Dr. Bruno Kluwe-Schiavon, PhD, is a psychologist and serves as an instructor in the Department of Psychiatry and Behavioral Sciences at McGovern Medical School, University of Texas Health Science Center at Houston. He earned his PhD at the Laboratory of Experimental and Clinical Pharmacopsychology at the University Hospital of Psychiatry, University of Zurich, Switzerland. Subsequently, he completed a postdoctoral research fellowship at the Developmental Cognitive Neuroscience Lab at the Pontifical Catholic University of Rio Grande do Sul, Brazil, before joining the University of Lisbon, Portugal, as a junior researcher at the Research Center for Psychological Science, Decision in Context Lab.
Dr. Kluwe-Schiavon specializes in a wide array of statistical analyses, encompassing predictive techniques such as mixed linear models, penalized regressions, and machine learning algorithms. He performed inferential methods like regularized network analysis, path analysis, structural equations, and factor analysis. His publications extends to diverse topics in clinical and experimental psychology, including decision-making, substance use disorders, and early life experiences and his expertise includes meta-analysis, meta-regressions, and biostatistics. Additionally, he has contributed to the adaptation and validation of interviews, questionnaires, and neuropsychological tasks for both clinical and cognitive assessments.
With his background in data science, clinical and experimental psychology, and psychopathology, Dr. Kluwe-Schiavon collaborates with fellow researchers in processing extensive datasets and integrating clinical knowledge with data science. This involves translating clinical information into objective data and also deriving insightful clinical outcomes from data. His main research embraces psychopathology and decision-making within specific contexts, aiming to comprehend how the interplay of biopsychosocial factors contributes to the development of maladaptive decision-making profiles over time and how these profiles can aid in identifying early signs of psychopathological conditions.
Cumulative lifetime stressors
Substance use disorders
Statistical data analysis