaboration and team leadership, aiming to translate theoretical insights into practical, scalable technologies. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No students listed in the provided texts; grants information not detailed. Labs/Teams: Leads research at ETH Zurich's Institute for Dynamic Systems and Control, collaborating with industry and academic partners globally.
Wim Gevers is a faculty member at the Université libre de Bruxelles (ULB) and leads the CS4S – Cognitive Control & Sleep laboratory within the CRCN research centre. His work bridges cognitive psychology, neuroscience and sleep research to understand how the brain exerts control over thoughts and actions and how sleep contributes to these processes. Research Interests Cognitive Control & Metacognition: Investigating how subjective experiences such as confidence and the "urge-to-err" guide strategic adjustments in behaviour. Working Memory & Ordinal Cognition: Examining how order information is maintained and manipulated, and how these processes relate to mathematical competence. Sleep, Memory & Decision Making: Exploring how sleep-dependent consolidation influences motor learning and decision strategies. Across his 2022–2025 publications a clear trend emerges: a focus on metacognitive monitoring —how humans evaluate their own cognitive states—and the role of emotional and temporal context in shaping those evaluations. Studies range from reaction-time introspection and confidence judgements in perceptual tasks to the impact of aging and depression on metacognitive accuracy. Doctoral Supervision & Mentoring Whitney Stee (PhD 2024) – Sleep-dependent structural brain reorganization & motor learning Gaia Corlazzoli (PhD 2024) – Subjective experience in decision-making Myrtille Dewulf (PhD 2023) – Ordinal coding mechanisms in working memory Rebeca Sifuentes-Ortega (PhD 2023) – REM sleep and memory reactivation All dissertations were defended at ULB, Faculté des Sciences psychologiques et de l’éducation, with Wim Gevers formally listed as Promotor . Laboratory & Collaborative Networks As head of CS4S, Gevers coordinates a multidisciplinary team that combines behavioural experimentation, EEG/MEG, computational modelling and sleep polysomnography. The lab is embedded in the larger CRCN ecosystem, fostering collaborations with groups such as CO3 (consciousness), LCLD (language & deafness), and UR2NF (neurofunctional imaging).
Dr. Qing Zhou is a Professor of Psychology at the University of California, Berkeley, and Director of the Culture and Family Study Lab. He received his Ph.D. from Arizona State University and specializes in understanding how cultural context, family dynamics, and temperament influence children's socio-emotional, academic, and executive function development, with a focus on immigrant families. Key research interests include: Developmental psychopathology Temperament and emotion regulation Family socialization and parenting Impact of bilingualism on child development Cultural values and migration effects on adjustment His work employs multi-method approaches, including questionnaires, behavioral observations, and neuropsychological testing, with ongoing projects like the NICHD-funded longitudinal study on dual language learners and the Chau Hoi Shuen Foundation-supported grandparent involvement research. Collaborations include scholars at UC-Davis, UC-Merced, Wellesley College, and institutions in France and Taiwan. Dr. Zhou has trained numerous students, including current doctoral candidates Xinyi Chen, Erika Roach, and Christopher Gys, as well as alumni at institutions like Harvard, Stanford, and UCSF. His lab's publications emphasize cross-cultural comparisons, longitudinal designs, and intervention implications for immigrant youth.
Daan Christiaens is a tenure track lecturer at KU Leuven's Faculty of Medicine and Faculty of Engineering Sciences. He is affiliated with the Department of Electrical Engineering (ESAT) and Department of Imaging & Pathology, serving as a member of the Medical Imaging Division and the KU Leuven Brain Institute (LBI). His academic responsibilities include membership in the Faculty Councils of Engineering Sciences and Medicine. His research focuses on: Inverse problems in medical imaging reconstruction Neuroimaging techniques for brain analysis Advanced quantitative MRI methodologies Diffusion-weighted imaging for microstructural assessment Dr. Christiaens' recent publications (2023-2025) demonstrate a consistent focus on diffusion MRI innovations, including novel reconstruction algorithms, neonatal brain development mapping, and clinical applications for neurodegenerative disorders. Key technical themes include motion correction, multi-shell modeling, and AI-enhanced image processing, while clinical applications span Alzheimer's disease, cerebral palsy, and autism research. He leads significant research projects including: MRI reconstruction with dynamic field monitoring (2024-2028) Compressed sensing for microstructure imaging (2022-2026) Neonatal diffusion MRI network connectivity analysis (2024-2028) As a core developer of the MRtrix3 software framework for medical image processing, he contributes to essential tools in neuroimaging research.
