جست‌وجوی استاد و پژوهشگر

• Autism Spectrum Disorders
• Medical Genetics
• Genomic Analysis
• +۳ مورد دیگر

Deqiong Ma is an Assistant Professor in the Department of Genetics at Yale University School of Medicine and Associate Director of the DNA Diagnostic Laboratory. She holds an MD from Tongji Medical University (1991), a PhD from the University of Tasmania (2003), and completed a postdoctoral fellowship at Duke University and a clinical fellowship at Albert Einstein College of Medicine. Her research focuses on genetic and genomic mechanisms underlying autism spectrum disorders, particularly copy number variants (CNVs), structural variation analysis, and clinical diagnostic methodologies. Key research interests include identifying novel genetic risk factors for autism using advanced genomic techniques, such as homozygosity mapping and fine-scale structural variation analysis. Her work bridges clinical genetics and molecular biology, with applications in diagnostic testing and understanding neurodevelopmental disorders. She collaborates extensively on studies involving autism candidate genes (e.g., MBD5, TBL1X) and genomic pathway analysis. Publications emphasize translational research, including diagnostic improvements for pediatric patients and elucidating genetic architecture in autism. She leads efforts in the DNA Diagnostic Lab to integrate genomic data into clinical practice, focusing on regions of homozygosity and uniparental disomy.

• Plant Developmental Biology
• Epigenetics
• Plant Genetics
• +۵ مورد دیگر

Ueli Grossniklaus is an Ordinary Professor at the University of Zurich within the Faculty of Mathematical and Natural Sciences , affiliated with the Department of Plant and Microbiology . His work focuses on plant developmental biology, particularly epigenetic and genetic mechanisms governing reproduction and adaptation. Key Courses: Epigenetics, Plant Biology Workshop, Group Seminars on Current Research Laboratory Techniques: Advanced methods in plant cell mechanics, transcriptomics, and genome editing Research Interests span plant epigenetics, reproductive biology, and the interplay between environmental stress and genetic regulation. He investigates: Mechanistic control of gametogenesis and fertilization Epigenetic contributions to plant adaptation Evolutionary implications of asexual reproduction Biophysical forces in plant cell growth Publication Trends (2025–2018) reveal expertise in: Arabidopsis and fern model systems Epigenetic regulation (DNA methylation, histone dynamics) Apomixis and hybrid seed failure mechanisms Biomechanics of pollen tubes and carnivorous plants Genome editing tools (CRISPR) and long-read sequencing Scientific Collaborations include interdisciplinary projects on: Microfluidic devices for plant cell analysis Gene drive ecology and ethics 3D imaging of plant reproductive structures Advising and Grants focus on mentoring through research internships in developmental biology, genetics, and systems biology. His lab engages in: Epigenetic response to environmental stress Cell wall mechanics in reproduction Computational modeling of plant growth Laboratory Teams integrate plant biologists, bioengineers, and computational scientists to study: Mechanistic gene regulation Evolutionary developmental biology Microrobotics for cellular force measurement

Max Pellertمشاهده پروفایل

استادیار

• Computational Social Science
• Digital Traces
• Affective Expression
• +۹ مورد دیگر

Max Pellert is a computational social scientist and cognitive scientist with faculty appointments at multiple institutions. Since 2022, he has served as an Assistant Professor at the Chair for Data Science in the Economic and Social Sciences at the University of Mannheim . He previously held an interim Professor position at the University of Konstanz and an Assistant Researcher role at Sony Computer Science Laboratories Rome. His work bridges computational methods with social science theory. Education M.Sc., University of Vienna (2017) in Middle European interdisciplinary Master's program in Cognitive Science (with distinction) Ph.D., Medical University of Vienna (2022) in Medical Informatics, Biostatistics & Complex Systems Research interests center on Computational Social Science , Digital Traces , and Natural Language Processing for emotion and sentiment analysis. He develops Temporal Adapters for tracking longitudinal emotional patterns and FAULTANA pipeline for polarization studies. His AI Psychometrics framework assesses personality-like traits in large language models. Recent publications include: (1) 2025 ACL work on political bias in LLMs; (2) 2025 ICWSM study of temporal emotion analysis; (3) 2024 Perspectives on Psychological Science paper on LLM psychometrics; (4) 2024 PNAS Nexus polarization analysis; (5) 2023 Emotion cross-cultural study of pandemic emotions. Scientific Awards Habilitation candidate status at University of Mannheim Teaching includes IS 616: Large Scale Data Analysis , IS 809: Advanced Text Mining Lab , and IS 723: Data Science Seminar at master’s and PhD levels. His Barcelona Supercomputing Center role focuses on principal investigator duties for computational social science projects.

