جست‌وجوی استاد و پژوهشگر

Alexis Battleمشاهده پروفایل

دانشیار

• Genomics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .

Kathryn Roederمشاهده پروفایل

استاد

• Statistical Genetics
• Genomics
• Biostatistics
• +۵ مورد دیگر

Kathryn Roeder is the UPMC University Professor of Statistics and Life Sciences at Carnegie Mellon University (CMU), affiliated with the Dietrich College of Humanities and Social Sciences and the Departments of Statistics & Data Science and Computational Biology. Her research focuses on developing statistical methods for genetic and genomic data, particularly in identifying autism risk genes and analyzing single-cell multi-omic data. She earned her Ph.D. in Statistics from Penn State University and has been at CMU since 1994, previously serving as Vice Provost for Faculty (2015–2019). Education: Ph.D. in Statistics, Penn State University (1988) B.S. in Wildlife Resources, University of Idaho (1982) Research Interests: Her work integrates modern statistical techniques (high-dimensional statistics, machine learning, networks) to study complex diseases like autism and schizophrenia. Recent efforts include tools for analyzing single-cell RNA-seq and proteomic data, such as UNICORN, DAWN, and SCEPTRE. Key Awards: COPSS Distinguished Achievement Award (2020) National Academy of Sciences Member (2019) COPSS Presidents’ Award (1997) AAAS Fellow (2020) Advising & Grants: She has advised over 20 Ph.D. students, many contributing to landmark studies in autism genetics. Her grants include NIH funding for projects like the Autism Sequencing Consortium. Current research teams focus on computational biology and statistical genetics. Labs & Collaborations: Her lab develops software tools (e.g., TADA, MIND) and collaborates with the Autism Sequencing Consortium and iPSYCH-BROAD Consortium on large-scale genomic studies.

Maria Timofeevaمشاهده پروفایل

دانشیار

• Cancer Epidemiology
• Genetic Risk Factors
• Colorectal Cancer
• +۷ مورد دیگر

Maria Timofeeva is an Associate Professor in the Epidemiology, Biostatistics and Biodemography (EBB) department at the University of Southern Denmark (SDU), with additional affiliation at the Danish Institute for Advanced Study (DIAS). She holds an Honorary Fellow position at the University of Edinburgh since December 2019. Her research focuses on cancer prevention and prediction, particularly studying the effects of environmental and genetic factors on cancer risk and progression. Dr. Timofeeva earned her Dr.sc.hum in Epidemiology from Heidelberg University (2005-2009), with a dissertation on genetic polymorphisms as risk factors for early onset lung cancer. Prior to her current position, she worked as a Statistical Geneticist at the University of Edinburgh (2013-2019) and as a Postdoctoral Fellow at the International Agency for Research on Cancer (2009-2013). Her research interests center around understanding the genetics of cancer risk through multi-omic analysis. She leads several significant projects, including the Interdisciplinary Project on Adherence to Colorectal Cancer Screening, meta-analysis of factors associated with false-positive and false-negative FOBT results (registered in PROSPERO ID: CRD42022315767), and the COlorectal Cancer screening Among RElatives (CoCARE) twin-family study in Denmark. Her methodological expertise spans observational epidemiological studies (case-control, population-based cohort studies, twin studies), meta-analysis, umbrella reviews, and multi-omics data analysis. Analysis of her recent publications reveals a strong focus on colorectal cancer genetics, with particular emphasis on genome-wide association studies, Mendelian randomization approaches, and trans-ancestry analyses. Her work frequently leverages large datasets including the UK Biobank and international consortia, with applications in cancer risk prediction and understanding gene-environment interactions. Dr. Timofeeva has an extensive publication record with 73 publications listed in her profile. Her research has been cited across multiple platforms, with mentions in news outlets, social media, and academic readership platforms like Mendeley. She is actively involved in academic service, serving as a peer reviewer for journals including BMC Cancer and Scientific Reports, and participating in conferences such as the 26th Nordic Congress of Gerontology. She also serves on evaluation committees, including with the World Cancer Research Fund International (April-May 2024). Her teaching activities include courses on evidence-based drug utilization and biostatistics, as well as supervision of research projects on gene expression in twins. Dr. Timofeeva has engaged with the public through media contributions, including an interview titled 'Jeg vil forstå, hvorfor vi får kræft' (November 15, 2021), where she discussed understanding why we get cancer.

