جست‌وجوی استاد و پژوهشگر

Steven Neubergمشاهده پروفایل

استاد

• Evolutionary Psychology
• Social Cognition
• Prejudice and Stereotyping
• +۴ مورد دیگر

Steven Neuberg is a Foundation Professor in the Department of Psychology at Arizona State University (ASU), where he directs the Evolution, Ecology, and Social Behavior Lab and co-directs the Kenrick-Neuberg Social Cognition Laboratory. He founded the ASU Global Group Relations Project, a multidisciplinary initiative examining intergroup conflict drivers like religion. Affiliated with ASU’s Center for Social Dynamics and Complexity and the Global Futures Laboratory, his work integrates evolutionary theory and social cognition to explore prejudices, stereotypes, and ecological influences on behavior. Education: A.B. Cornell University (1983) M.A. Carnegie Mellon University (1984) Ph.D. Carnegie Mellon University (1987) NATO Postdoctoral Fellowship, University of Waterloo (1987–1988) Research Interests: Neuberg investigates how fundamental motivations—such as self-protection, disease avoidance, and mating—shape social cognition and behavior. His research addresses stigma, prejudice, and intergroup conflict through an evolutionary lens, examining how ecological factors (e.g., resource scarcity, disease threats) modulate social perceptions. Recent work explores COVID-19’s impact on prejudices and environmental aesthetics in migration decisions. Publication Trends: Neuberg’s recent articles emphasize evolutionary psychology frameworks applied to social phenomena like stereotyping, life satisfaction, and cultural variation. Key themes include affordance management (how people perceive and act on social opportunities/threats), ecological influences on cognition, and functional approaches to prejudice. His work consistently bridges theoretical innovation with empirical rigor across cross-cultural and experimental studies. Awards and Honors: Gordon Allport Intergroup Relations Prize Daniel M. Wegner Theoretical Innovation Prize Fellow, American Association for the Advancement of Science (AAAS) ASU Outstanding Doctoral Mentor Award ASU College of Liberal Arts and Sciences (CLAS) Outstanding Teaching Award Advising and Grants: Neuberg has mentored over 50 doctoral and master’s students, many now faculty at institutions like UCLA, UC Irvine, and Hamilton College. His research is funded by the National Science Foundation (NSF), National Institutes of Health (NIH), Templeton World Charity Foundation, and Army Research Institute. Notable grants include a study on religious fasting’s paradoxical effects on prosociality and a RAPID project analyzing COVID-19’s impact on prejudices. Labs and Teams: He leads the Evolution, Ecology, and Social Behavior Lab, investigating stereotypes, prejudices, and ecological affordances. The Kenrick-Neuberg Lab focuses on social cognition and decision-making. Neuberg also oversees Psych for Life®, an ASU initiative promoting applied psychology for public benefit.

Chris Spencerمشاهده پروفایل

پژوهشگر ارشد

• Statistical Genetics
• Genetic Epidemiology
• Infectious Diseases
• +۳ مورد دیگر

Chris Spencer is a Wellcome Trust Career Development Fellow at the Nuffield Department of Medicine, University of Oxford. His research focuses on statistical genetics, with emphasis on African population genetics, malaria susceptibility (via the MalariaGEN consortium), and stratified medicine applications in hepatitis C (STOP-HCV consortium). He develops methodologies to analyze genetic determinants of host-parasite interactions and their role in disease prevention and treatment. His work explores infectious disease impacts on human immune physiology through natural selection, aiming to translate genetic insights into clinical strategies. Recent studies include structural variation in malaria resistance genes and polymorphisms linked to pneumococcal bacteremia in Kenyan children. His computational tools, such as FINEMAP, advance variable selection in genome-wide association studies. Publications span malaria genetics, viral resistance, and population admixture, reflecting a multidisciplinary approach to genomic medicine. Collaborations with global consortia highlight his commitment to addressing global health challenges through genetics.

