جست‌وجوی استاد و پژوهشگر

Yi-Hsun Hsiehمشاهده پروفایل

پژوهشگر

• Power Electronics
• Resonant Converter Design
• Solid-State Transformers
• +۵ مورد دیگر

Yi-Hsun Hsieh is a Researcher at the Center for Power Electronics Systems (CPES) at Virginia Tech. His work focuses on advanced power electronics systems, including resonant converters, solid-state transformers, and modular multilevel converters. He specializes in high-frequency transformer design, power quality optimization, and high-power conversion technologies. His research addresses challenges in energy distribution, renewable energy integration, and high-efficiency power conversion. Key research areas include resonant converter modeling, insulation techniques for high-voltage applications, and control strategies for modular systems. Hsieh contributes to the development of efficient power electronics solutions for industries such as renewable energy systems, electric vehicles, and smart grids. His publications emphasize rigorous analysis of converter dynamics, small-signal modeling, and practical implementation of high-density power electronics. Hsieh collaborates with CPES's industry consortium to advance technologies like Global Intergrid and Power Management Modeling.

Kathleen Palm Reedمشاهده پروفایل

دانشیار

• Clinical Psychology
• Trauma Studies
• Substance Use Disorders
• +۴ مورد دیگر

Kathleen Palm Reed is an Associate Professor in the Psychology Department at Clark University. She holds a Ph.D. in Clinical Psychology from the University of Nevada, Reno (2004), and completed postdoctoral training at Brown University's Warren Alpert Medical School. Her research focuses on trauma, substance use disorders, and violence prevention, emphasizing Acceptance and Commitment Therapy (ACT) and emotion regulation. She has authored numerous articles on topics such as PTSD, intimate partner violence, and adolescent substance use. Education: Ph.D. in Clinical Psychology, University of Nevada, Reno, 2004 M.A. in Clinical Psychology, Minnesota State University, 1998 B.S. in Psychology, James Madison University, 1996 Research Interests: Dr. Palm Reed examines trauma recovery, substance use interventions, and prevention strategies for violence. Her work integrates ACT principles to address emotion regulation deficits in high-risk populations. Recent studies explore the impact of socioeconomic stress on trauma survivors and the role of stigma in treatment-seeking behaviors. Grants & Awards: Department of Justice Grant (2013–2016): 'Building Coalitions to Foster Change on College Campuses' focused on violence prevention programs. Grants & Advising: Her grants support multilevel violence prevention initiatives. She collaborates with colleagues on bystander intervention programs and studies the efficacy of ACT-based therapies. Her work bridges clinical practice and community outreach, emphasizing evidence-based strategies for marginalized populations. Labs/Teams: Engaged in interdisciplinary teams addressing trauma, substance use, and violence at Clark University and affiliated institutions. Collaborations include the Warren Alpert Medical School and the Association for Behavioral and Cognitive Therapies.

Jaehoon Leeمشاهده پروفایل

دانشیار

• Multilevel modeling
• Latent variable modeling
• Markov Chain Monte Carlo simulation
• +۴ مورد دیگر

Jaehoon Lee serves as an Associate Professor in the Educational Psychology, Leadership and Counseling department at Texas Tech University's College of Education, specializing in the Research, Evaluation, Measurement, and Statistics (REMS) concentration. He maintains cross-institutional roles as a faculty associate at Texas Tech University Health Science Center and adjunct associate professor at Baylor College of Medicine, demonstrating strong interdisciplinary engagement across education and medical research domains. His academic credentials include: B.A. in Industrial and Organizational Psychology from Sungkyunkwan University, South Korea (2001) M.S. in Experimental Psychology from Western Illinois University (2003) Ph.D. in Quantitative Psychology from the University of Kansas (2009) Dr. Lee's methodological expertise centers on advanced statistical techniques including multilevel modeling, latent variable modeling, Markov Chain Monte Carlo simulation, and propensity score analysis. His research specifically targets the evaluation of mixture models and Bayesian structural equation models using complex, less favorable datasets, addressing critical gaps in quantitative methodology for real-world applications. Analysis of his recent publications reveals a pronounced interdisciplinary trajectory spanning health sciences, education, and psychology. His work demonstrates consistent application of sophisticated statistical frameworks to diverse problems including telehealth implementation, cancer treatment efficacy, educational assessment design, and health intervention evaluation across global contexts from Malaysia to rural Texas. This pattern underscores his ability to bridge methodological rigor with practical domain challenges.