Sara Häggمشاهده پروفایل

مدرس ارشد

• Epidemiology
• Gerontology
• Medical Genetics and Genomics
• +۳ مورد دیگر

Sara Hägg is a Senior Lecturer at the Karolinska Institutet , affiliated with the Department of Medical Epidemiology and Biostatistics . She is also a Docent in molecular epidemiology. PhD in Computational Biology (Linköping University, 2009) MSc in Molecular Biology (Stockholm University, 2003) BSc in Computer Science (Stockholm University, 2003) Her research focuses on human biological aging , including measurement of aging markers (telomere length, epigenetic clocks, frailty index), causal pathway analysis, and identification of geroprotectors for age-related diseases. She utilizes longitudinal twin studies (SATSA, GENDER, HARMONY), UK Biobank, and Swedish cohorts with methods like Mendelian randomization and genome-wide analyses . Recent articles demonstrate trends in epidemiological aging research , with emphasis on cardiovascular aging , neurological disease interactions , metabolic profiling , and epigenetic clocks . Her work often involves multivariable modeling and cross-cohort validation . Leadership roles include Director of LifeGene Core Facility (2024-) and Founding Board Member of the Nordic Aging Society (2023-). She serves on expert groups for the Swedish Twin Registry and Strategic Research Area in Epidemiology and Biostatistics .

• Plastic and Reconstructive Surgery
• Hand Surgery
• Genetics of Musculoskeletal Disorders
• +۳ مورد دیگر

Dominic Furniss serves as Professor of Plastic and Reconstructive Surgery at the University of Oxford's Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), concurrently holding an Honorary Consultant Plastic Surgeon position. His clinical expertise centers on hand surgery and supermicrosurgery for lymphoedema treatment. His educational background includes undergraduate medical studies at Trinity College, Cambridge (Junior and Senior Scholar, first-class degree in genetic pathology) followed by clinical training at Oxford University Clinical School. He completed basic surgical training in London before returning to Oxford's Plastic Surgery Department in 2003. Professor Furniss leads pioneering research into genetic and non-genetic causes of hand conditions through multiple initiatives including the Furniss Group, Centre for OA Pathogenesis, and Hand Research Group. His work spans molecular genetics of Dupuytren's disease, carpal tunnel syndrome epidemiology, and kidney stone disease mechanisms. Recent investigations extend to AI applications in health data through the PHAIR study and causal inference methods in genetic epidemiology. Analysis of his 2024-2025 publications reveals a strategic shift toward large-scale epidemiological studies of hand injuries, interdisciplinary genetic research, and AI integration in surgical practice. These works bridge orthopaedics, genetics, and medical informatics with significant real-world clinical implications. His major scientific recognitions include: Pushpa Chopra Award Plenary Prize of the MRS Wellcome Trust Intermediate Fellowship (first awarded to a plastic surgeon) Professor Furniss has secured substantial research funding including the NIHR Clinical Lectureship (2007) and Wellcome Trust Fellowship (2012). He directs multiple research streams: RAMBOH-1 studies, Molecular Genetics of Carpal Tunnel Syndrome project, and HAWAII initiative. His team actively investigates public perceptions of health data sharing for AI through the PHAIR study while advancing supermicrosurgical techniques for lymphoedema. He maintains active leadership in the Athena SWAN gender equality initiative as a Self-assessment team member, demonstrating commitment to inclusive academic culture.