Qiaoning Carol Zhangمشاهده پروفایل

استادیار

• Human-AI Collaboration
• Human-Robot Interaction
• Human Factors in Automated Vehicles
• +۴ مورد دیگر

Qiaoning Carol Zhang serves as Assistant Professor of Human Systems Engineering within The Polytechnic School at Arizona State University's Ira A. Fulton Schools of Engineering. Her research investigates the critical intersection of human perception, social contexts, and emerging technologies including artificial intelligence, robotics, and automated vehicles, with emphasis on creating intuitive, user-friendly, and inclusive systems. Her academic foundation includes: Ph.D. in Information, University of Michigan (2023) M.S. in Industrial and Operations Engineering, University of Michigan (2018) B.S. in Industrial Engineering, Hunan University (2016) Dr. Zhang's research program centers on understanding how individual differences and social dynamics shape technology interactions. Key focus areas include Human-AI Collaboration , Human-Robot Interaction , Human Factors in Automated Vehicles , and User Experience Design . Her work employs interdisciplinary methodologies to ensure technology adapts to diverse user needs across complex socio-technical environments, particularly in transportation and healthcare robotics. Analysis of her 15 most recent publications (2021-2025) reveals dominant themes in trust dynamics within automated vehicles, with significant attention to explainable AI interfaces. Research consistently examines how voice characteristics (gender, similarity), explanation modalities, and individual differences (age, personality) impact cognitive and affective trust. Recent work extends to healthcare robotics for elderly populations using Kano model analysis to identify critical user requirements. No scientific awards are documented in the provided materials. Dr. Zhang actively recruits Ph.D. candidates and undergraduate/master's researchers with backgrounds in human-computer interaction, data science, and interdisciplinary fields (design, computer science, cognitive science). She emphasizes opportunities in transportation technology, healthcare robotics, AI, and UX research/design, requiring applicants to submit CVs, research statements, and representative work samples. While specific grants aren't detailed, her research scope indicates substantial funding in human factors and emerging technology domains. Her research team focuses on developing empathetic technology through projects examining trust calibration in automated vehicles and healthcare robot design for older adults. Current initiatives include voice interface optimization for diverse user groups and Kano model applications in home healthcare robotics, aiming to bridge technical capabilities with human-centered design principles.

Florian Jeltschمشاهده پروفایل

استاد

• Community Ecology of Grasslands and Agricultural Landscapes
• Community Ecology of Drylands
• Biodiversity in Heterogeneous Environments
• +۵ مورد دیگر

Prof. Dr. Florian Jeltsch leads the Plant Ecology and Nature Conservation research group at the Institute of Biology and Biochemistry, University of Potsdam. His work spans multiple ecological domains with a focus on understanding biodiversity patterns and processes in changing environments. His research group investigates community ecology across various landscapes including grasslands, agricultural systems, and drylands. Dr. Jeltsch's research interests encompass Community Ecology of Grasslands and Agricultural Landscapes, Community Ecology of Drylands, Biodiversity in Heterogeneous Environments, Movement Ecology and Biodiversity Dynamics, and Applied Regional Conservation. His work integrates theoretical and empirical approaches to address pressing ecological questions related to global change. He has been instrumental in developing and applying individual-based models to understand complex ecological systems. Analysis of Dr. Jeltsch's recent publications reveals a strong focus on individual-based ecological modeling, movement ecology, and the impacts of landscape heterogeneity on biodiversity. His work spans from theoretical foundations to practical conservation applications, with particular emphasis on savanna ecosystems, habitat fragmentation effects, and climate change impacts. The research demonstrates integration of multiple scales from individual energetics to community dynamics. Dr. Jeltsch has mentored numerous doctoral students and postdoctoral researchers who have gone on to establish their own research careers. His group has been involved in multiple collaborative projects including BioHet, GrassYear, BioMove, and ORYCS, addressing biodiversity conservation in heterogeneous environments. The Plant Ecology and Nature Conservation group maintains active research stations including the Gülpe Research Station, providing field-based research opportunities. The group's work bridges theoretical ecology with practical conservation applications, particularly in the context of global environmental change.

