Denise Reyes

ORCID: 0000-0003-0455-8821
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About
Contact & Profiles
Research Areas
  • Team Dynamics and Performance
  • Human Resource Development and Performance Evaluation
  • Job Satisfaction and Organizational Behavior
  • Gender Diversity and Inequality
  • Dementia and Cognitive Impairment Research
  • Organizational Learning and Leadership
  • Knowledge Management and Sharing
  • Social and Intergroup Psychology
  • Functional Brain Connectivity Studies
  • Alzheimer's disease research and treatments
  • Health, Environment, Cognitive Aging
  • Software Engineering Techniques and Practices
  • Human Resource and Talent Management
  • Organizational Leadership and Management Strategies
  • Death Anxiety and Social Exclusion
  • Global Health Workforce Issues
  • Disaster Response and Management
  • Psychological Well-being and Life Satisfaction
  • Psychological and Educational Research Studies
  • Systems Engineering Methodologies and Applications
  • Emotional Intelligence and Performance
  • Racial and Ethnic Identity Research
  • Mindfulness and Compassion Interventions
  • Fashion and Cultural Textiles
  • Single-cell and spatial transcriptomics

University of Houston
2021-2024

Collaborative Research Group
2024

Hartnell College
2023

Alzheimer’s Disease Neuroimaging Initiative
2023

Rice University
2015-2021

Asian Development Bank
2018

American College of Financial Services
2018

Houston Methodist
2018

American University
2018

American College Testing
2018

Heejong Kim Batuhan K. Karaman Qingyu Zhao Alan Q. Wang Mert R. Sabuncu and 95 more Michael D. Weiner Paul Aisen Ronald Petersen Clifford R. Jack William Jagust Susan Landau Mónica Rivera Mindt Ozioma C. Okonkwo Leslie M. Shaw Edward B. Lee Arthur W. Toga Laurel Beckett Danielle Harvey Robert C. Green Andrew J. Saykin Kwangsik Nho Richard J. Perrin Duygu Tosun Perminder S. Sachdev Robert C. Green Erin Drake Tom Montine Cat Conti Michael W. Weiner Rachel L. Nosheny Diana Truran Sacrey Juliet Fockler Melanie J. Miller Winnie Kwang Chengshi Jin Adam Diaz Miriam T. Ashford Derek Flenniken Adrienne Kormos Ronald Petersen Paul Aisen Michael S. Rafii Rema Raman Gustavo Jimenez‐Maggiora Michael Donohue Jennifer Salazar Andrea Fidell Virginia Boatwright Justin Robison Caileigh Zimmerman Yuliana Cabrera Sarah Walter Taylor Clanton Elizabeth Shaffer Caitlin Webb Lindsey Hergesheimer Stephanie Smith Sheila Ogwang Olusegun Adegoke Payam Mahboubi Jeremy Pizzola Cecily Jenkins Laurel Beckett Danielle Harvey Michael Donohue Naomi Saito Adam Diaz Kedir Adem Hussen Ozioma C. Okonkwo Mónica Rivera Mindt Hannatu Amaza Mai Seng Thao Shaniya Parkins Omobolanle Ayo Matt Glittenberg Isabella Hoang Kaori Kubo Germano Joe Strong Trinity Weisensel Fabiola Magana Lisa S. Thomas Vanessa Guzmán Adeyinka Ajayi Joseph Di Benedetto Sandra Gómez Talavera Clifford R. Jack Joel P. Felmlee Nick C. Fox Paul Thompson Charles DeCarli Arvin Forghanian-Arani Bret Borowski Calvin Reyes Caitie Hedberg Chad Ward Christopher G. Schwarz Denise Reyes Jeff Gunter John Moore-Weiss Kejal Kantarci

Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on significant changes. In this work, we present a machine learning–based method that automatically ignores irrelevant changes extracts the time-varying signal of interest. Our method, called Learning-based Inference imAge Changes (LILAC), performs pairwise...