Hugues Aschardمشاهده پروفایل

پژوهشگر

• Statistical Genetics
• Genome-Wide Association Studies (GWAS)
• Microbiome Research
• +۷ مورد دیگر

Hugues Aschard is a Principal Investigator and Structure Manager at the Pasteur Institute in Paris, where he leads research in statistical genetics, microbiome analysis, and computational genomics. He is the principal investigator of the MicMat project, the EpiGenCOV Consortium, and several bioinformatics software initiatives including JASS, RAISS, and MGMM. Research Interests: Statistical and computational methods in genetics Genome-wide association studies (GWAS) Gene-environment interactions Microbiome and host genetics in inflammatory bowel disease Genetic epidemiology of infectious diseases like COVID-19 Development of open-source tools for multi-trait and summary-statistic analysis Recent Research Trends: His recent publications and projects emphasize integrative genetic modeling, multi-trait analysis across diverse populations, and the development of novel computational methods to handle missing data and improve SNP discovery. His work bridges statistical innovation with biological and clinical applications in complex diseases. Scientific Contributions: Development of JASS, RAISS, and MGMM software tools Leadership in large-scale consortia like EpiGenCOV Advancing methods for cross-ancestry genetic studies Advising and Collaboration: He supervises multiple PhD students and postdoctoral fellows, including Christophe Boetto, Antoine Auvergne, and Lucas Chataigner. He collaborates with major institutions such as APHP and CNRGH. His team includes research engineers and administrative staff, indicating an active and well-supported research group. Laboratories and Teams: He is a key member of the Biomaterials and Microfluidics team at the Pasteur Institute, where he contributes to interdisciplinary research involving Bayesian decision processes and genetic modeling.

• Chronic Obstructive Pulmonary Disease (COPD)
• Respiratory Medicine
• Asthma
• +۴ مورد دیگر

Per Sigvald Bakke is a Professor at the University of Bergen's Faculty of Medicine, Department of Clinical Science, with extensive expertise in respiratory medicine. His research primarily focuses on Chronic Obstructive Pulmonary Disease (COPD), asthma, and related pulmonary conditions, with significant contributions to understanding disease mechanisms, clinical phenotyping, and epidemiology. Dr. Bakke's research interests span COPD phenotyping, asthma heterogeneity, genomics of respiratory diseases, pulmonary function testing, and clinical epidemiology. His work frequently involves large-scale cohort studies and international collaborations, particularly through the U-BIOPRED consortium. His research has significantly advanced understanding of COPD progression, exacerbation risk factors, and the relationship between respiratory diseases and systemic conditions like metabolic syndrome. His publication record demonstrates consistent contributions to respiratory medicine, with recent work focusing on multi-omics approaches to disease phenotyping, genetic determinants of lung function, and clinical management of COPD. His research often bridges basic science with clinical application, addressing critical questions in respiratory disease management and patient outcomes. Dr. Bakke has been instrumental in numerous international collaborative studies including the ECLIPSE cohort, U-BIOPRED, and various genome-wide association studies examining COPD and asthma. His work has contributed to clinical guidelines and improved understanding of respiratory disease mechanisms across diverse populations.

Florian Kronenbergمشاهده پروفایل

استاد

• Lipoprotein metabolism
• Genetic epidemiology
• Lipoprotein(a)
• +۳ مورد دیگر

Florian Kronenberg is a Full Professor and Head of the Institute of Genetic Epidemiology at the Medical University of Innsbruck, Austria. He has held leadership roles since 2004 and previously directed the Department of Medical Genetics, Molecular and Clinical Pharmacology (2008–2017). His research focuses on genetic and clinical epidemiological studies, particularly on lipoprotein(a) as a major genetic risk factor for cardiovascular disease. He leads a team with the largest sample collection (40,000+ individuals) for LPA gene characterization and serves as Co-Editor of Atherosclerosis , contributing to international guidelines (K/DOQI, KDIGO, EAS). MD from University of Innsbruck Training in Medical Genetics at Gerd Utermann's lab Postdoctoral work at University of Utah His work spans over 500 publications (400+ original papers, 100+ reviews) with an H-index of 107 (Google Scholar) and 47,408+ citations. Key research areas include lipoprotein metabolism, genetic epidemiology, and the interplay of complex diseases like atherosclerosis, kidney disease, and diabetes mellitus. Recent publications emphasize Mendelian randomization, cardiovascular risk stratification, and molecular genetics of LPA variants. Scientific Awards & Honors Lifetime Achievement Award (Dr. Johannes und Hertha Tuba-Stiftung, 2021) APART Fellowship (Austrian Academy of Sciences, 1997–2000) Knoll William Harvey Prize (1999) Research awards from Austrian Stroke Foundation, Diabetes Association, and others