Prof. Abbas Samani is a Professor at the Department of Electrical and Computer Engineering and holds a joint appointment in the Department of Medical Biophysics at Western University . He is a core faculty member of the Biomedical Engineering Graduate Program and an Associate Scientist at Imaging Research Laboratories of Robarts Research Institute . His academic journey includes a Ph.D. from the University of Waterloo, an M.Sc. from the University of Tehran, and a B.Sc. from Amirkabir University of Technology. His research focuses on biological tissue computational modeling and its applications in medical imaging, intervention, and image analysis . He develops computer/image-assisted tools for minimally invasive disease diagnosis and therapy , targeting heart disease, cancer, and lung disease . Key projects include myocardium biomechanical modeling , handheld medical devices for breast cancer screening , and lung disease diagnostics via CT image segmentation . His recent publications emphasize ultrasound elastography , finite element modeling , and inverse problems in biomechanics , primarily in journals like IEEE Transactions on Computational Imaging and Translational Oncology . His work spans both computational modeling and medical device development . Selected Graduate Supervision : Ph.D. Candidates : Seyed Hassan Haddad, Elham Karami, Seyed Mohammad Hesabgar Graduated Ph.D. Students : Ali Sadeghi Naini, Seyed Reza Mousavi M.Sc. Students : Cristian Linte, Patrick Courtis, Joseph O'Hagan, Hatef Mehrabian, Hirad Karimi, Hosein Amooshahi, Seyed Mohammad Hesabgar, Nastaran Ghadarghadr, Shadi Shavakh, Ehsan Salamati, Ehsan Omidi Teaching Contributions : Graduate: BME9519B/CAMI9519B/ECE9202B/ECE9022B - Advanced Image Processing and Analysis , MBP9530A - Human Biomechanics and Biomedical Applications Undergraduate: ECE4438B - Advanced Image Processing and Analysis , ES1050 - Introductory Engineering Design and Innovation Studio , MBP3330F - Human Biomechanics and Biomedical Applications Research Affiliations : Robarts Research Institute - Associate Scientist at Imaging Research Laboratories Western University - Core Faculty, Biomedical Engineering Graduate Program
Heather A. Jones, Ph.D., serves as Associate Professor in the Department of Psychology within Virginia Commonwealth University's College of Humanities and Sciences, holding joint appointments with the Department of African American Studies, Department of Pediatrics, and Institute for Women's Health. As a licensed clinical psychologist in Virginia, she maintains an active research program focused on reducing mental health disparities through culturally responsive interventions. Ph.D. in Psychology, University of Maryland at College Park (2006) Dr. Jones' research centers on three interconnected pillars: Black children and families' mental health, maternal mental health across the perinatal spectrum, and training culturally competent clinical psychologists. Her work specifically examines ADHD manifestations in Black youth, impacts of racial discrimination on adolescent mental health, and integration of behavioral health services within primary care settings. She employs mixed-methods approaches to address systemic barriers in mental healthcare access for underserved communities. Analysis of her 2023-2025 publications reveals consistent emphasis on health equity through studies of cultural competence in cancer survivorship, ADHD treatment representation gaps, and digital interventions for perinatal depression. Her methodological approaches span latent class analyses of service utilization, content analyses of historical research biases, and clinical trials of integrated care models, all contextualized within structural determinants of health. Dr. Jones has received significant recognition for her contributions: VCU College of Humanities and Sciences Distinguished Teaching Award (2023) VCU Department of Psychology Outstanding Mentoring Award (2023) Elizabeth Fries Young Investigator Award (2016) Clinical and Translational Research Award (2016) She actively mentors students, particularly supporting Black graduate trainees in pediatric psychology as evidenced by numerous student co-authorships. As Principal Investigator, she directs the $1.4M HRSA-funded Primary Care Psychology Training Collaborative providing pro bono services to urban Richmond and rural Virginia communities, recently expanded through an additional $1.1M grant serving Latinx immigrants and refugees. Her federally funded work consistently bridges research, clinical service, and community engagement. Dr. Jones co-directs the Families and Mental Health Research Lab and Primary Care Psychology Training Collaborative, leading interdisciplinary teams comprising psychology graduate students, pediatric residents, and community health workers. These initiatives operate within VCU's integrated primary care clinics, focusing on implementation science to scale evidence-based practices for underserved populations while training the next generation of healthcare providers.
