جست‌وجوی استاد و پژوهشگر

• Marketing
• Consumer Behavior
• Privacy Issues
• +۵ مورد دیگر

Dr. Joris Demmers is an Associate Professor and Head of the Marketing Department at the Faculty of Economics and Business , University of Amsterdam. His research focuses on consumer behavior, privacy in digital environments, environmental sustainability in marketing strategies, and the intersection of technology with consumer engagement. He leads academic initiatives in marketing while exploring interdisciplinary topics like corporate greenwashing detection and data governance. Key Research Themes: Consumer preferences for eco-labels and corporate social responsibility Privacy risks vs. behavioral incentives in financial and social media contexts Visual content analysis and machine learning applications in marketing Data-sharing dynamics and ethical marketing practices Recent Trends in Publications: Recent work emphasizes greenwashing detection (e.g., GreenScreen dataset), psychological drivers of financial self-disclosure, and the role of digital tools in customer journeys. Earlier studies delve into consumer data-sharing motivations and ethical privacy frameworks. Awards and Activities: No awards explicitly mentioned. Active in teaching and ancillary academic activities related to marketing strategy and digital media. Lab/Team Affiliations: No specific labs or teams listed, but collaborates across disciplines, including molecular biology studies on aging mechanisms (possibly through interdisciplinary projects).

Nigel Boschمشاهده پروفایل

استادیار

• Machine Learning
• Human-Computer Interaction
• Educational Technology
• +۳ مورد دیگر

Nigel Bosch is an Assistant Professor in the School of Information Sciences (iSchool) at the University of Illinois Urbana-Champaign, with a joint appointment in the Department of Educational Psychology. He is also a faculty affiliate at the National Center for Supercomputing Applications (NCSA) and Illinois Informatics. His primary research focuses on machine learning and human-computer interaction applications in education, with particular emphasis on affective computing, metacognition, and online learning environments. Bosch holds a PhD in Computer Science from the University of Notre Dame, followed by a postdoctoral research position at the National Center for Supercomputing Applications. His research explores machine learning applications in education, including automatic emotion measurement in programming education, metacognition analysis through natural language processing, and ethical implications of AI in learning. He also investigates wearable technologies for health monitoring and algorithmic bias mitigation in educational data. Bosch’s work is supported by grants from the National Science Foundation (NSF), the Institute of Education Sciences (IES), and the University of Illinois. He leads the (Human + Machine) Learning lab, which develops innovative technologies for educational analytics, AI ethics, and human-centered computing.

Lu Chengمشاهده پروفایل

استاد مهمان

• Genomics
• Bioinformatics
• Microbial Genetics
• +۳ مورد دیگر

Lu Cheng is a Visiting Professor in the Department of Computer Science at the University of Helsinki, affiliated with the Vehtari Aki Professorship. He holds a Doctor of Philosophy in Natural Sciences from the University of Helsinki (2013). His research focuses on computational genomics, bioinformatics, and microbial genetics, with emphasis on DNA sequence analysis, nanopore sequencing technologies, and systems biology. He leads projects on alternative splicing in cancer and the impact of microbiota on human health. Notable contributions include the NanoBaseLib benchmark dataset and methods for RNA modification analysis. His work addresses UN Sustainable Development Goals related to good health and innovations in data science. Education: Doctor of Philosophy in Natural Sciences (2013), University of Helsinki; Doctoral degree in Natural Sciences (2013), University of Helsinki. Research Interests: Genomics, computational biology, microbial ecology, RNA sequencing technologies, and bioinformatics tool development. His projects explore bacterial population dynamics, host-pathogen interactions, and applications of machine learning in genomics. Advising: Supervises doctoral researchers including Guangzhao Cheng and Chengbo Fu. Active in grants such as the Academy of Finland Research Fellowship (2023-2025). Labs/Teams: Leads research groups focused on single-cell genomics and computational methods for biological systems.

