جستجوی استاد راهنمای دانشگاهی

Mark S. Handcockمشاهده پروفایل

استاد

• Statistics
• Social Network Analysis
• Survey Sampling
• +۳ مورد دیگر

Mark S. Handcock is a Distinguished Professor in the Department of Statistics and Data Science at the University of California, Los Angeles (UCLA), where he leads research at the intersection of statistical methodology and applied problems in social sciences, epidemiology, and environmental science. His work bridges theoretical statistics with real-world challenges through innovative methodological development. His primary research interests encompass statistical models for social networks, network inference, methodology for hard-to-reach population surveys, spatial processes, demography, and environmetrics. Handcock has pioneered advances in exponential-family random graph models (ERGMs) and developed foundational R packages like ergm and tergm within the statnet suite, enabling sophisticated network analysis across disciplines. Analysis of his recent publications (2023-2025) reveals three dominant research thrusts: (1) Antarctic sea ice modeling using Bayesian reconstruction and temporal variability analysis, (2) epidemiological modeling of infectious disease transmission dynamics (particularly COVID-19), and (3) methodological innovations in network inference and causal analysis over stochastic networks. His work consistently integrates advanced computational statistics with domain-specific applications in climate science, public health, and social systems.

Louis Hickmanمشاهده پروفایل

استادیار

• Industrial-Organizational Psychology
• Algorithmic Fairness
• Machine Learning in Personnel Assessment
• +۴ مورد دیگر

Louis Hickman is an Assistant Professor of Industrial-Organizational Psychology at Virginia Tech’s Department of Psychology. He also serves as a Visiting Academic at Amazon and holds a Senior Fellow position at Wharton People Analytics, University of Pennsylvania. His research bridges technology and work, focusing on machine learning applications in organizational science, particularly automated interviews and algorithmic fairness. He leads the Workplace Assessment and Social Perceptions (WASP) Lab, exploring how biases influence hiring and using AI to reduce algorithmic bias. Hickman holds a Ph.D. in Industrial-Organizational Psychology from Purdue University (2021), alongside advanced degrees in Computer Science and Creative Writing. His work emphasizes interdisciplinary collaboration, spanning psychology, computer science, and management. Research Interests: Automated personnel assessment via AI Algorithmic bias mitigation in hiring Machine learning applications in HR and education Interpersonal perception dynamics Unproctored testing in the AI era Publications: Recent work examines automated interview validity, LLM impacts on testing, and recruitment algorithm ethics. His 2025 studies highlight risks of unproctored testing and bias in automated systems. Earlier research (2023–2022) explores text mining for personality assessment and fairness in AI-driven selection. Awards: None explicitly mentioned, though his work has been widely cited in organizational psychology and AI ethics domains. Advising & Labs: Currently not accepting graduate students for 2026, but oversees the WASP Lab. Past research collaborations include projects on LLM competencies, bias simulation, and algorithmic fairness frameworks. Grants and funding sources are unspecified in provided text.

Claudia Wagnerمشاهده پروفایل

استاد

• Computational Social Science
• Algorithmic Fairness
• Digital Behavioral Data
• +۷ مورد دیگر

Claudia Wagner is a full professor for Applied Computational Social Sciences at RWTH Aachen University and the Scientific Director of the Computational Social Science department at GESIS—Leibniz Institute for the Social Sciences. She is also an External Faculty member at the Complexity Science Hub Vienna. Her work bridges computer science and the social sciences to study algorithmic systems and their societal impacts. Her research focuses on socio-technical phenomena such as inequality, sexism, and perception bias in algorithmically infused societies. She investigates methodological challenges in using digital behavioral data to study human behavior, attitudes, and group dynamics. Her interests span computational social science, algorithmic fairness, network science, and AI ethics. The analysis of her recent publications reveals a strong emphasis on bias, fairness, and methodological rigor in digital data analysis. Her work spans AI psychometrics, gender inequality in online platforms, and validation frameworks for digital traces. She frequently publishes in top-tier venues such as Nature , Science , and AAAI conferences. DOC-fFORTE fellowship from the Austrian Academy of Sciences Four best paper awards at international conferences (ICWSM, CSCW, WWW, AAAI) Associate Editor, EPJ Data Science Steering Committee Member, International AAAI Conference on Web and Social Media Board Member, International Society for Computational Social Science Claudia Wagner has led and co-led substantial research projects funded by national and international agencies. She mentors a diverse group of PhD students working on topics like algorithmic bias, data quality, and dehumanization. She has organized training events such as the CSS Methods Summer School and delivered keynotes globally on inequality and computational social science. She leads the Computational Social Science department at GESIS and collaborates with interdisciplinary teams at RWTH Aachen and the Complexity Science Hub. Her group develops tools for measuring algorithmic impacts and visualizing disparities in socio-technical systems, such as the 'Planets of Disparity' dashboard.