• Power Electronics
• Electrical Engineering
• Model Predictive Control (MPC)
• +۴ مورد دیگر

José Rodríguez is a Professor in the Department of Computer Science at CINVESTAV-IPN in Mexico City, Mexico. His research focuses on power electronics, model predictive control (MPC), renewable energy systems, and electric drives. He has collaborated extensively with researchers worldwide, contributing to advancements in energy transition technologies and grid integration strategies. His work emphasizes improving efficiency, reducing computational complexity, and enhancing reliability in power conversion systems. Key areas of expertise include fault diagnosis in rotating machinery, optimization of photovoltaic systems, and the development of advanced control algorithms for electric drives and converters. Rodríguez has authored over 200 peer-reviewed publications, with a strong presence in top-tier journals like IEEE Transactions on Industrial Electronics and IEEE Access . His recent work explores hybrid models (e.g., CWT-LeNet-5-LSTM) for fault detection, low-cost sensor integration, and data-driven predictive control techniques. He also investigates multilevel inverter topologies and grid-connected converter systems, addressing challenges like transient DC offset mitigation and harmonic distortion reduction. Rodríguez’s contributions span both theoretical and applied research, bridging the gap between control systems and practical energy solutions. His interdisciplinary approach combines machine learning, optimization algorithms, and traditional engineering principles to tackle modern energy challenges.

Karen Nielsenمشاهده پروفایل

استادیار

• Biostatistics
• Multilevel modeling
• Analysis of Physiological Data

Dr. Karen Nielsen is an Assistant Professor of Biostatistics in the Department of Population Health Sciences at Georgia State University's School of Public Health. She holds a Ph.D. (2017) and M.S. (2014) from the University of Michigan and a B.A. (2011) from the University of Oklahoma. Her research focuses on developing and applying statistical techniques for modern data challenges, including multilevel modeling and analysis of high-frequency physiological sensor data. She collaborates across disciplines such as psychology, gerontology, and public health.

Robert Bishopمشاهده پروفایل

استاد

• History and Philosophy of Science
• Philosophy of Physics
• Philosophy of Social Sciences
• +۴ مورد دیگر

Robert Bishop, Ph.D., is a Professor of Physics and Philosophy and the John and Madeleine McIntyre Chair of Philosophy and History of Science at Wheaton College since 2007. He holds degrees from the University of Texas at Austin: B.S. in Physics (1984), M.A. in Physics (1986), and Ph.D. in Philosophy (1999). His research focuses on the history and philosophy of science, philosophy of physics, and the philosophical implications of chaos and complex systems. He serves as area editor for the Internet Encyclopedia of Philosophy and critiques assumptions in science and theology. Education : B.S., Physics, University of Texas at Austin (1984) M.A., Physics, University of Texas at Austin (1986) Ph.D., Philosophy, University of Texas at Austin (1999) His research interests include determinism, irreversibility in statistical mechanics, nonlinear dynamics, and the intersection of science with free will, mind, and theology. Recent work explores cultural/ethical ideals in social sciences and the limitations of methodological naturalism. Publications span philosophy of science, physics, and interdisciplinary topics, emphasizing foundational questions in physical and social sciences. Notable works address contextual emergence theory, teleology, and critiques of evidentialist atheism. Awards : Fellow of the American Scientific Affiliation Bishop teaches courses on thermodynamics, particle physics, philosophy of science, and theories of origins. He actively engages in academic service, including editorial roles and interdisciplinary dialogue.

Bryan P. Actonمشاهده پروفایل

استادیار

• Leadership emergence
• Leadership identity
• Agent-based modeling & simulation
• +۳ مورد دیگر

Bryan P. Acton is an Assistant Professor of Organizational Behavior and Leadership at Binghamton University's School of Management. His research focuses on leadership dynamics in collectives, leveraging cutting-edge methodologies like agent-based modeling to explore how leadership emerges and evolves. He holds a strong interest in leadership identity, perception measurement, and the intersection of social processes with organizational behavior. Acton's teaching interests include business statistics, teams and leadership, and R programming for modeling. His work emphasizes dynamic processes and challenges traditional static views of leadership roles. His research has explored topics such as leader identity fluidity, memory systems in leadership measurement, and team composition impacts on cohesion. He advocates for process-oriented frameworks that integrate multilevel dynamics and computational modeling. No scientific awards or grants are explicitly listed in the provided materials. His CV indicates ongoing research in leadership emergence and collective dynamics but provides no details about advising students or lab affiliations.