Kushal Deyمشاهده پروفایل

استادیار

• Computational Biology
• Genomics
• Machine Learning
• +۵ مورد دیگر

Kushal Dey, PhD, is an Assistant Professor in the Computational and Systems Biology Program at Memorial Sloan Kettering Cancer Center (MSKCC). His research develops machine learning models that integrate genetic, genomic, and epigenomic data (e.g., RNA-seq, ChIP-seq, Perturb-seq, spatial transcriptomics) to decode the causal functional architecture of heritable complex diseases, including immune-related disorders like Alzheimer’s and inflammatory bowel disease, as well as heritable cancers such as breast and prostate cancer.

Todd Oakleyمشاهده پروفایل

استاد

• Evolution
• Bioluminescence
• Convergent Evolution
• +۷ مورد دیگر

Todd Oakley is a Professor and Department Chair of the Department of Ecology, Evolution, and Marine Biology (EEMB) at the University of California, Santa Barbara (UCSB). He joined the faculty in 2003 and currently serves as Vice Chair of resources for EEMB, while also being a member of UCSB’s Marine Science Institute. His academic career includes a BS and MS from the University of Wisconsin-Milwaukee, a PhD in Biological Sciences from Duke University, and an NIH-NRSA postdoctoral fellowship at the University of Chicago. His research focuses on the origins and evolution of complex traits, particularly visual systems and bioluminescence in marine invertebrates. The lab investigates four main paths: (1) the evolutionary origins of vision and light-interacting genes, (2) diversification of arthropod eye designs, (3) convergent evolution in mollusks like octopuses and chitons, and (4) genetic drivers of ecological interactions in algae relevant to biofuel production. Notable tools developed include the Osiris Galaxy workflow for phylogenomic analysis and the CoMET plug-in for character evolution modeling. Dr. Oakley has advised over 17 students, including graduate and undergraduate researchers, many of whom have pursued postdoctoral or academic roles. His scientific contributions include the NIH-NRSA postdoctoral fellowship and over 119 peer-reviewed publications, often leveraging phylogenetics and genomics to address evolutionary questions. Collaborators include institutions like University of Chicago, UC-Davis, and international centers such as the University of Tartu and Museum Victoria. The lab emphasizes interdisciplinary approaches, combining fieldwork, molecular techniques, and computational biology.

Jon Olav Vikمشاهده پروفایل

استاد

• Systems Biology
• Computational Biology
• Aquaculture
• +۷ مورد دیگر

Jon Olav Vik is a Professor at the Norwegian University of Life Sciences (NMBU), affiliated with the Department of Mathematical Sciences and Technology within the Faculty of Science and Technology. He leads the DigiSal project—"Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture"—funded under the Research Council of Norway’s Digital Life initiative. He is also a lead modeller in the GenoSysFat project, which aims to enhance omega-3 content in farmed salmon through integrated genomics and systems biology approaches. His research spans systems biology , computational physiology , genotype-phenotype modeling , and ecological dynamics . He works at the intersection of biology, mathematics, and computer programming, developing models to understand how genetics, nutrition, and environment interact in fish and ecological systems. His pedagogical focus includes biostatistics and programming in R, and he teaches courses such as STIN100, STIN300, and STAT100. The 15 most recent publications reflect a consistent focus on systems-level understanding in biology, particularly in salmon aquaculture, metabolic regulation, and genotype-phenotype relationships. These works appear in high-impact journals like Nature , Science , PLOS Computational Biology , and Journal of The Royal Society Interface , demonstrating interdisciplinary reach across computational biology, genomics, ecology, and biostatistics. Key themes include metabolic modeling, microbiome stability, lipidome remodeling, and sensitivity analysis in dynamic models. Jon Olav Vik has contributed to major collaborative efforts including the Infrastructure for Systems Biology Europe (ISBE) , where he helped develop frameworks for "modelling as a service." He has also authored book chapters and technical deliverables on systems biology and modeling practices. He actively supervises students and invites master’s thesis candidates with interests in quantitative biology. While no specific awards are listed, his leadership in national and international research projects underscores his scientific impact. His work supports both fundamental science and sustainable aquaculture innovation.