Carsten Nowakمشاهده پروفایل

استاد پژوهش

• Conservation Genetics
• Wildlife Monitoring
• Environmental DNA (eDNA) Analysis
• +۵ مورد دیگر

Dr. Carsten Nowak serves as Head of Conservation Genetics at the Senckenberg Research Institute and Natural History Museum Frankfurt, where he leads the national reference center for genetic analyses of wolves and lynx. His work bridges cutting-edge molecular methods with practical conservation applications, focusing on wildlife monitoring and species preservation. Since 2010, his laboratory has been responsible for central examination of all samples collected through Germany's nationwide wolf and lynx monitoring programs. Nowak's research interests center on developing highly sensitive molecular marker systems for wildlife monitoring, with particular expertise in environmental DNA (eDNA) methods and SNP chips optimized for genotyping forensic and non-invasively collected environmental samples. His work addresses critical questions in conservation biology, including inbreeding, genetic impoverishment, population origins, and human environmental impacts on genetic population structures of native species. He investigates how genetic methods can clarify previously unanswered questions in nature conservation, where data limitations often hinder efficient and targeted conservation measures. His extensive publication record (2023-2025) reveals a strong focus on wolf population dynamics across Europe, hybridization detection methodologies, and conservation genomics of endangered species like the garden dormouse. Nowak's research demonstrates sophisticated approaches to tracking animal movements across national borders, assessing genetic diversity in recovering populations, and developing practical tools for non-invasive wildlife monitoring. His work on wolf-dog hybridization has particular policy relevance as wolf populations expand across Europe. As a public-facing scientist, Nowak regularly engages with policymakers and the public through presentations, media appearances, and citizen science projects. He has participated in high-profile events including briefings for Federal Environment Minister Svenja Schulze and numerous public lectures on wildlife conservation topics. His leadership extends to coordinating international research collaborations, including the CEwolf Consortium and various transboundary monitoring networks. Nowak directs the Center for Wildlife Genetics in Gelnhausen, where his team conducts DNA-based analyses of predator-prey interactions, livestock depredation incidents, and wildlife population monitoring. His laboratory serves as the national reference center for genetic analyses of wolves and lynx in Germany, processing samples from across the country to distinguish individuals, determine relatedness, and monitor population health. The center also develops molecular methods for detecting wolf-dog hybrids and other conservation genetics applications.

Shamya Karumbaiahمشاهده پروفایل

استادیار

• Human-Centered AI in Education
• Equitable and Responsible AI
• Algorithmic Bias in Education
• +۳ مورد دیگر

Shamya Karumbaiah is an Assistant Professor in the Learning Sciences department at the University of Wisconsin–Madison's School of Education. She holds a PhD in Learning Sciences from the University of Pennsylvania (2021) and previously served as a postdoc fellow at Carnegie Mellon University. Her research focuses on equitable and responsible use of AI in education, addressing algorithmic bias, and methodological innovations in learning analytics. Education: PhD in Learning Sciences (University of Pennsylvania, 2021), MS in Computer Science (University of Massachusetts Amherst, 2017), BE in Computer Science (Sri Jayachamarajendra College of Engineering, 2011). Research Interests: Human-centered AI in education, algorithmic bias mitigation, affective computing, and teacher practices in human-AI collaboration. She critiques colonial continuities in algorithmic systems and advocates for upstream equity in AI development. Awards: Includes the Nellie McKay Fellowship (UW-Madison), multiple best paper nominations, and the Dean’s Fellowship (UPenn). Grants & Labs: Active in projects analyzing multimodal classroom data and AI ethics. Collaborates with institutions like Cisco and USC ICT.