Andrew Heissمشاهده پروفایل

استادیار

• Nonprofit Studies
• International Studies
• Authoritarian Politics
• +۳ مورد دیگر

Andrew Heiss is an Assistant Professor in the Andrew Young School of Policy Studies at Georgia State University . He holds a PhD in Public Policy from Duke University, an MPA in Nonprofit Management from Brigham Young University, and an MA in Middle East Studies from the American University in Cairo. Education: PhD in Public Policy, Sanford School of Public Policy, Duke University MPA in Nonprofit Management, Brigham Young University MA in Middle East Studies, American University in Cairo Research Interests: Dr. Heiss focuses on the interplay between nonprofit organizations and authoritarian governments, particularly examining how NGOs navigate restrictive legal environments. His work emphasizes NGO survival strategies under repressive regimes, the impact of anti-NGO laws, and the effectiveness of human rights advocacy in contentious political climates. He also explores statistical methodologies applicable to policy research and cross-sectoral institutional trust dynamics. Publications Trends: His recent work highlights themes of civil society repression , transnational advocacy networks , and statistical modeling innovations . He analyzes how NGOs adapt to shrinking civic spaces and the implications of global health emergencies on democratic governance. Awards: 2016–2018 Emerging Scholar Dissertation Award from ISTR Grants & Advising: While no formal advisees are listed, his research has been supported by grants focusing on NGO resilience and policy impact analysis. He has collaborated on projects examining pandemic governance and urban transit equity. Labs/Teams: No specific lab affiliations are mentioned, but his work engages with global civil society networks and interdisciplinary policy research teams.

Emmeke Aartsمشاهده پروفایل

دانشیار

• Data Science
• Longitudinal Data Analysis
• Machine Learning
• +۳ مورد دیگر

Dr. Emmeke Aarts is an Associate Professor in Statistics at Utrecht University's Department of Methodology and Statistics, within the Faculty of Social and Behavioural Sciences. She serves as Director of Education for the department and coordinates several academic programs including the Research Master Methodology and Statistics. Her research focuses on developing novel statistical methods for intensive longitudinal data, particularly multilevel hidden Markov models and real-time prediction algorithms in healthcare. Key areas include personalized latent dynamics and cardiovascular disease monitoring. She has received a 2024 fellowship for her work on depression dynamics in emerging adults. A资深的统计学家 and educator, she supervises PhD students and contributes to interdisciplinary collaborations with medical institutions like UMC Utrecht. Education: Research Master in Methodology and Statistics (cum laude, Utrecht University) and a PhD in interdisciplinary statistics and neuroscience (VU University Amsterdam). Postdoctoral roles included positions at the Max Planck Institute and TNO. Research Themes: Applied Data Science, Multilevel Analysis, Machine Learning, and Hidden Markov Models. Her work bridges methodological innovation with practical applications in mental health and cardiology. Current projects include Health-Holland grant-funded collaborations on heart failure prediction and real-time deterioration monitoring. Teaching: Coordinates courses such as 'Introduction to Multilevel Modelling' and leads summer schools on structural equation modeling. Supervises over 10 graduate students and provides statistical consultation for biomedical and social science projects. Grants & Awards: 2024 Fellowship for personalized depression dynamics research; Health-Holland grants for heart failure machine learning projects. Extensive record of interdisciplinary funding and academic service roles in education committees. Labs/Teams: Active in the Utrecht Platform for Applied Data Science and collaborates with UMC Utrecht Cardiology Department. Leads methodological development for multilevel HMM applications in behavioral and biomedical data.