Margaret Kalacskaمشاهده پروفایل

دانشیار

• Remote Sensing
• Environmental Science
• Hyperspectral Imaging
• +۷ مورد دیگر

Margaret Kalacska is an Associate Professor in the Department of Geography at McGill University, leading the Applied Remote Sensing Lab. Her research focuses on advancing remote sensing technologies like hyperspectral imaging, Remotely Piloted Aircraft Systems (RPAS), LiDAR, and thermal imaging for environmental science and natural hazard monitoring. She has pioneered the use of RPAS-HSI systems, including developing Canada’s first fully operational RPAS-HSI for the Canadian Airborne Biodiversity Observatory (CABO) since 2018. Dr. Kalacska holds a PhD and MSc in Earth and Atmospheric Sciences from the University of Alberta. Her interdisciplinary work spans Canada, Brazil, Tanzania, Ghana, the Peruvian Amazon, Panama, Madagascar, and Costa Rica. Notable achievements include being the first Canadian woman to lead an airborne hyperspectral mission (MAC-13) in Costa Rica (2013) and receiving the Silver Medal from the Canadian Remote Sensing Society (2018). Her lab specializes in integrating cutting-edge remote sensing tools for biodiversity conservation, ecosystem monitoring, and disaster response. Recent projects include the Fish + Forest initiative studying aquatic habitats in Brazil and advancing custom RPAS for hyperspectral imaging. She also collaborates with the National Research Council of Canada and international organizations like NATO. Awards: Fessenden Prize (2014), Silver Medal (2018), Steacie Prize Nomination (2020) Key Projects: CABO, Fish + Forest , RPAS-HSI System Development Technologies: UAV LiDAR, Structure-from-Motion Photogrammetry, Satellite Data Validation Her research bridges environmental science and technology, emphasizing global applications in conservation and climate resilience.

• Autism Genetics
• Genetic Architecture
• Copy Number Variants
• +۵ مورد دیگر

Lauren Weiss, PhD is a Professor of Psychiatry at the University of California, San Francisco (UCSF) School of Medicine and a faculty member at the UCSF Weill Institute for Neurosciences. Her research focuses on understanding the genetic architecture of autism spectrum disorder through genome-wide genetic data analysis and human induced pluripotent stem cell (iPSC) models. Dr. Weiss's laboratory investigates the genetic mechanisms by which DNA variants influence autism risk, examining questions about copy number vs. SNP variation, rare vs. common variation, gene-sex interaction, gene-gene interaction, and gene-environment interaction. Her team uses rich genetic datasets to identify susceptibility loci and the physiological pathways these risk loci implicate. Additionally, they employ iPSC models to study known mutations or copy number variants predisposing to autism, first identifying the effects of genetic risk variants and then determining whether these effects can be modified at the cellular level by environmental or pharmacological agents. Analysis of Dr. Weiss's recent publications reveals a strong focus on sex differences in autism genetics, the role of specific copy number variants (particularly 16p11.2 and 22q11.2), maternal environmental factors during pregnancy, and the integration of multi-omics data to understand neurodevelopmental pathways. Her work bridges basic genetic research with potential clinical applications for improving understanding, prevention, diagnosis, and treatment of autism and related traits. Dr. Weiss has secured significant research funding as Principal Investigator on multiple NIH grants, including R01MH114924 (Decoding the Genetics of Sexual Dimorphism in Autism Spectrum Disorders), R01MH107467 (Utilizing eQTL networks to gain biological insight into multigenic CNVs), and DP2OD007449 (Dissecting Epistasis and Pleiotropy in Autism towards Personalized Medicine). Her laboratory offers research opportunities for students interested in analytical genetics projects related to gene-environment effects, gene-sex effects, gene-gene effects, and the relationship between ASD and brain size. Dr. Weiss actively collaborates with numerous researchers across institutions, particularly on large-scale genomic studies of autism and other neurodevelopmental disorders. Her work has contributed significantly to our understanding of the complex genetic architecture underlying autism spectrum disorder and related conditions.