• Behavioral Ecology
• Animal Behavior
• Social Systems
• +۴ مورد دیگر

Eli D. Strauss is a behavioral ecologist and Postdoctoral Researcher at the Max Planck Institute of Animal Behavior and the University of Konstanz. He will transition to an Assistant Professor position at the Department of Integrative Biology, Michigan State University in late 2025. His research focuses on the evolution of stable social systems, particularly in spotted hyenas, analyzing how individual behaviors and relationships shape group-level dynamics. Strauss employs field experiments, computational techniques, and long-term observational data to study dominance hierarchies, social inequality, and the interplay between individual experiences and collective behaviors. Research Interests : Strauss investigates how societies emerge from individual interactions, emphasizing long-term perspectives. Key themes include dominance hierarchy dynamics, social inheritance, and the ecological drivers of social behavior. His work bridges behavioral ecology with computational methods, addressing questions about social structure stability and evolutionary adaptations. Key Projects : Co-director of the Mara Hyena Project in Kenya, a long-term study on hyena behavior and ecology. Developing methodologies for longitudinal studies of dominance hierarchies, including frameworks for analyzing hierarchy dynamics across timescales. His computational tools (e.g., DynaRankR ) are widely used for dominance inference. Upcoming Initiatives : Establishing a lab at Michigan State University focusing on social behavior and collective ecology. Recruiting graduate students and postdocs to study social systems, computational ecology, and animal behavior.

Samet ÖZDEMİRمشاهده پروفایل

پژوهشگر

• Human Resources Management
• Organizational Behavior
• Reverse Mentoring
• +۵ مورد دیگر

Res.Asst.Dr. Samet ÖZDEMİR is a faculty member at the Department of Human Resources Management within Sakarya University's Faculty of Business Administration. He holds a Researcher academic rank and teaches courses such as Social Entrepreneurship, Career Planning, Human Resources Management, and Graduation Project supervision. His research focuses on reverse mentoring, HR risk assessment, workplace discrimination, leadership competencies, and sustainable career development. He has published extensively in national and international journals, contributing to organizational behavior and management science domains. Education & Academic Background: While specific educational details are not explicitly stated, his titles (Res.Asst.Dr.) indicate doctoral-level qualifications in a relevant field such as Business Administration or Human Resources Management. His academic contributions include co-authoring book chapters on topics like digital HR management and sustainable entrepreneurship. Research Interests: His work bridges theoretical frameworks with practical HR applications, emphasizing reverse mentoring case studies (e.g., research assistants-advisors dynamics), ethical recruitment practices, and leveraging digital tools for leadership development. He also explores cross-cultural career perceptions and the role of lifelong learning in managerial roles, as seen in his analysis of historical business figures like Madam C.J. Walker. Publication Trends: Recent works (2022-2023) highlight digital transformation in HR practices, entrepreneurship competency frameworks, and LinkedIn-based executive leadership analysis. Earlier studies (2015-2017) addressed blue-collar workforce underrepresentation in academic research and discrimination in HR job advertisements. Teaching & Supervision: He manages various theses and oversees vocational training programs, integrating practical workplace experiences into academic curricula. Courses like 'Vocational Training in Business' and 'Career Planning' reflect his commitment to bridging educational theory with professional readiness. Awards & Grants: No specific awards are mentioned, though his active publication record suggests contributions meriting academic recognition. Grant details are not provided in the text. Labs & Teams: While no specific labs are noted, his collaborative publications indicate involvement in academic teams focusing on human resources innovation, organizational behavior, and sustainable development initiatives.