Carlos Fernandez-Granda is an Associate Professor of Mathematics and Data Science at New York University, holding joint appointments at the Courant Institute of Mathematical Science and the Center for Data Science. He currently serves as the Interim Director of the Center for Data Science. His academic career spans over a decade at NYU, where he has taught probability and statistics to data-science students. Dr. Fernandez-Granda's research focuses on designing and analyzing data-science methodology, with current emphasis on machine learning applications in medicine, climate science, and scientific imaging. His work bridges theoretical foundations with practical applications across multiple domains. His notable contributions include: Development of the COBRA (COnfidence-Based chaRacterization of Anomalies) score for automatic assessment of impairment and disease severity Applications of machine learning to improve climate projections through the M2LInES project Research on magnetic resonance fingerprinting for quantitative tissue parameter estimation Development of AI systems for medical diagnostics including Alzheimer's detection and breast cancer diagnosis Dr. Fernandez-Granda is the author of the book "Probability and Statistics for Data Science," published by Cambridge University Press. The book serves as a comprehensive guide to the two pillars of data science, featuring real-world datasets and addressing fundamental challenges like overfitting, the curse of dimensionality, and causal inference. His research has been supported by grants from the National Science Foundation (Division of Mathematical Sciences, grants 1616340 and 2009752) and the Alzheimer's Association (grant AARG-NTF-21-848627). Dr. Fernandez-Granda is actively involved in several collaborative projects: M2LInES project: An international collaboration focused on improving climate projections using machine learning to capture unaccounted physical processes at the air-sea-ice interface Math and Data group: Exploring the intersection of mathematical theory and data science applications
Kep Kee Loh is a Senior Tutor in the Department of Psychology at the National University of Singapore (NUS). Currently, he also holds an NUS Overseas Postdoctoral Fellowship position at both the Montreal Neurological Institute (McGill University) and the University of Oxford. His research focuses on comparative primate neuroanatomy, examining what makes the human brain special compared to other primates through multimodal MRI techniques. Ph.D. in Neuroscience from Université Claude Bernard Lyon I (2014-2018) M.Sc. in Cognitive Neuroscience from University College London (2011-2012) B.Soc.Sci. (Hons.) in Psychology from National University of Singapore (2007-2011) Dr. Loh's research primarily investigates the anatomical organization of brains across humans and various primate species including chimpanzees, baboons, and macaques. He employs different magnetic resonance imaging techniques (anatomical, resting-state, diffusion-weighted MRI) to compare brain organization across species, with particular focus on the medial frontal cortex, sulcal anatomy, and the evolution of speech and language in the human brain. His work adopts a multimodal approach to provide an integrative view of what sets human brains apart from other primates. His recent publications demonstrate a strong focus on comparative neuroanatomy across species, with particular emphasis on primate brain evolution, frontal cortex organization, and language-related neural pathways. The research spans multiple disciplines including neuroscience, cognitive science, and evolutionary biology, with increasing attention to methodological advancements in neuroimaging techniques for cross-species comparisons. NUS Overseas Postdoctoral Fellowship (2021) Institute of Language, Communications and the Brain (ILCB) Postdoctoral Fellowship (2019) Fondation Recherche Médicale (FRM) Fin de Thèse (PhD funding) (2017) BRAIN Student Travel Award, 6th Motivation and Cognitive Control Symposium (2016) Dr. Loh has been involved in numerous collaborative research projects across international institutions, including the French Institute of Health and Medical Research (Stem Cell and Brain Research Institute), Aix-Marseille Université, and currently McGill University and the University of Oxford. His work has received significant recognition with over 1,000 citations for his 33 publications. While specific grant information isn't detailed in the provided text, his postdoctoral fellowships indicate successful competitive funding. Dr. Loh collaborates with several research groups including the Montreal Neurological Institute at McGill University and research teams at the University of Oxford. His work connects with broader initiatives like the collaborative resource platform for non-human primate neuroimaging, indicating participation in larger research networks focused on advancing primate neuroscience through shared resources and methodologies.