• Wildlife Health
• Aquatic Animal Health
• Exotic Animal Welfare
• +۶ مورد دیگر

Stéphane Lair is a Full Professor at the Faculty of Veterinary Medicine , University of Montreal , leading the Department of Clinical Sciences . He serves as Director of the Québec Center for Wildlife Health (CQSAS) and regional director for the Canadian Cooperative Wildlife Health Centre. His expertise focuses on wildlife health, aquatic animal medicine, and exotic species welfare. Education: IPSAV in Avian Pathology (1989) DVM from University of Montreal (1990) Residency in General Pathology (1995) DVSc in Zoo Animal Medicine (1998, University of Guelph) ACZM Diplomate (1999) His research investigates human impacts on wildlife health, including contaminant effects on marine mammals like belugas, and disease ecology in caribou and lemur populations. He leads projects funded by agencies like Fisheries and Oceans Canada and the American Association of Zoo Veterinarians. Recent work includes studying beluga body condition via 'omics techniques, toxin exposure in cetaceans, and pharmacokinetics in exotic species. Over 20 students have been supervised in topics ranging from beluga necropsy trends to analgesia in pigeons. Collaborations include the Nunavik Trichinellosis Prevention Program and studies on Besnoitia tarandi in caribou. His lab actively addresses wildlife health challenges in changing ecosystems, emphasizing conservation and veterinary medicine intersections.

Daniel Edlerمشاهده پروفایل

پژوهشگر

• Network Science
• Biodiversity
• Ecological Modeling
• +۳ مورد دیگر

Daniel Edler is a Researcher and Postdoctoral Fellow at the Department of Physics, Umeå University. His work focuses on network science, biodiversity analysis, and ecological modeling, with a particular emphasis on developing computational tools for community detection and biogeographical mapping. He contributes to interdisciplinary research, integrating methods from computer science, ecology, and information theory. Edler leads the development of Infomap Bioregions, a tool for mapping biogeographical regions using species distribution data, and CoordinateCleaner, which standardizes biological occurrence records. His research also explores threats to Madagascar’s biodiversity and the interplay between socio-political factors and biodiversity data availability through tools like Bio-Dem. He has co-developed raxmlGUI 2.0, a phylogenetic analysis interface, and contributes to the Infomap software package for network analysis. Edler’s publications highlight themes in higher-order network flows, multilayer community detection, and ecological network modules. His work appears in journals such as Science , American Journal of Botany , and Methods in Ecology and Evolution . He is an active member of the Complex Systems research group at Umeå University.

Fabio Lucianiمشاهده پروفایل

استاد

• genomics
• immunology
• computational biology
• +۶ مورد دیگر

Fabio Luciani is a Professor in Systems Immunology and Machine Learning at the School of Medical Sciences at UNSW Sydney, with visiting fellow positions at the Garvan Institute for Medical Research and Weill Cornell College of Medicine NY, USA. His interdisciplinary research program integrates immunology, genomics, and computational approaches to develop novel immunotherapies for cancer and autoimmune diseases. With a background spanning physics, theoretical biology, and biophysics, Luciani leads an interdisciplinary team with expertise in immunology, mathematical modeling, statistics, and bioinformatics. His research focuses on T cell responses using single-cell genomic technologies to understand immune responses in viral infections, autoimmunity, and CAR T cell therapies. He has developed landmark bioinformatic methods for combining single-cell transcriptome data with antigen receptor sequences and computational models for haplotype reconstruction. Luciani's work demonstrates a strong emphasis on translating molecular and genomic discoveries into clinical interventions, particularly in predicting side effects and identifying solutions for unmet clinical needs in immunotherapy. His research spans multiple collaborative projects including single-cell multi-omics analysis in coeliac disease with Prof Chris Goodnow's team at the Garvan Institute, and CAR T cell therapy response studies with clinicians at Westmead Hospital and Weill Cornell. His scientific contributions include over 140 peer-reviewed publications and successful acquisition of more than $20 million in research funding from organizations including ARC, NHMRC, JDRF, NIH, and private industry partners. He serves as Principal Investigator of the UNSW Future Institute of Cellular Genomics, which has secured $4.5 million over seven years for single-cell technologies in cellular genomics. As an academic supervisor, Luciani currently mentors 3 PhD students, 2 honours students, and 2 postdoctoral researchers, welcoming applications from students interested in bioinformatics, statistics, data science, immunology, and genomics. His work bridges theoretical approaches with experimental immunology to advance precision medicine and transform current immunotherapies into more precise and accessible solutions.