Charu Gupta Kumarمشاهده پروفایل

استاد پژوهشی

• Systems and Computational Biology
• Microbiome/Pathogen Computational Genomics
• Metabolic Network Modeling
• +۳ مورد دیگر

Charu Gupta Kumar is a Research Professor in the Department of Bioengineering at the University of Illinois Urbana-Champaign, affiliated with the Neuroscience program. Her research focuses on systems and computational biology, integrating computational genomics, bioinformatics, and systems biology approaches to study microbiome/pathogen dynamics, neurological diseases, and evolutionary processes. She leads the Systems and Computational Biology Group, emphasizing interdisciplinary methodologies to address complex biological questions. Her academic roles include a zero-time appointment in the Department of Neuroscience (2013–present) and service as an admission reviewer for the Carle Illinois College of Medicine (2020–2022). She advises a diverse cohort of undergraduate and graduate students engaged in bioengineering and computational biology projects. Her work bridges environmental microbiology with human health, exploring astrocyte roles in neurological disorders like glioblastoma and autism, and investigating evolutionary mechanisms of metabolic networks across species. Publications highlight contributions to bovine genomics, microbial community analysis in subsurface environments, and computational tools for genomic data management. Her research trends emphasize translational applications of computational biology to environmental and clinical challenges, with recent focus on microbiome-disease interactions and astrocyte signaling pathways. Advising spans mentoring over 18 students across bioengineering and computer science disciplines, with notable alumni advancing to institutions like MIT and Johns Hopkins. She collaborates with跨学科 teams in bioengineering and neuroscience, contributing to the broader Grainger College of Engineering research ecosystem.

Melissa A. Schillingمشاهده پروفایل

استاد

• Innovation Strategy
• Technological Change
• Platform Ecosystems
• +۷ مورد دیگر

Melissa A. Schilling is the Herzog Family Professor of Management at New York University Stern School of Business, where she is also Deputy Chair of the Management & Organizations Department and Director of the Innovation Initiative at the Fubon Center for Technology, Business and Innovation. She joined NYU Stern in 2001 and is a leading scholar in innovation and strategic management. Ph.D., Strategic Management, University of Washington, 1997 B.S., Business Administration, University of Colorado at Boulder, 1990 Melissa Schilling's research centers on innovation in high-technology industries, including smartphones, biotechnology, pharmaceuticals, and renewable energy. She explores platform ecosystems, network externalities, technological standards, and the cognitive and social traits of breakthrough innovators. Her work integrates strategic management with organizational behavior and technological evolution. She is particularly known for her studies on how firms can accelerate innovation adoption and create value in complex ecosystems. Her recent publications reveal a strong trend in digital transformation, platform competition, and the cognitive foundations of visionary leadership. She analyzes how firms manage innovation in platform-based markets and how breakthrough ideas emerge from outlier thinking. Her articles frequently appear in top journals such as Strategic Management Journal , Organization Science , and Management Science . Scientific Awards and Recognitions: National Science Foundation CAREER Award 2022 Sumantra Ghoshal Award for Rigour and Relevance in Management 2018 Leadership in Technology Management, PICMET Best Paper in Management Science and Organization Science, 2012 Broderick Prize for Excellence in Research, Boston University Melissa Schilling has advised numerous doctoral students and contributed to major research initiatives, including a National Academy of Sciences committee on electric vehicle deployment. She has secured grants from the NSF and Kauffman Foundation. She is a senior editor at Strategy Science and serves on the editorial boards of several leading management journals. She also leads the Innovation Initiative at the Fubon Center, fostering industry-academia collaboration in tech innovation. She is actively involved in research labs and innovation centers at NYU Stern, particularly those focused on technology ecosystems and digital transformation. Her leadership in the Fubon Center drives interdisciplinary research on how businesses can leverage technological change for competitive advantage.