Dr Deborah Wells is a Reader in the School of Psychology at Queen's University Belfast, specializing in animal welfare and behavior, particularly in dogs and cats. Her research focuses on improving psychological welfare of animals, human-animal bond, and laterality studies. She holds a PhD from Queen's (1996) and has been a lecturer since 1999. Education: BSc (Hons) Psychology, Queen's University Belfast, 1992 PhD in Animal Welfare, Queen's University Belfast, 1996 Research Interests: Animal welfare assessment, laterality in animals, enrichment strategies, and pets' impact on human health. Recent work includes studies on auditory enrichment for dogs and equine-assisted therapy. Awards: Multiple grants and awards, including CAST DfE Collaborative PhD Studentships and the Most Popular Paper Award. Teaching & Grants: Teaches animal behavior modules and supervises PhD students. Leads projects like the KTP with Devenish Nutrition and lateralised behavior research. Active in the Animal Behaviour Centre. Labs/Teams: Director of the Animal Behaviour Centre, promoting interdisciplinary research in animal welfare.
Irena Koprinska is a prominent researcher at the University of Sydney with over 150 publications from 1996 to 2025. Her work spans multiple interdisciplinary domains with significant contributions to machine learning applications in educational technology, time series forecasting, and health informatics. She maintains strong research collaborations, particularly with Kalina Yacef (38 joint publications), Mashud Rana (26 papers), and Bryn Jeffries (22 papers), indicating leadership in her research group. Her research interests focus on practical applications of machine learning across diverse domains. In educational data mining, she has pioneered methods for predicting student performance in programming courses, analyzing syntax errors, and developing automated hint generation systems. Her work in time series forecasting has made significant contributions to solar power prediction using advanced neural network architectures. Additionally, she has applied machine learning techniques to medical domains, particularly in sleep disorder detection and analysis. The analysis of her 15 most recent publications (2022-2025) reveals a continued focus on educational technology and time series analysis, with increasing attention to interpretable methods and health applications. Her work demonstrates a consistent trajectory of applying sophisticated machine learning techniques to solve real-world problems across multiple domains, with particular emphasis on creating practical tools for education and renewable energy management. Notable Research Contributions: Development of the HINTS framework for automated programming hint generation Innovative approaches to multistep-ahead time series forecasting Applications of deep learning to sleep disorder detection Methods for predicting student performance in programming education Her publication record in top venues including Machine Learning journal, AIED, EDM, and IJCNN demonstrates significant impact in both machine learning and educational technology communities. The consistent output of high-quality research over nearly three decades indicates sustained scholarly productivity and leadership in her fields of expertise.