Tim Rogersمشاهده پروفایل

استاد

• Stochastic Processes
• Random Matrix Theory
• Collective Behavior
• +۴ مورد دیگر

Professor Tim Rogers is affiliated with the University of Bath as a faculty member in the Department of Mathematical Sciences . He is actively involved in research spanning complex systems, network theory, and stochastic processes. PhD in Random Matrix Theory from King's College London (2010) His research focuses on emergent behavior in random systems , including: Collective Behavior : Crowd dynamics, lane formation, and noise-enhanced synchronization Epidemics & Networks : Spread prediction, node risk assessment, and misinformation impacts Ecology & Evolution : Trait emergence, species boundaries, and demographic noise effects Random Matrix Theory : Spectral analysis and applications to complex systems Publication trends reflect interdisciplinary work bridging Physics, Biology, and Mathematics , with a focus on network structures , stochastic modeling , and emergence phenomena . Scientific awards include: 2015 : Editor's Choice for Europhys. Lett. 109, 28005 2016 : Highlight of Journal of Physics A 2017 : Editor's Suggestion for Phys. Rev. E 92, 032708 He has supervised numerous PhD students and postdocs on projects related to stochastic dynamics , network modeling , and mathematical biology , with ongoing grants from agencies like EPSRC and The Leverhulme Trust .

Howard Rundleمشاهده پروفایل

استاد

• Evolutionary ecology
• Evolutionary genetics
• Sexual selection
• +۷ مورد دیگر

Howard Rundle is a Full Professor in the Department of Biology within the Faculty of Science at the University of Ottawa. His research laboratory focuses on empirical studies in evolutionary ecology and evolutionary genetics, utilizing both laboratory and field approaches with model systems including various Drosophila species and the antler fly ( Protopiophila litigata ). His work is conducted both in controlled laboratory settings and in natural environments, particularly in Algonquin Park's Wildlife Research Station. Dr. Rundle's primary research interests span evolutionary ecology and evolutionary genetics, with particular emphasis on: The role of sexual selection in adaptation and purging of deleterious mutations Sexual conflict and its ecological context The evolutionary divergence of mate preferences and its contribution to speciation Quantitative genetics of sexual displays, particularly cuticular hydrocarbons in insects The impact of ecological complexity on evolutionary processes His recent publications reveal a consistent focus on how mating environments influence the dynamics of sexual conflict, adaptation, and speciation. Much of his work examines whether sexual selection helps or hinders adaptation, with growing emphasis on genomic approaches to understand the genetic basis of evolutionary responses. His research program demonstrates how ecological context fundamentally shapes evolutionary outcomes, particularly in the interface between natural and sexual selection. Dr. Rundle collaborates extensively with researchers at other institutions including Aneil Agrawal (University of Toronto), Russell Bonduriansky (University of New South Wales), Vincent Careau (University of Ottawa), Kelly Dyer (University of Georgia), Amanda Moehring (Western University), and Locke Rowe (University of Toronto). These collaborations enhance the scope of his research across multiple dimensions of evolutionary biology. The Rundle Lab maintains a strong commitment to equity, diversity, and inclusion, explicitly welcoming and supporting members from all racial, religious, and cultural backgrounds, as well as those from the LGBTQ+ community, operating under the University of Ottawa's principles in these areas.

Pier Palamaraمشاهده پروفایل

دانشیار

• Statistical Genetics
• Population Genetics
• Genomics
• +۶ مورد دیگر

Pier Palamara is an Associate Professor of Statistical and Population Genetics at the University of Oxford's Department of Statistics, affiliated with the Centre for Human Genetics. He holds a PhD in Computer Science from Columbia University (2014) and completed postdoctoral training at Harvard Chan School of Public Health and the Broad Institute of MIT and Harvard. His research integrates statistics, computer science, and genetics to develop methods for analyzing large genomic datasets, focusing on evolutionary parameters, demographic history, complex trait genetics, and disease variation. Key research interests include reconstructing population movements via genetic data, studying natural selection and mutation rates in human genomes, and developing scalable algorithms for genomic analysis. He leads the Palamara Lab, which collaborates on projects like the Genomics England haplotype reference panel and the UK Biobank imputation. His lab's work is supported by grants and partnerships, and they develop software tools such as ASMC, Quickdraws, and Threads. Recent publications highlight contributions to Indo-European genetic origins, scalable mixed-model association methods, and ancient DNA analysis of European farmers. He advises graduate students and has mentored researchers in computational biology and statistical genetics.