Aaron A. Kingمشاهده پروفایل

استاد

• Theoretical Ecology
• Epidemiological Dynamics
• Evolutionary Biology
• +۵ مورد دیگر

Aaron A. King, Ph.D. , is the Nelson G. Hairston Collegiate Professor of Ecology and Evolutionary Biology, Complex Systems, and Mathematics at the University of Michigan and an External Professor at the Santa Fe Institute . He is a Fellow of the American Association for the Advancement of Science and a Biological Sciences Scholar at the University of Michigan. His research integrates mathematical modeling, statistical inference, and empirical data to study ecological and epidemiological systems. Education: Ph.D. in Applied Mathematics, University of Arizona, 1999 M.A. in Mathematics, University of Hawai'i, 1992 B.A. summa cum laude in Mathematics, Rice University, 1989 Research Interests: Dr. King's lab focuses on the dynamics of ecological, epidemiological, and evolutionary systems . His work includes: Modeling host-pathogen systems (COVID-19, influenza, dengue, pertussis, cholera, malaria) Antibiotic resistance in hospital settings Statistical inference for ecological and epidemiological data Integration of genomic and epidemiological data Mathematical frameworks for understanding parasite infections and immune responses Scientific Awards: Fellow of the American Association for the Advancement of Science Biological Sciences Scholar, University of Michigan Teaching and Mentorship: Dr. King teaches courses in Mathematical Ecology , Adaptive Systems , and Statistical Inference . He mentors graduate students and postdoctoral fellows, including Avinash Subramanian and Madeline Peters , and is affiliated with multiple interdisciplinary centers at the University of Michigan. Lab and Collaborations: He leads the King Laboratory of Theoretical Ecology & Evolution , which emphasizes reproducible research and rigorous theoretical approaches. The lab collaborates with institutions like the Santa Fe Institute and accepts students from programs such as Ecology & Evolutionary Biology , Applied & Interdisciplinary Mathematics , and Data Science .

• Biostatistics
• Public Health
• Epidemiology
• +۹ مورد دیگر

Dr. Shuvo Bakar is a Senior Lecturer in the Sydney School of Public Health at the University of Sydney, within the Faculty of Medicine and Health. He holds a PhD in Statistics from the University of Southampton, UK, and has prior experience as an Assistant Professor at Yale University, Lecturer at the Australian National University, and Scientist at Data61 (CSIRO). His research focuses on statistical methods applied to public health challenges, including Bayesian hierarchical modeling, machine learning, spatio-temporal analysis, and their applications in epidemiology, clinical trials, and environmental health. Dr. Bakar's research interests span statistical methodologies such as Bayesian adaptive designs, small area estimation, and spatial risk modeling, alongside applications in child health, infectious diseases, and extreme weather impacts on health. He is an active member of academic communities, including the Royal Statistical Society (RSS Fellow), Statistical Society of Australia, and the Australian Trials Methodology Research Network. His work also involves collaborations on grants totaling millions in funding, addressing topics like climate change impacts on health inequity and cardiovascular disease prevention in remote regions. Education: PhD in Statistics (University of Southampton, UK) Key Research Themes: Obesity, Diabetes, Cardiovascular Disease; Reproductive, Maternal & Child Health Grants/Projects: Includes NHMRC-funded trials on respiratory infections in First Nations children and MRFF grants for cardiovascular risk reduction in regional Australia. Dr. Bakar's contributions extend to editorial roles for Nature Scientific Reports and Discover Public Health , and his research has been published in journals like PloS One , Climatic Change , and Journal of the Royal Statistical Society .

Kevin Langergraberمشاهده پروفایل

دانشیار

• Primate Behavior
• Conservation Biology
• Genetics
• +۳ مورد دیگر

Dr. Kevin Langergraber is an Associate Professor at Arizona State University's School of Human Evolution and Social Change. His research focuses on primate behavior, conservation biology, and evolutionary anthropology, particularly through his leadership in the Ngogo Chimpanzee Project in Uganda's Kibale National Park. This long-term study examines chimpanzee social structures, health dynamics, and ecological interactions, with a strong emphasis on conservation strategies against poaching and disease transmission. Key research interests include genetic adaptation in primates, the impact of human activities on wildlife communities, and behavioral ecology across varying environmental conditions. He has pioneered methods combining genomic analysis, field observations, and machine learning to study ape behavior and biodiversity monitoring. His work integrates socioecological data with physiological measurements to understand aging patterns, reproductive strategies, and disease epidemiology in wild populations. Recent publications highlight advancements in wildlife conservation protocols, primate menopause studies, and innovative datasets for behavior recognition. Collaborations span global institutions to address challenges in primate conservation and evolutionary biology. Dr. Langergraber also engages in public outreach through documentaries and crowdfunding initiatives to fund anti-poaching patrols and support chimpanzee research.