Professor Lyudmila Mihaylova is a distinguished academic at the University of Sheffield's School of Electrical and Electronic Engineering, where she holds the position of Professor of Signal Processing and Control. She has established herself as a leading researcher in the fields of signal processing, Bayesian methods, and autonomous systems, with significant contributions to particle filtering techniques for intelligent transportation systems. Her work bridges theoretical developments with practical applications across multiple domains including transportation, healthcare, and industrial automation. Prof. Mihaylova's research interests center on nonlinear filtering, sequential Monte Carlo methods, statistical signal processing, and sensor data fusion. Her work spans both theoretical advancements and practical implementations, with particular focus on high-dimensional problems including vehicular traffic flow estimation, image processing, and localization in sensor networks. She has extensive experience with various image modalities such as optical, thermal, LIDAR, SAR, and hyperspectral imaging. Her group actively develops novel methods for autonomous intelligent systems focusing on sensing, tracking, decision making, and machine learning applications. Analysis of Prof. Mihaylova's recent publications reveals a strong trend toward uncertainty quantification in machine learning models, particularly for safety-critical applications. Her work increasingly integrates traditional signal processing techniques with modern deep learning approaches, with applications spanning sewer inspection robotics, medical diagnostics (particularly sleep apnea detection), UAV swarm tracking, industrial manufacturing, and autonomous vehicle systems. A significant portion of her recent research focuses on developing robust methods that can handle incomplete or outlier-corrupted data while providing reliable uncertainty estimates. Among her notable professional achievements: President of the International Society of Information Fusion (ISIF) Senior member of the IEEE Signal Processing Society Associate Editor for IEEE Transactions on Aerospace and Electronic Systems Associate Editor for Elsevier Signal Processing Journal Prof. Mihaylova has successfully mentored numerous PhD students and postdoctoral researchers, many of whom have gone on to prominent academic and industry positions. Her research has been supported by major funding bodies including EPSRC, EU, MOD/DSTL, and industry partners, with recent projects including 'Protecting Environments with UAV Swarms' (InnovateUK, 2022-2024), 'ShiRAS: Towards Safe and Reliable Autonomy in Sensor Driven Systems' (NSF-EPSRC, 2019-2023), and 'Confident safety integration for Cobots' (Lloyd's Register Foundation, 2019-2020). Her research group follows a collaborative approach with the philosophy 'We share knowledge, we grow.' Prof. Mihaylova maintains active research collaborations with institutions worldwide and has held previous academic positions at Lancaster University (2006-2013) and University of Bristol (2004-2006), along with research visiting positions at the University of Ghent, Katholic University of Leuven, and the Bulgarian Academy of Sciences.
Andreawan Honora is a Lecturer in Marketing at the UWA Business School, University of Western Australia, since February 2024, previously serving as a Postdoctoral Research Associate at Ivey Business School, Western University, Canada. His academic qualifications include: Ph.D. in Business Administration (Marketing) from National Dong Hwa University (awarded January 31, 2022) Master of Management (Marketing) (awarded July 31, 2017) Bachelor of Science in Management (Marketing) (awarded February 1, 2016) Honora's research examines how digital technologies shape consumer and employee behavior, focusing on service management, consumer-brand relationships, and psychological impacts. His work explores business applications of technology and contributions to social goals like health and well-being through experimental methodologies. His 2024-2025 publications reveal interdisciplinary trends spanning healthcare informatics (telemedicine, electronic health records), AI-driven workplace dynamics, and social media psychology. Key themes include technology-induced behavioral changes, service recovery mechanisms, and health-focused digital interventions, bridging marketing, information systems, and public health. Honora serves as co-applicant on a 2025 SSHRC Insight Development Grant (CAD 58,165) from Canada's Social Sciences and Humanities Research Council. No student advising information is available.
Adam Elga serves as Professor of Philosophy and Director of the Program in Linguistics at Princeton University, based in the Department of Philosophy with his office in Laura Wooten Hall (204). His contact information includes email adame@princeton.edu and phone 609 258-1477, confirming active institutional engagement. Elga's research spans philosophy of probability, decision theory, self-locating belief, and existential risk, with notable intersections in linguistics through his program directorship. His work addresses fragmentation in belief systems, cognitive instability, and rational decision-making under uncertainty, contributing significantly to epistemological frameworks and philosophical probability models. Recent publications (2020-2025) demonstrate sustained focus on existential risk analysis, decision theory paradoxes, and belief fragmentation. His scholarship bridges theoretical philosophy with practical applications in risk management and cognitive science, particularly through investigations of suboptimal risk decisions and cognitive limitations in high-stakes scenarios. Scientific awards: None mentioned in provided text. Advising and grants: The scraped text contains no information about doctoral students, mentees, or specific research funding. As a full professor and program director, he likely oversees graduate research and secures institutional support, though concrete details are absent from the source material. Labs and research teams: No dedicated laboratories, research groups, or collaborative teams are referenced in the available documentation.