David Sbarraمشاهده پروفایل

استاد

• Social Relationships and Health
• Stress and Health
• Divorce and Marital Separation
• +۴ مورد دیگر

David Sbarra serves as Professor and EOS Foundation Endowed Chair in Health Psychology at the University of Arizona's Department of Psychology, where he directs the Laboratory for Social Connectedness & Health (LSCH). His research examines the biopsychosocial mechanisms linking social relationships to health outcomes, with particular focus on how divorce, marital separation, and loneliness function as risk pathways for poor health. Dr. Sbarra's academic credentials include: B.S. in Psychology from Cornell University (1996) Clinical Internship at University of Wisconsin Department of Psychiatry Ph.D. in Clinical Psychology from University of Virginia (2004) His research program centers on social relationships and health, stress physiology, and genetically-informed methodologies including twin studies, polygenic risk scores, and Mendelian Randomization. The Laboratory for Social Connectedness & Health investigates how high-quality relationships promote health resilience while relationship disruptions create vulnerability, emphasizing causal inference through advanced quantitative methods and open science practices. Recent publications reveal a pronounced shift toward establishing causal relationships in the social connection-health field, with heavy utilization of genetically-informed designs and multi-method approaches. His 2024-2025 work demonstrates particular innovation in applying Mendelian Randomization to loneliness-depression pathways, examining cardiovascular impacts of marital separation, and developing novel measures for couple therapy processes. Dr. Sbarra holds the prestigious EOS Foundation Endowed Chair in Health Psychology, recognizing his significant contributions to understanding social determinants of health. His co-authored work in the American Psychologist has helped establish social connection as a critical public health priority. While specific advising details aren't documented in available sources, his laboratory direction and course instruction (including PSY 383 Health Psychology and clinical practica) indicate active mentorship of graduate students. His research program likely operates through multiple federally funded grants supporting genetically-informed longitudinal studies. The Laboratory for Social Connectedness & Health employs diverse methodologies including daily diary assessments, physiological monitoring, fMRI, and genetically-informed designs to examine how social connection operates as a fundamental health determinant across the lifespan. Current projects focus on causal mechanisms linking relationship quality to biological aging, intervention development for attachment security, and public health applications of social connection research.

• Precision Psychiatry
• Machine Learning in Psychiatry
• Psychosis Prediction
• +۵ مورد دیگر

Nikolaos Koutsouleris serves as a Research Professor leading the Precision Psychiatry team at the Max Planck Institute of Psychiatry in Munich, Germany. He directs the KOUTSOULERIS LAB, which focuses on developing advanced machine learning methodologies for clinical psychiatry applications. His work bridges computational neuroscience, clinical psychology, and precision medicine approaches to transform psychiatric diagnosis and treatment. Dr. Koutsouleris's research program centers on precision psychiatry, with particular emphasis on multimodal data integration for predicting psychiatric outcomes. His laboratory develops sophisticated machine learning workflows that combine neuroimaging, clinical assessments, genetic information, and biomarker data to create personalized prediction models. This approach enables more accurate identification of individuals at risk for psychosis and other psychiatric disorders, facilitating earlier intervention and tailored treatment strategies. Analysis of Dr. Koutsouleris's publication record reveals a consistent trajectory toward increasingly sophisticated applications of artificial intelligence in psychiatry. His recent work demonstrates a shift from single-modality prediction to complex multimodal frameworks that capture the heterogeneous nature of psychiatric conditions. Key themes include addressing methodological challenges in clinical prediction generalizability, exploring neurobiological underpinnings of mental illness through advanced analytics, and translating computational findings into clinically actionable tools. As leader of the KOUTSOULERIS LAB at the Max Planck Institute of Psychiatry, Dr. Koutsouleris oversees a multidisciplinary research environment that brings together computational scientists, clinicians, neuroscientists, and data analysts. His team collaborates extensively with international consortia to validate prediction models across diverse populations, ensuring robustness and clinical applicability of their findings. The laboratory serves as a nexus for innovation in computational psychiatry, driving methodological advances while maintaining strong connections to clinical practice.