Facundo M. Fernandezمشاهده پروفایل

استاد

• Analytical Chemistry
• Bioanalytical Mass Spectrometry
• Ambient Sampling/Ionization
• +۴ مورد دیگر

Facundo M. Fernandez is a Regents' Professor and Vasser-Woolley Chair in Bioanalytical Chemistry at the Georgia Institute of Technology, where he leads the Fernandez Research Group within the School of Chemistry and Biochemistry in the College of Sciences. His research spans multiple cutting-edge areas of analytical chemistry with significant applications in medicine, forensics, and basic science. Dr. Fernandez earned his M.Sc. in Chemistry (1996) and Ph.D. in Analytical Spectrometry/Metallomics (1999) from the Facultad de Ciencias Exactas y Naturales at Buenos Aires University, Argentina. His research program focuses on Bioanalytical Mass Spectrometry with particular emphasis on Ambient Sampling/Ionization & Molecular Imaging, Ion Mobility Spectrometry, Metabolomics, and Pharmaceutical Forensics. His work has pioneered new approaches in ambient ionization techniques that enable direct analysis of complex samples without extensive preparation. His recent publications reveal a strong trend toward spatial metabolomics, particularly in traumatic brain injury and ovarian cancer research, with increasing integration of machine learning approaches for data analysis. His work also extends to pharmaceutical quality control, exercise physiology through the MoTrPAC consortium, and prebiotic chemistry investigations. The interdisciplinary nature of his research is evident in collaborations across Georgia Tech's campus and with external institutions. NSF CAREER Award (2007) 3M Non-tenured Faculty Award (2008) CETL/BP Junior Faculty Teaching Excellence Award (2009) Ron A. Hites Award for Outstanding Research Publication (2010) Sigma Xi (GT Chapter) Best Faculty Paper Award (2010) Vasser-Wooley Faculty Fellow (2012) Dr. Fernandez has secured significant funding for his research, including NSF CAREER support, and leads projects related to metabolomics for ovarian cancer detection, pharmaceutical forensics through the CODFIN network, and participation in the large-scale Molecular Transducers of Physical Activity Consortium (MoTrPAC). His laboratory develops advanced instrumentation for mass spectrometry applications and maintains strong collaborations with the Integrated Cancer Research Center, the College of Computing, and the Center for Chemical Evolution at Georgia Tech.

Xihong Linمشاهده پروفایل

استاد

• Statistical Machine Learning and AI
• Statistical Genetics and Genomics
• Causal Inference and Mediation Analysis
• +۴ مورد دیگر

Xihong Lin is a Professor of Statistics at Harvard University and a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health. She is a distinguished academic, holding membership in both the National Academy of Sciences and the National Academy of Medicine. Her research focuses on scalable statistical inference for big data, statistical machine learning, causal inference, and integrative data analysis, with applications in genomics, public health, and precision medicine. Lin’s work addresses challenges in analyzing large-scale genomic and multi-ancestry data, including methods for rare variant association testing, ancestry-adjusted sample analysis, and scalable computing frameworks. Her contributions span biobank studies (e.g., UK Biobank, TOPMed) and clinical applications in lung cancer, cardiovascular health, and smoking cessation. Her scientific awards reflect her leadership in statistical genetics and public health. Key research trends include leveraging single-cell sequencing for functional genomics, developing ensemble machine learning methods for health subtyping, and enhancing polygenic risk prediction across diverse populations. Lin’s methodologies prioritize interpretability and scalability, enabling impactful analyses of complex observational and genomic datasets. Awards: Member, National Academy of Sciences; Member, National Academy of Medicine Her grants and advising efforts focus on interdisciplinary collaborations, bridging statistics, AI, and domain sciences. Lin leads initiatives to improve genomic data management and ethical use of federated data (e.g., FADI framework). She is affiliated with labs advancing statistical genetics and cloud-based workflows (e.g., STAAR workflow).

H. (Han) Olffمشاهده پروفایل

استاد

• Ecology
• Biodiversity Conservation
• Environmental Sciences
• +۳ مورد دیگر

Prof. Han Olff is a Professor of Community and Conservation Ecology at the University of Groningen's Faculty of Science and Engineering, within the Groningen Institute for Evolutionary Life Sciences. He leads research on ecosystem structure, species interactions, and theoretical ecology, with fieldwork in savannas, salt marshes, and coastal systems. His work bridges theory and conservation, advising organizations like WWF and ARK Nature. Education: PhD (Cum Laude) in Biology from the University of Groningen (1992), MSc in Biology (1988). Research Interests: Focuses on plant-herbivore-predator interactions, ecosystem engineering, and the impact of human activities on biodiversity. Key themes include savanna ecology, food web dynamics, and restoration ecology. Awards: Gold Medal from Teyler Museum (2006) and PIONIER Award (2002). Active in grants like the EU Horizon 2020 AfricanBioServices project. Teaching: Coordinates courses in Conservation Biology, Ecological Research Skills, and Advanced Population Ecology. Leadership: Directed the Centre for Ecological and Evolutionary Studies (2011–2015) and chairs the National Research Agenda's 'Green Route'. Fieldwork: Organizes expeditions to the Serengeti-Mara, Banc d'Arguin, and Bijagos Archipelago to study human-wildlife interactions and ecosystem dynamics.