Ya-Jane Wangمشاهده پروفایل

استاد

• Carbohydrate Chemistry
• Starch Chemistry
• Rice Quality
• +۳ مورد دیگر

Jane Wang is a Professor in the Department of Food Science at the University of Arkansas , where she has served since 1999, progressing from Assistant to Full Professor. She also holds the title of Director of the Experiment Station in the Department of Food Science. Her research focuses on starch structure-functionality relationships , rice quality , and biomaterial utilization , with over 120 refereed publications and 5 patents. Education: B.S. in Agricultural Chemistry (1986) from National Taiwan University , M.S. in Food Science (1989) from the University of Minnesota , and Ph.D. in Food Science (1992) from Iowa State University . Postdoctoral research in starch chemistry at Iowa State University (1993-1994). Research Interests: Jane Wang's work explores starch chemistry, rice processing optimization, and value-added applications of agricultural byproducts. She investigates how starch modifications affect food and pharmaceutical properties, with a particular focus on parboiling, germination, and enzymatic treatments. Her research also examines the impact of environmental factors on rice starch development and quality. Scientific Awards: Outstanding Departmental Research Award (2008) Outstanding Volunteer, IFT Carbohydrate Division (2007) Outstanding Mentor, University of Arkansas (2005) Grants & Professional Service: She has secured over $3M in research funding, including USDA-NIFA grants and industry contracts with more than 50 food companies. Jane has served on numerous academic committees (Patent, Promotion & Tenure, Curriculum) and held leadership roles in professional organizations like IFT and AACC. She has also acted as associate editor for Cereal Chemistry and Carbohydrate Polymers , and reviewed for multiple journals and agencies. Labs & Teams: Dr. Wang leads the Carbohydrate Research Program at the University of Arkansas, focusing on starch structure-functionality, rice fortification, and biomaterial development. Her lab collaborates with industry partners and academic institutions to advance food science applications.

Michael Nothnagelمشاهده پروفایل

استاد

• Statistical Genetics
• Genetic Epidemiology
• Population Genetics
• +۵ مورد دیگر

Michael Nothnagel is a Professor at the University of Cologne, where he leads the Department of Statistical Genetics and Bioinformatics within the Cologne Center for Genomics (CCG). His work spans statistical genetics, genetic epidemiology, and forensic genetics, focusing on methodological development and large-scale genomic data analysis. His research interests encompass theoretical and applied statistical genetics, with emphasis on human genetic diversity, disease etiology, and forensic applications. Key areas include Y-chromosomal phylogeography, genome-wide association studies for complex diseases, development of statistical methods for variant interpretation, and forensic marker optimization. His group leverages next-generation sequencing data and specialized forensic markers to address questions in population history, disease mechanisms, and identification systems. Recent publications reveal a strong focus on computational approaches to genetic analysis, including spatial frequency interpolation for haplogroup mapping, polygenic risk score applications for behavioral traits, and advanced methods for variant classification. His work demonstrates consistent integration of statistical theory with practical applications in medical and forensic genetics, often through international collaborations like the VISAGE Consortium. Nothnagel maintains active involvement in the Cologne Center for Genomics, contributing to seminars and collaborative projects including the upcoming 34th International Genetic Epidemiology Society meeting. His research group operates at the intersection of computational biology and medicine, with particular strengths in handling complex genomic datasets and developing novel analytical frameworks for genetic epidemiology.

Robert Muscarellaمشاهده پروفایل

مدرس ارشد

• climate change
• community ecology
• tropical ecology
• +۵ مورد دیگر

Robert Muscarella is a Senior Lecturer at the Department of Ecology and Genetics, Plant Ecology and Evolution, Uppsala University. His work bridges plant ecology, climate change impacts, and tropical forest dynamics. Research interests include Climate change effects on forest structure Functional trait analysis Species distribution modeling Post-disturbance forest recovery Ecohydrology of tropical systems Remote sensing applications in ecology Recent publications highlight trends in tree mortality , hurricane impacts , drought responses , and functional trait variability across tropical ecosystems. Methodological contributions include open-access species distribution modeling tools.