Manuela Truebanoمشاهده پروفایل

مدرس

• Marine Molecular Biology
• Ecophysiology
• Climate Change Adaptation
• +۳ مورد دیگر

Dr Manuela Truebano is a Lecturer in Marine Molecular Biology at the University of Plymouth, affiliated with the School of Biological and Marine Sciences (part of the Faculty of Science and Engineering). She holds a BSc in Marine Biology from the University of Liverpool, an MSc in Shellfish Biology from Bangor University, and a PhD in Molecular Ecophysiology (focusing on thermal stress) from Swansea University and the British Antarctic Survey. Her research group is part of the Ecophysiology and Development Research group within the Marine Biology and Ecology Research Centre. Her teaching portfolio includes module leadership roles in Marine Molecular Biology, Ecophysiology of Marine Animals, Conservation Physiology, and field courses. She has supervised two postgraduate research degrees: Michael Collins (PhD, 2019) and George Mason (ResM, 2021). Dr Truebano’s research focuses on thermal tolerance, hypoxia, and environmental stress responses in marine organisms, particularly invertebrates. She employs molecular and physiological approaches to study climate change impacts, including the development of tools like Dev-ResNet and HeartCV for automated phenotyping. Her work intersects with global sustainability goals, emphasizing organismal resilience to environmental shifts. Her recent publications highlight advancements in understanding transgenerational plasticity, thermal acclimation, and the interplay of multiple stressors. Teaching and learning grants include a 2015 initiative exploring video tutorials for lab skill training. She collaborates extensively in interdisciplinary projects, contributing to both academic and applied marine science.

• Biostatistics
• Oncology
• Hematology
• +۳ مورد دیگر

Andrea M. Baran, M.S. serves as a Senior Associate (Part-Time) in the Department of Biostatistics and Computational Biology at the University of Rochester School of Medicine and Dentistry. With expertise spanning biostatistics, oncology, and infectious diseases, she contributes significantly to clinical research across multiple medical disciplines through rigorous statistical analysis and methodological innovation. Her educational background includes: MS in Medical Statistics from University of Rochester School of Medicine & Dentistry (2009) BS in Cell Biology, Cytology from University of Rochester (2008) BA in Statistics from University of Rochester (2008) Ms. Baran's research focuses on biostatistical methodology applied to clinical medicine , with particular emphasis on oncology, hematology, and infectious disease applications. Her work bridges statistical theory with clinical practice, developing analytical approaches for complex medical data including gene expression patterns, clinical trial outcomes, and disease progression models. She has made significant contributions to studies examining miRNA analysis, clinical trial design, and biomarker development. Analysis of her recent publication record reveals a strong concentration on hematologic malignancies, particularly chronic lymphocytic leukemia and lymphoma, where she applies sophisticated statistical models to evaluate treatment efficacy, resistance mechanisms, and patient outcomes. Her work also extends to infectious disease research, where she develops statistical approaches for understanding host immune responses to respiratory viruses and other pathogens. While specific awards are not mentioned in available records, her extensive publication history in high-impact journals including Journal of Infectious Diseases , Blood Advances , and Genome Biology demonstrates significant recognition within her fields of expertise. Ms. Baran collaborates extensively with clinical researchers across the University of Rochester Medical Center, providing biostatistical leadership for numerous clinical trials and observational studies. Her work supports research initiatives in oncology, hematology, infectious diseases, and geriatric care, contributing to evidence-based medical practice through rigorous statistical analysis and interpretation of complex datasets. She is actively involved in multiple research teams studying hematologic malignancies, infectious diseases, and clinical trial methodology, where her biostatistical expertise helps shape research design, data collection protocols, and interpretation of findings for clinical application.