Owen Skinnerمشاهده پروفایل

استادیار

• Mass Spectrometry
• Proteomics
• Metabolomics
• +۶ مورد دیگر

Owen Skinner is an Assistant Professor in the Department of Chemistry and Chemical Biology at Northeastern University, affiliated with the Barnett Institute of Chemical and Biological Analysis. He leads the Skinner Lab, which specializes in high-resolution mass spectrometry to study protein-metabolite interactions in health and disease. Skinner earned his Ph.D. from Northwestern University and conducted postdoctoral research at Massachusetts General Hospital. His research focuses on thiol redox regulation, vitamin cofactor metabolism, and oxidative phosphorylation dynamics. Education: Ph.D. in Chemistry (Northwestern University), Postdoctoral Fellowship in Analytical Chemistry (Massachusetts General Hospital). Research interests include proteomics, metabolomics, mitochondrial dysfunction, and metabolic signaling. The lab actively recruits graduate students, undergraduates, and postdoctoral researchers across Northeastern's scientific community. Affiliations: Barnett Institute, College of Science Lab Members: PhD students Yifan Liu, Michael Xiao, Angela Rojas-Merchan; Undergraduates Helena Rittenhouse, Ridha Shah; High School collaborator Helen Loango Techniques: Native mass spectrometry, proteomics, metabolomics, redox biology Publications span mitochondrial metabolism, metabolic biomarkers in septic shock, and enzyme engineering. The lab emphasizes interdisciplinary collaboration and supports students through Northeastern's experiential learning programs.

Hugues Aschardمشاهده پروفایل

پژوهشگر

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

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

• Multiple stressors
• Environmental condition assessment
• Ecosystem services
• +۴ مورد دیگر

Dr. Sebastian Birk is an environmental scientist and researcher at the Aquatic Ecology department within the Faculty of Biology at the University of Duisburg-Essen. His work focuses on the science-policy interface for aquatic ecosystems in Europe, emphasizing large-scale bioassessment and management under multiple stressors. He served as coordinator for the EU project MARS (2014-2018) and currently manages freshwater science initiatives at the European Topic Centre for Inland, Coastal and Marine Waters (ETC-ICM) supporting the European Environment Agency (EEA). Research Interests : Multiple stressors, ecosystem services, restoration ecology, environmental policy assessment, bioassessment methods, and climate change impacts. Teaching : Scientific writing, surface water ecology, taxonomic identification, and fieldwork in river/lake systems. Recent publications highlight integrated frameworks for freshwater restoration, stressor interactions, and policy-driven water management. Key themes include agricultural land use effects on rivers, diversification of restoration funding, and challenges in harmonizing ecological assessment across Europe. His work bridges ecological theory with practical implementation for sustainable water resource management. Projects like MARS and MERLIN reflect his leadership in addressing complex environmental issues through collaborative science and stakeholder engagement. Dr. Birk's role in the Water Framework Directive intercalibration exercises underscores his technical expertise in standardizing ecological assessment across national borders.

Barbara Drosselمشاهده پروفایل

استاد

• Complex Systems Theory
• Theoretical Ecology
• Random Boolean Networks
• +۷ مورد دیگر