• Health Economics
• Public Health
• Econometric Modelling
• +۳ مورد دیگر

Dr. Julie Abimanyi-Ochom is a Senior Lecturer at Deakin University's School of Health and Social Development, part of the Faculty of Health and the Institute for Health Transformation. She holds a PhD in Health Economics from Monash University, an MSc in Development and Resource Economics from the Norwegian University of Life Sciences, and a BSc in Agricultural Economics from Makerere University. Her research focuses on health economics, particularly in low- and middle-income countries (LMICs), with expertise in econometric modelling and burden of disease analysis. Key areas include chronic disease management (e.g., osteoporosis, Parkinson’s Disease, HIV/AIDS), youth alcohol prevention, endometriosis, and maternal and child health equity. She has led or contributed to over $2 million in grants, including projects on diabetes and dementia links, youth alcohol prevention, and osteoporosis costing studies. Education: PhD in Health Economics, Monash University (Australia) MSc in Development and Resource Economics, Norwegian University of Life Sciences BSc in Agricultural Economics, Makerere University (Uganda) Research Interests: Health economics in LMICs Chronic disease burden and prevention Health service utilisation equity Econometric analysis of health systems Her recent articles analyze topics such as childhood pneumonia costs in Bangladesh, antenatal care inequities in Sub-Saharan Africa, and the economic impact of Huntington’s disease. She has been awarded grants for projects like the Communities That Care initiative and has received accolades including the 2009 Australian Health Economics Society Best Paper Award. Dr. Abimanyi-Ochom supervises doctoral candidates on maternal health, refugee care models, and disability equity. She also contributes to editorial boards (e.g., Frontiers in Public Health) and professional societies like the Australian Health Economics Society. Grants & Awards: $475,498 MRFF Grant for Endometriosis Research (2020–2026) $97,000 Osteoporosis Australia Grant (2024) Brown University Advanced Research Institute Scholar Award (2013) Teaching & Supervision: Teaches Health Economics and Biostatistics at Deakin Supervises 4 doctoral candidates on topics like refugee maternal care and child health outcomes

Emorie D Beckمشاهده پروفایل

استادیار

• Personality Psychology
• Social Psychology
• Psychometrics
• +۴ مورد دیگر

Dr. Emorie D Beck is an Assistant Professor in the Psychology Department at the University of California, Davis. Her work focuses on redefining personality psychology through idiographic methods, exploring how individual-level data can transform our understanding of personality measurement and prediction. She holds a PhD from Washington University in St. Louis (2020) and a BA from Brown University (2016). Her postdoctoral training was at Northwestern University's Feinberg School of Medicine. Dr. Beck's research employs cutting-edge techniques including machine learning, network analysis, and longitudinal panel data to study personality's role in predicting long-term outcomes like dementia diagnosis. She emphasizes personalized approaches, demonstrating how individual-specific prediction models outperform traditional methods. Current projects investigate cross-continental panel data to uncover how personality traits interact with neuropathology and well-being over time. Teaching includes graduate-level courses on data visualization (PSC 203B) and undergraduate courses on personality theory (PSC 162). She directs the Beck Personality Lab, currently recruiting undergraduate researchers. Awards include the 2025 Early Achievement Award from the European Association of Personality Psychology and 2023 Walter Klopfer Award for Best Paper. Methodological innovations span experience sampling, passive sensing, and hybrid statistical approaches combining machine learning with structural equation modeling. Her work bridges theoretical foundations of personality with applied questions about health outcomes and individual variability.

Siwei Liuمشاهده پروفایل

دانشیار

• Research Methodology
• Developmental Psychology
• Health Psychology
• +۴ مورد دیگر

Dr. Siwei Liu is an Associate Professor in the Department of Human Development & Family Studies at the University of California, Davis. Their research focuses on advanced statistical methods for analyzing longitudinal data in developmental and health psychology, with an emphasis on biobehavioral synchrony in close relationships and health disparities. They lead a lab investigating multi-layer contextual factors (e.g., environment, family characteristics) affecting health behaviors, prioritizing diversity in both research subjects and student recruitment. Research Interests : Longitudinal data methodologies: multilevel modeling, time series analysis, functional data analysis Biobehavioral synchrony in parent-child and couples relationships Health disparities, environmental justice, and stress physiology Intensive longitudinal methods in health research Key Projects : GROWell randomized controlled trial for dietary interventions in prenatal/postpartum populations Multimodal assessment of biobehavioral synchrony in autism spectrum disorder Analysis of family risk dynamics and parenting stress through cortisol contagion Labs/Teams : Directs a lab prioritizing underrepresented students, focusing on innovative methods for studying emotions, well-being, and family systems. Collaborates on NIH-funded projects involving wearable devices and ecological momentary assessments.