• Thyroid dysfunction
• Diabetes
• Pregnancy complications and cardiovascular risk
• +۱ مورد دیگر

Bjørn Olav Åsvold, MD, PhD, is a Professor of Medicine (Epidemiology) and Center leader at the HUNT Centre for Molecular and Clinical Epidemiology (HUNT MCE), Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU). He also serves as a Consultant at the Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital. His research spans epidemiology, genetics, and clinical medicine. MD, Norwegian University of Science and Technology, 2001 PhD, Norwegian University of Science and Technology, 2008 Specialist in internal medicine, 2014 Specialist in endocrinology, 2015 Åsvold's research focuses on thyroid dysfunction and diabetes , investigating their interplay with cardiometabolic diseases and pregnancy complications . He utilizes Mendelian randomization studies to explore causal relationships between genetic factors and health outcomes, including sleep traits , autoimmune thyroid disease , and kidney function . His work also addresses global health issues like obesity in Nepal and diabetic complications in Norway. Recent publications highlight his contributions to understanding hip fracture risk prediction , cardiovascular implications of sleep patterns , and genetic determinants of trace elements . Åsvold's collaborations span multiple international institutions, including the HUNT Study and HUNT MCE in Norway.

Guanghao Qiمشاهده پروفایل

استادیار

• Statistical Genetics
• Genomics
• Single-cell RNA Sequencing Analysis
• +۳ مورد دیگر

Guanghao Qi is an Assistant Professor in the Department of Biostatistics at the University of Washington. His research focuses on developing statistical and machine learning methods for multi-omics approaches in genetic studies, particularly integrating single-cell RNA-seq, GWAS, and functional genomic data. Key areas include single-cell eQTL analysis, Mendelian randomization, and multi-trait genetic association analyses. Education: PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health (2020), BS in Mathematics from Fudan University (2015). Research interests emphasize high-dimensional data analysis, allele-specific expression in single cells, and causal inference using genetic variants. Notable achievements include a 2025 NIH K01 award for developing methods to integrate single-cell eQTL and GWAS data, and the development of the TWiST method for single-cell transcriptome-wide association studies. Recent work highlights advancements in computational tools like SURGE for context-specific genetic regulation analysis, and evaluations of Mendelian randomization methods in studies of type 2 diabetes and cardiovascular disease. His work often bridges computational biology and statistical theory to address challenges in interpreting large-scale genomic datasets. Awards: NIH K01 Award (2025) Key Contributions: TWiST method (2025), SURGE framework (2024), HIPO power optimization (2018) Labs/Teams: Active collaborations in genomic epidemiology and statistical genetics, with a focus on single-cell multi-omics integration and causal inference methodologies.

• Psychiatric Genetics
• Substance Use Disorders
• Gene-Environment Interaction
• +۵ مورد دیگر