• Clinical and Health Psychology
• Social and Personality Psychology
• Applied and Developmental Psychology
• +۷ مورد دیگر

Dr. Bradley Elphinstone is a Senior Lecturer in the School of Health Sciences at Swinburne University of Technology, where he conducts research and teaching in clinical and health psychology, with a focus on mindfulness, nonattachment, self-compassion, and gender-affirming mental health. He is actively involved in PhD supervision and has led research on public trust in genomic data, emotional well-being, and digital mental health interventions. His research interests include: Clinical and Health Psychology Social and Personality Psychology Mindfulness-Based Interventions Nonattachment and Self-Compassion Gender Euphoria and Transgender Mental Health Public Trust in Health Data Systems His recent publications (2020–2025) reflect a strong trend in psychometric scale development (e.g., Gender Euphoria Scale, Equanimity Scale), emotional regulation, and public health psychology, particularly during the pandemic. His work bridges clinical psychology with public engagement and policy, especially in genomic governance and mental well-being. Scientific contributions include: Development and validation of psychological scales Studies on trust and compliance during public health crises Exploration of non-dualistic approaches to mental health (e.g., A Course in Miracles) Telehealth and dignity therapy for older adults Dr. Elphinstone supervises multiple PhD students on topics ranging from financial well-being to gender identity and digital interventions. He has secured external funding, including a grant from the Department of Health and Aged Care on genomic data trust. He is also involved in collaborative research networks and public engagement through platforms like The Conversation. He is affiliated with research teams focused on: Mindfulness and psychological development Trans and gender diverse mental health Digital and telehealth interventions Public attitudes toward biobanks and genomics

Geoff Childsمشاهده پروفایل

استاد

• Anthropological Demography
• Tibetan Societies
• Migration Studies
• +۴ مورد دیگر

Geoff Childs is a Professor of Sociocultural Anthropology at Washington University in St. Louis, Department of Anthropology. He holds a PhD from Indiana University. His research bridges anthropology and demography, focusing on Tibetan communities in Nepal, China, and India. He investigates demographic trends, migration, family strategies, and adaptation to rapid development. Education: PhD in Anthropology and Tibetan Studies from Indiana University (2001). Research interests include: Interdisciplinary methods combining quantitative demography and qualitative ethnography. Demographic transitions in Tibetan societies, including fertility, migration, and aging. Impact of development policies on highland communities. Key projects include: Long-term fieldwork in Nubri, Nepal, since 1995, supported by NSF, Fulbright, and others. Collaborative research on elderly well-being in Tibet with Melvyn Goldstein and Puchung Wangdui. Studies on Yartsa Gunbu (cordyceps) harvesting and its socioeconomic impacts. Publications span books and peer-reviewed articles, including Tibetan Diary (2004) and From a Trickle to a Torrent (2018). His work frequently explores themes of cultural preservation, migration, and development. Grants and collaborations include funding from NSF, Wenner-Gren, and co-PI roles with institutions like Case Western Reserve University and the Tibet Academy of Social Sciences. Labs/Teams: Active in multidisciplinary teams studying highland adaptation, including projects on genetics and reproduction in high-altitude populations with Cynthia Beall and Sienna Craig.

Liqun Diaoمشاهده پروفایل

دانشیار

• Statistical Methodology
• Machine Learning
• Causal Inference
• +۷ مورد دیگر

Liqun Diao is an Associate Professor (Tenured) in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds affiliations with the Health Data Science Lab and the Waterloo Artificial Intelligence Institute. His research focuses on developing statistical methods and machine learning algorithms for applications in medicine, public health, and insurance. Education: B.Econ. in Statistics, Renmin University of China (2007) M.Math. in Statistics (Biostatistics), University of Waterloo (2009) Ph.D. in Statistics (Biostatistics), University of Waterloo (2013) Research Interests: Recursive partitioning and tree-based methods for survival and health data Causal inference and missing data methodologies Bayesian nonparametric models and copula dependence structures Mortality forecasting and actuarial science applications Awards: 2013 Pierre Robillard Award (best doctoral thesis in Canadian statistics) 2024 Outstanding Performance and Teaching Awards at UW Professional Activities: Led research groups in health data science and AI Recipient of multiple grants from NSERC and industry partners Advises graduate students in statistics and actuarial science Labs/Teams: Active contributor to the Health Data Science Lab and Waterloo AI Institute, focusing on applying statistical innovations to real-world health and insurance challenges.