Dr. Christine So is an Assistant Professor of Psychology at Washington State University, where she leads the Laboratory for Understanding Nocturnal behaviors and Affect (LUNA). Her research focuses on the intersection of sleep, trauma, and psychopathology, investigating how sleep disturbances serve as both causes and consequences of mental health disorders through multimodal research approaches. Dr. So's educational background includes: Ph.D. in Clinical Psychology from the University of Houston (2022) Pre-doctoral clinical internship at the University of Pittsburgh Medical Center Western Psychiatric Hospital MIRECC postdoctoral fellowship in trauma-related sleep disturbances at the Corporal Michael J. Crescenz VA Medical Center Her primary research interests examine mechanisms of trauma-related sleep disturbances, particularly nightmares, and how sleep problems function as transdiagnostic risk factors for health issues. Dr. So employs ecological momentary assessment, polysomnography, actigraphy, and computerized tasks to investigate cognitive and affective processes underlying sleep disruptions. Additional research areas include sleep health disparities, environmental influences on sleep, and personalized behavioral sleep medicine interventions targeting Alzheimer's risk biomarkers. Dr. So's publication record demonstrates consistent growth in sleep and trauma research, with recent work examining neighborhood effects on sleep in trauma-exposed populations, bidirectional sleep-pain relationships among Veterans, and sleep health disparities. Her research bridges clinical psychology, sleep medicine, and public health with particular attention to vulnerable populations including trauma survivors and Veterans. Dr. So has been recognized through a MIRECC postdoctoral fellowship supporting her specialized training. Her work appears in leading journals including Psychological Trauma: Theory, Research, Practice, and Policy , Sleep Health , and International Journal of Psychophysiology . As a licensed clinical psychologist in Washington state, Dr. So mentors graduate students in WSU's Clinical Psychology PhD program, with recruitment for Fall 2025 and 2026 cohorts underway. She maintains active collaborations with researchers at the University of Pittsburgh, University of Houston, and VA medical centers, particularly with Drs. Phil Gehrman and Katherine Miller. Her laboratory provides training opportunities for students interested in the intersection of sleep, trauma, and health. The Laboratory for Understanding Nocturnal behaviors and Affect (LUNA) serves as the hub for Dr. So's research program, focusing on how disrupted sleep acts as both precipitating and exacerbating factors of psychopathology, particularly in trauma contexts. The lab employs multimodal approaches to characterize cognitive and affective processes underlying nightmares and investigates environmental influences on sleep health disparities, with plans to expand into identifying sleep biomarkers of Alzheimer's risk.
Professor Andrew Coogan is a behavioral neuroscientist specializing in circadian rhythms, chronobiology, and sleep. He is a Professor at Maynooth University's Department of Psychology, part of the Faculty of Science & Engineering, and directs the Chronobiology and Sleep Research Laboratory. His research focuses on circadian clock function in human environments, with a strong emphasis on their impact on health conditions like ADHD, diabetes, and mental health. He holds a Bachelors from Trinity College Dublin and a PhD from University College Dublin, after which he worked in the UK before joining Maynooth in 2008, serving as Department Head from 2015–2021. Education: BSc (Trinity College Dublin), PhD (University College Dublin). Research Interests: His work spans circadian rhythms in disease contexts (e.g., ADHD, diabetes, Parkinson’s), sleep disorders, and societal impacts of light pollution. He investigates how circadian disruptions influence health outcomes, using interdisciplinary approaches combining neuroscience, chronobiology, and clinical studies. Recent studies focus on pandemic-related sleep changes, chronotherapeutics, and sleep timing in metabolic disorders. Publications & Grants: Over 120 peer-reviewed papers (H-index 44), funded by grants from Science Foundation Ireland, Health Research Board, and others. His articles analyze topics like vaccine timing, social jetlag in diabetes, and ADHD chronobiology. Collaborations span Europe, addressing global health challenges through circadian lens. Awards & Recognition: While no specific awards are listed, his extensive publications and leadership roles reflect significant scholarly impact. Advising & Teams: Supervised 11 PhD, 5 MSc, and 2 MD students. Leads the Chronobiology and Sleep Research Lab, collaborating widely on clinical and basic research projects. Future Work: Ongoing studies include circadian data collection in bipolar disorder (AMBIENT-BD) and societal-level sleep patterns post-pandemic. He advocates for evidence-based chronotherapeutic strategies in clinical settings.