10.1073/pnas.2411492122 article EN cc-by Proceedings of the National Academy of Sciences 2025-02-20
André Altmann Leon M. Aksman Neil P. Oxtoby Alexandra L. Young Michael W. Weiner and 95 more Paul Aisen Ronald Petersen Michael Weiner Paul Aisen Ronald Petersen Clifford R. Jack William Jagust Susan Landau Mónica Rivera Mindt Ozioma C. Okonkwo Leslie M. Shaw Edward B. Lee Arthur W Toga Laurel Beckett Danielle Harvey Robert C Green Andrew J. Saykin Kwangsik Nho Richard J. Perrin Duygu Tosun Perminder S. Sachdev Robert C Green Tom Montine Cat Conti Michael W. Weiner Rachel L. Nosheny Juliet Fockler Melanie J. Miller Catherine Conti Winnie Kwang Chengshi Jin Adam Diaz Miriam T. Ashford Derek Flenniken Adrienne Kormos Ronald Petersen Paul Aisen Michael Rafii Rema Raman Gustavo Jimenez‐Maggiora Michael Donohue Jennifer Salazar Andrea Fidell Virginia Boatwright Justin Robison Caileigh Zimmerman Yuliana Cabrera Sarah Walter Taylor Clanton Elizabeth Shaffer Caitlin Webb Lindsey Hergesheimer Stephanie Smith Sheila Ogwang Olusegun Adegoke Payam Mahboubi Jeremy Pizzola Cecily Jenkins Laurel Beckett Danielle Harvey Michael Donohue Naomi Saito Adam Diaz Kedir Adem Hussen Ozioma C. Okonkwo Mónica Rivera Mindt Hannatu Amaza Mai Seng Thao Shaniya Parkins Omobolanle Ayo Matt Glittenberg Isabella Hoang Kaori Kubo Germano Joe Strong Trinity Weisensel Fabiola Magana Lisa Thomas Vanessa Guzmán Adeyinka Ajayi Joseph Di Benedetto Sandra Gómez Talavera Clifford R. Jack Joel P. Felmlee Nick C. Fox Paul Thompson Charles DeCarli Arvin Forghanian-Arani Bret Borowski Calvin Reyes Caitie Hedberg Chad Ward Christopher G. Schwarz Denise Reyes Jeff Gunter John Moore-Weiss

Abstract Alzheimer’s disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression biomarkers has condensed into ATN framework, each can be either positive (+) or negative (−). Over past decades, genome-wide association studies implicated ∼90 different loci involved with development late-onset disease. Here, we investigate whether genetic risk for contributes equally to stages...

10.1093/brain/awae176 article EN cc-by Brain 2024-05-30

10.1016/j.orgdyn.2021.100846 article EN publisher-specific-oa Organizational Dynamics 2021-01-01

To better understand the effects of demographic diversity on teams, we conducted a meta-analytic investigation relationship between team and processes. Drawing from categorization-elaboration model, hypothesized that elicits opposing performance via information elaboration social categorization We also explored several team-level contextual moderators these relationships. In our meta-analysis 406 38,304 found is related to increased processes, but did not find support for elaboration....

10.1177/20413866241245312 article EN Organizational Psychology Review 2024-04-16

10.1016/j.orgdyn.2020.100785 article EN publisher-specific-oa Organizational Dynamics 2020-08-22

Most organizations invest in leadership training and development initiatives, but which programs are worth the money is not always clear. To help leaders policymakers make informed decisions about their investments, we review empirical research from organizational sciences provide evidence-based guidance regarding appropriate design delivery of such interventions. Leadership distinct initiatives based on different needs targeted at albeit interrelated goals. We describe important...

10.1177/237946152100700105 article EN Behavioral Science & Policy 2021-04-01

Background Certain leadership behaviours are particularly helpful for healthcare teams remain effective through crisis situations, such as the Covid-19 pandemic. This paper summarizes evidence-based insights based on their importance and prevalence in literature to provide recommendations that apply medical team leaders broadly construed. We recommend adopt these conditions of intense difficulty, uncertainty, well physical psychological peril. Results draw from research workplace resilience,...

10.1136/leader-2020-000349 article EN BMJ Leader 2021-06-04

Most organizations invest in leadership training and development initiatives, but which programs are worth the money is not always clear. To help leaders policymakers make informed decisions about their investments, we review empirical research from organizational sciences provide evidence-based guidance regarding appropriate design delivery of such interventions. Leadership distinct initiatives based on different needs targeted at albeit interrelated goals. We describe important...

10.1353/bsp.2021.0001 article EN Behavioral Science & Policy 2021-01-01

Abstract An understanding of the demands contemporary world work may help guide policy‐ and decision‐making processes. However, despite importance this understanding, few studies have attempted to examine universe available occupations determine most in‐demand knowledge, skills, abilities, other worker characteristics (KSAOs) as well relative these KSAOs across occupations. This study addresses first concern by calculating weighted averages that rely on Occupational Information Network's...

10.1002/cdq.12367 article EN public-domain The Career Development Quarterly 2024-10-17
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