Olga Maslovskayaمشاهده پروفایل

دانشیار

• Survey Methodology
• Data Quality
• Survey Data Collection
• +۳ مورد دیگر

Dr. Olga Maslovskaya serves as an Associate Professor in Survey Research and Social Statistics at the University of Southampton within the Faculty of Social Sciences, Department of Social Statistics and Demography. She is a prominent Survey Methodologist specializing in data quality and survey data collection methodologies. As Principal Investigator of the Survey Data Collection Network (SDC-Net), she leads research on the impact of COVID-19 on survey methodologies and previously directed the GenPopWeb2 international network focused on transitioning to online data collection. Her research interests center on all aspects of survey methodology with particular emphasis on data quality, survey data collection techniques, non-probability-based surveys, and mixed-mode survey design. She has made significant contributions to understanding smartphone survey effects, response propensity modeling, and the development of online survey methodologies for demographic research. Analysis of her recent publications reveals a strong focus on methodological innovations in survey research, particularly examining data quality across different survey modes, developing advanced statistical techniques for addressing nonresponse, and advancing online survey design for demographic studies. Her work frequently addresses practical challenges in contemporary survey methodology while maintaining rigorous statistical standards. Dr. Maslovskaya has secured substantial research funding through multiple ESRC grants for projects including the Generations and Gender Survey in the UK and the Survey Data Collection Network. She serves as a Co-Investigator on major ESRC-funded initiatives and leads methodological workpackages for national survey implementations. She currently supervises PhD students Ni Kadek Oki Wahyu Krisnadevi and Norizan Abdullah in the Social Statistics and Demography program. Her external professional engagements include membership on the editorial board of the Journal of Survey Statistics and Methodology (2020-2024), active participation in the Royal Statistical Society (2018-2024), and membership in the European Survey Research Association (2021-2025). As a member of the Statistical Sciences Research Institute (S3RI), Dr. Maslovskaya contributes to the Methodological Innovation: Survey Methods and Official Statistics research group. Her current projects examine underrepresented population subgroups in surveys, patient perspectives on health data collection, and continuing research on survey data collection methods in the post-pandemic era.

Katharina Rebay-Salisburyمشاهده پروفایل

استاد

• Prehistoric Archaeology
• European Bronze and Iron Ages
• Archaeology of the Human Body
• +۵ مورد دیگر

Univ.-Prof. Katharina Rebay-Salisbury is a prehistoric archaeologist specializing in European Bronze and Iron Ages, particularly focusing on the human body, social identities, and gender archaeology. She leads the Research Group 'Prehistoric Identities' at the Austrian Academy of Sciences (ÖAI) and holds a professorship in Prehistory of Humanity at the University of Vienna. Her work bridges archaeology with bioarchaeology, genetics, and proteomics. After earning her PhD from the University of Vienna (2005), she conducted postdoctoral research at Cambridge and Leicester, exploring cremation practices and Iron Age networks. She received the ERC Starting Grant (2015) for studying societal responses to motherhood and childbirth. Key projects include analyses of cremated remains, mobility patterns, and kinship structures in prehistoric communities. Education: PhD (2005, University of Vienna), Habilitation (2017, University of Vienna). Research interests include bioarchaeology, maternal status, and interdisciplinary methods. She is a member of the Young Academy of the Austrian Academy of Sciences (since 2016) and has published extensively on prehistoric burial practices, gender roles, and archaeological theory. Her research integrates osteological analysis, isotopic studies, and ancient DNA to reconstruct social dynamics. Notable contributions include studies on Bronze Age maternal health, mobility inferred from cremation burials, and leadership roles in Iberian megalithic societies. She chairs the ERC-funded project 'The Value of Mothers to Society' and collaborates internationally on bioarchaeological projects. Grants and awards include the ERC Starting Grant and multiple fellowships. Her team addresses questions of social inequality, kinship, and human-environment interactions in prehistory.