Siri Hausland Folstadمشاهده پروفایل

پژوهشگر ارشد

• Mental Health
• Public Health
• Youth Health
• +۵ مورد دیگر

Siri Hausland Folstad is a Research Fellow and PhD student at the University of Oslo’s Department of Psychology, affiliated with the PROMENTA research center. Her work focuses on promoting mental health and wellbeing in children and adolescents, particularly through interdisciplinary approaches to public health and life skills education. She is funded by the DAM Foundation for her project evaluating the effects of curricular changes on youth mental health. Education : Master of Research in Psychology (2018–2019), University of Manchester, UK Bachelor of Science in Psychology (2014–2017), University of Manchester, UK Research Interests : Mental health promotion, youth health, prevention of mental illnesses, statistical methods (multilevel modeling, structural equation modeling), and open science practices. Her work integrates quantitative and qualitative approaches to address systemic gaps in healthcare and education. Professional Background : Research Assistant, Norwegian Social Research (NOVA), OsloMet (2021) Research Assistant, Department of Media and Communication, UiO (2020) Mental Health Care Therapist, Døgnseksjonen Sikta, Asker DPS (2019–2021) Labs/Teams : PROMENTA, Youth Mental Health Unit (UK), and the Department of Psychology’s health promotion research groups.

• Employee Proactive Behavior
• Leadership Styles
• Job Crafting
• +۳ مورد دیگر

Zhijun Chen is a Professor and Head of the Department of Human Resources Management at the College of Business, Shanghai University of Finance and Economics (SUFE). He also serves as the Academic Director of SUFE's MBA program and holds an honorary research fellow position at the UWA Business School, University of Western Australia. His research focuses on employee proactive behavior, leadership styles, job crafting, and socialmateriality. He contributes to editorial roles for journals like Human Relations and Asian Pacific Journal of Management . Chen teaches organizational behavior, strategic HR management, and social psychology. His work bridges leadership dynamics, employee behavior, and organizational contexts, with publications in high-impact journals such as Journal of Applied Psychology and Organization Science . His research emphasizes multilevel analyses of proactive behavior and leadership’s role in shaping workplace outcomes. With 12 publications cited over 400 times (Scopus), Chen’s scholarship addresses topics like authoritarian leadership’s impact on proactivity, peer influence in teams, and ambidextrous leadership’s role in newcomer integration. He has supervised 3 students and actively engages in international research collaborations.

Farzad Farajizadehمشاهده پروفایل

پژوهشگر ارشد

• Power Electronic Converters
• Wireless Power Transfer Systems
• Renewable Energy Conversion
• +۴ مورد دیگر

Farzad Farajizadeh is a Research Fellow in Power Engineering at the School of Engineering, The University of Western Australia (UWA). He holds a PhD in Electrical Engineering from Queensland University of Technology (2021), specializing in wireless power transfer systems for dynamic chargers. Previously, he served as a post-doctoral researcher at the University of Queensland, focusing on electromagnetic interference modeling in power electronic systems. His research interests encompass power electronic converters, renewable energy systems, wireless power transfer (WPT), and FACTS technologies. He leads projects on stackable multi-level power electronic modules and has contributed to advancements in dynamic WPT for applications like electric vehicle charging. His work aligns with UN Sustainable Development Goals, particularly in sustainable energy and innovation. Farajizadeh has authored over 20 peer-reviewed publications, including studies on grid-side current oscillations, EMI mitigation in IPT systems, and control strategies for cascaded multilevel inverters. He is a co-investigator on the ARC-funded Renewable Microgrid Pilot for Gravitational Wave Facilities project, addressing energy resilience in remote infrastructure. His research bridges theoretical analysis and experimental validation, with applications in smart grids, renewable integration, and high-efficiency power systems. Key contributions include novel converter designs for dynamic WPT and harmonic mitigation techniques in parallel grid-tied inverters.