Barbara Drossel is a Full Professor at the Institute of Solid State Physics within the Faculty of Physics at the Technical University of Darmstadt, where she has been conducting research since February 2002. Her work bridges theoretical physics, complex systems theory, and theoretical ecology, focusing on interdisciplinary approaches to understanding emergent phenomena in natural systems. She leads the AG Drossel research group that investigates the theoretical foundations of complex networks, ecological communities, and quantum systems. Professor Drossel's research spans multiple domains with emphasis on complex systems theory, where she has made significant contributions to understanding random Boolean networks, food web modeling, and the physics of ecological communities. Her work demonstrates how simple rules can lead to complex emergent behavior across different scales, from quantum systems to ecological networks. She investigates how top-down causation operates in complex systems and explores the relationship between microscopic dynamics and macroscopic patterns in diverse contexts. Analysis of her recent publications reveals a consistent focus on theoretical frameworks that connect physics with ecology. Her work shows increasing integration of quantum mechanics with ecological modeling, particularly in understanding emergence and time evolution in complex systems. She frequently employs network theory to analyze ecological communities and has developed innovative approaches to studying species interactions, mutualistic networks, and spatial dynamics in meta-communities. Minerva Fellowship Heisenberg Fellowship DFG Fellowship for research at MIT Professor Drossel has supervised numerous doctoral students whose work spans theoretical ecology, complex systems, and statistical physics. Her research group has secured funding for projects examining the stability of ecological networks, quantum decoherence, and the mathematical foundations of complex systems. She maintains active collaborations with researchers across Europe and has contributed to major theoretical advances in understanding how complexity emerges from simple interactions in diverse systems. The AG Drossel research group operates at the intersection of physics and theoretical biology, maintaining strong connections with both the physics and biology departments at TU Darmstadt. The group combines mathematical rigor with biological relevance, developing models that capture essential features of complex natural systems while remaining analytically tractable. Their work has influenced both theoretical physics and ecological theory, demonstrating the power of interdisciplinary approaches to complex systems.

Romdhane Rekayaمشاهده پروفایل

استاد

• Animal Breeding and Genetics
• Quantitative Genetics
• Genomics
• +۴ مورد دیگر

Romdhane Rekaya serves as a Professor in the Department of Animal and Dairy Science within the College of Agricultural & Environmental Sciences at the University of Georgia. He also holds courtesy faculty positions in the Department of Statistics and is an associate faculty member with the Institute of Bioinformatics at UGA. His research program focuses on developing statistical and computational tools for analyzing large genetic and genomic datasets with applications in livestock, poultry, and human health. Dr. Rekaya's educational background includes: Agriculture Engineer from the High Institute of Agriculture, Tunisia Master of Science from the International Center for Advanced Studies in Mediterranean Agriculture of Zaragoza, Spain Ph.D. from the Polytechnic University of Madrid, Spain Dr. Rekaya's research interests span quantitative genetics, genomics, biostatistics, and bioinformatics. His work centers on developing statistical and computational methodologies for analyzing big genetic and genomic data sets with practical applications in livestock, poultry, and human health. His research has been particularly focused on addressing critical challenges in animal agriculture including horn fly resistance in beef cattle, water utilization efficiency in poultry, and greenhouse gas emissions in dairy production. His methodological approaches often integrate machine learning, Bayesian statistics, and genomic technologies to solve complex biological problems. Dr. Rekaya's publication record demonstrates a consistent focus on statistical methodology development for genetic analysis, with recent work increasingly emphasizing practical applications of genomic technologies in animal agriculture. His research spans both theoretical statistical development and practical implementation in livestock improvement programs, with particular emphasis on innovative approaches to traditional breeding challenges. Among his professional recognitions: Student Career Success Influencer Award 2024 Mini-Sabbatical Award Student Career Success Influencer Award 2022 Carnegie fellowship Carnegie African Diaspora Fellow Faculty with significant positive impact of at least one graduate student Gamma Sigma Delta outstanding Research Achievements Award Dr. Rekaya has successfully mentored numerous graduate students including PhD candidates Amanda Warner, Mahsa Zare, Koushik Das, and Evan Hartono, along with undergraduate researchers. His research has been consistently supported by major funding agencies including USDA NIFA, USDA ARS, Georgia Agricultural Commodity Commission for Beef, National Academy of Sciences, and industry partners including Tyson Foods and Cobb-Vantress. Current projects include developing genetic solutions to the horn fly problem in beef cattle, improving water utilization efficiency in poultry, and examining associations between greenhouse gas emissions and feed efficiency in dairy cattle. Dr. Rekaya leads an active research laboratory that collaborates with multiple departments and institutions. His lab focuses on applying advanced statistical and computational methods to solve pressing problems in animal agriculture, with particular emphasis on integrating genomic information into practical breeding programs. The lab maintains strong industry connections and international collaborations, particularly with researchers in Africa through the African Animal Breeding Network.