Qiongshi Luمشاهده پروفایل

دانشیار

• Biostatistics
• Genetic Epidemiology
• Human Genetics
• +۳ مورد دیگر

Qiongshi Lu is an Associate Professor at the University of Wisconsin–Madison, affiliated with the Department of Biostatistics and Medical Informatics within the School of Medicine and Public Health. He also holds affiliate faculty positions in the Department of Statistics, Computer, Data & Information Sciences at the College of Letters and Science. His research focuses on developing statistical methods for human genetics, including genome-wide association studies (GWAS), gene-environment interactions, and genetic risk prediction. Lu’s work bridges computational biology, epidemiology, and clinical genetics, with a particular emphasis on understanding complex trait variability and resilience mechanisms in neurodegenerative diseases like Alzheimer’s. His lab (qlu-lab.org) explores innovative statistical frameworks such as PIGEON for gene-environment interaction analysis and has contributed to tools like the R package 'ipd' for predictive data inference. Recent studies highlight his interdisciplinary approach, addressing topics from congenital heart disease genetics to socioeconomic health gradients using large-scale genomic datasets. While no formal advisees are listed, his research collaborations span multiple institutions and disciplines.

Hilary Martinمشاهده پروفایل

پژوهشگر

• Medical Genomics
• Population Genetics
• Genetic Architecture of Diseases
• +۶ مورد دیگر

Dr. Hilary Martin is a Group Leader in Human Genetics at the Wellcome Sanger Institute and a College Research Associate at St John's College, Cambridge. Her research focuses on medical and population genomics, analyzing high-throughput sequence and genotype data from large cohorts to address various medical and population genetic questions. She leads the Martin Group which studies the genetic architecture of rare and common disorders in diverse populations, with particular emphasis on populations with high levels of parental relatedness. BSc (Human Genetics) from the University of Queensland, Australia PhD from the Wellcome Trust Centre for Human Genetics in Oxford Postdoctoral research at Sanger Institute with Jeff Barrett Group Leader at Sanger Institute since September 2018 Dr. Martin's research program spans several key areas in human genetics. Her group analyzes large-scale genetic and electronic health record data to explore fine-scale population structure, its impact on disease risk, and the genetic architecture of both rare and complex diseases. A particular focus is on populations with high levels of parental relatedness (consanguinity), where her team investigates how autozygosity affects disease risk across the phenotypic spectrum. Her work on developmental disorders examines the role of rare recessive variants and polygenic risk, while her research with South Asian populations explores the genetic basis of cardiometabolic diseases. Analyzing her recent publications reveals a strong trend toward multi-ancestry studies, particularly focusing on British Pakistani and Bangladeshi populations through the Genes & Health project. Her research increasingly integrates rare variant analysis with polygenic risk scores to understand the full genetic architecture of complex traits. There's also a growing emphasis on understanding how population structure, consanguinity, and founder effects influence disease risk across diverse populations. Her work bridges fundamental population genetics with clinical applications, particularly in neurodevelopmental disorders and cardiometabolic diseases. Extensive publication record in top journals including Nature, Cell, and Nature Genetics Leadership in major collaborative projects like Deciphering Developmental Disorders (DDD) Key contributions to understanding the role of consanguinity in disease architecture Development of methods for analyzing recessive variants in diverse populations Dr. Martin leads a dynamic research group comprising PhD students, postdoctoral fellows, and staff scientists. Her group works closely with multiple large-scale studies including the Avon Longitudinal Study of Parents and Children (ALSPAC), Millennium Cohort Study, Born in Bradford, Deciphering Developmental Disorders study, Genomics England, and Genes & Health. She maintains strong collaborations with clinical and research teams across the UK and internationally, particularly with groups studying South Asian populations. Her research has secured significant funding through institutional support and collaborative grants that enable large-scale genomic analyses. The Martin Group operates within the Human Genetics Programme at the Wellcome Sanger Institute, maintaining close ties with the Hurles Group and other related teams. They collaborate extensively with the East London Genes and Health project, which is one of the world's largest community-based genetics studies focusing on people of Pakistani and Bangladeshi heritage. The group maintains strict data security and confidentiality procedures while working closely with the communities they study through community engagement and dissemination of scientific findings.