Bao-Zhu Yang is a Researcher at Yale School of Medicine , specializing in the Department of Psychiatry . With a PhD from University at Albany (2001), his work focuses on genetic mechanisms underlying psychiatric disorders. Positions: Research Scientist in Psychiatry Labs: Gelernter Lab, Division of Human Genetics His research explores gene-environment interactions , admixture mapping , and comorbid substance use-depression using linkage/association methods. Supported by NIH K01 funding, he investigates genetic bases for conditions including childhood depression , alcoholism , and PTSD . Recent publications highlight: Microbiome studies in methamphetamine use disorder (2023-2025) Genetic polymorphism analyses in NGF and GABAergic pathways (2020-2024) Network approaches to nicotine-alcohol comorbidity (2019) Epigenetic research on child maltreatment effects (2020) Scientific Recognition: Young Investigator Award (2011) from NARSAD Brain and Behavior Research Foundation Active grant support includes NIH K01 career development award for gene-mapping in comorbid disorders. Collaborates with leading researchers including Joel Gelernter and Hongyu Zhao across 30+ joint publications. His work spans 15+ years with recent focus on integrative -omics approaches to addiction psychiatry. Based at 300 George St, New Haven, CT , Yang's laboratory work involves genetic epidemiology , transcriptomic integration , and neurogenetic mapping of substance use disorders.

Nikolaos Koutsoulerisمشاهده پروفایل

استاد

• Predictive Psychiatry
• Machine Learning in Psychiatry
• Psychosis Prediction
• +۵ مورد دیگر

Professor Nikolaos Koutsouleris serves as a Research Group Leader for the Max Planck Fellow Group for Precision Psychiatry at the Max Planck Institute of Psychiatry and holds a position as Senior Physician in the Department of Psychiatry and Psychotherapy at Ludwig Maximilian University (LMU) Munich. His work bridges clinical practice with advanced computational approaches to transform psychiatric diagnostics and treatment. Dr. Koutsouleris specializes in predictive psychiatry, focusing on extracting meaningful patterns from neurobiological, neurocognitive, and clinical data to improve early recognition of functional psychoses. His research employs structural MRI, neuropsychological testing, and clinical evaluations within cross-sectional and longitudinal studies, utilizing advanced machine learning methods to identify and validate biomarkers for single-subject prediction of psychosis. As head of the Early Psychosis Studies and the Workgroup for Neurodiagnostic Applications, he drives initiatives to implement predictive models across healthcare settings for personalized management of high-risk individuals. His publication record reveals a consistent focus on machine learning applications in psychiatry, with recent work addressing critical issues like the generalizability of clinical prediction models, brain aging patterns in large populations, and multimodal approaches to psychosis prediction. His research spans from fundamental methodological challenges to clinical applications, demonstrating how AI and machine learning are transforming psychiatric practice toward precision medicine. Dr. Koutsouleris actively trains pre- and post-doctoral investigators in advanced data analysis techniques, emphasizing comprehensive analysis of complex, high-dimensional datasets using multivariate methods. His leadership in the PRONIA Consortium and other collaborative efforts highlights his commitment to advancing the field through international cooperation and rigorous scientific inquiry.

Kristine Beate Walhovdمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuropsychology
• Brain Aging
• +۵ مورد دیگر

Kristine Beate Walhovd is a Professor at the Department of Psychology , University of Oslo, and co-leader of the Center for Lifespan Changes in Brain and Cognition (LCBC) . She is affiliated with the UiO:Life Science initiative and has led major projects like Lifebrain (€2.5M) and Neurocognitive Plasticity (ERC Starting Grant, €1.5M). Current roles: Professor (since 2016), Co-leader of LCBC Key affiliations: University of Oslo, Lifebrain Consortium, UiO:Life Science Her research focuses on lifespan brain and cognitive changes , examining both positive/negative developmental trajectories from age 4 to 90. She studies interactions between biomedical risks (e.g., Alzheimer's, fetal drug exposure) and cognitive outcomes, employing MRI , DTI , and ERP methodologies. Recent publications highlight work on Alzheimer's biomarkers , sleep-brain interactions , memory consolidation , and fetal brain influences . Her 2025 papers in Scientific Reports and Neurobiology of Aging examine hippocampal stability and brain network segregation. Awards include: 2015 University of Oslo Research Prize (shared with Anders Fjell) 2011 Member, Norwegian Academy of Sciences and Letters 2006 His Majesty the King's Gold Medal for best doctoral thesis She supervises doctoral candidates and teaches cognitive neuroscience , experimental methods , and thesis writing .