Jean Fanمشاهده پروفایل

استادیار

• Single-cell omics
• Spatial omics
• Computational biology
• +۳ مورد دیگر

Jean Fan, PhD is an Assistant Professor of Biomedical Engineering at Johns Hopkins University, affiliated with the Center for Computational Biology and Institute for Computational Medicine. Her research focuses on developing machine learning methods to analyze spatially resolved and single-cell omics data. Her team, the JEFworks Lab, creates open-source tools for analyzing high-dimensional biological data to understand cellular identity, tissue organization, and disease progression. Dr. Fan's work bridges computational biology with clinical applications, particularly in leukemia and pediatric brain cancers. Education: BS in Biomedical Engineering & Applied Math from Johns Hopkins (2013); PhD in Bioinformatics from Harvard Medical School (2018); Postdoc in Chemical Biology/Physics at Harvard (2018–2020) under Xiaowei Zhuang, focusing on spatial transcriptomics. Research emphasizes spatial genomics and computational tool development, with key contributions to spatial alignment algorithms (STalign), normalization techniques, and cell-type deconvolution methods. Her lab's work has advanced understanding of kidney ischemic injury, glioblastoma spatial dynamics, and CLL pathogenesis. Awards include Forbes 30 Under 30, NSF CAREER Award, and 2025 PECASE. She founded CuSTEMized, a nonprofit providing STEM storybooks for girls. Recent collaborative projects include HuBMAP 3D reference atlas construction and Discovery Award-funded interdisciplinary initiatives. Labs/Teams: JEFworks Lab (primary); active collaborations with Dana-Farber Cancer Institute and Harvard Medical School. Current efforts focus on spatially resolved multi-omic integration and clinical translation of computational tools.

Silvia Rondonمشاهده پروفایل

استاد

• Integrated Pest Management
• Insect-Plant Interactions
• Biological Control
• +۲ مورد دیگر

Silvia Rondon is a Professor and Director of the Integrated Pest Management Center at Oregon State University (OSU), affiliated with the College of Agriculture and Department of Crop & Soil Science. She moved to OSU's Corvallis campus in September 2022 after extensive work in eastern Oregon. Education: PhD in Crop Sciences (2002), MS in Entomology (1999), BA in Biology/Zoology (1993) from Universidad Nacional Agraria La Molina (Peru) and University of Illinois. Research Focus: Ecological-based Integrated Pest Management for irrigated crops (potatoes, onions, corn, wheat) emphasizing insect ecology, biological/chemical control, and pest population dynamics. Her publications span potato psyllid management, zebra chip disease, wireworm genomics, and landscape-driven pest movement. Key awards include the Erasmus Teaching Award, Pacific Branch ESA Excellence in Extension, and multiple NACAA/OSU honors. She leads extension programs through on-farm demonstrations and train-the-trainer workshops, while mentoring graduate students in IPM research.

Raul A. Urrutiaمشاهده پروفایل

استاد

• Genomics
• Epigenomics
• Precision Medicine
• +۴ مورد دیگر

Raul A. Urrutia, MD is a Professor in the Department of Surgery & Biochemistry and the Director of the Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine at the Medical College of Wisconsin. He holds the Warren P. Knowles Endowed Chair of Genomics and Precision Medicine and directs the Pancreas Cancer Program. His research focuses on genomics, epigenomics, and precision medicine, particularly in pancreatic diseases such as cancer and diabetes. He has discovered key tumor suppressor genes and epigenetic pathways operational in pancreatic cancer and other diseases. His lab employs a multidisciplinary team of biochemists, geneticists, and bioinformaticians to advance precision medicine. Education: MD, University of Cordoba Postdoctoral Fellowship, National Institute on Deafness and Other Communication Disorders, NIH Research Interests: Dr. Urrutia’s work integrates genomic and epigenomic approaches to uncover mechanisms underlying pancreatic cancer, diabetes, and other diseases. His lab has made seminal contributions to understanding KLF proteins, histone-modifying enzymes (HDACs, HATs, HMTs), and histone-protein subcodes. Recent studies focus on epigenetic regulators in cancer progression and therapy resistance, mitochondrial genomic variants in transplantation outcomes, and precision medicine simulation models. Publications Trends: Recent articles emphasize targeting epigenetic regulators (e.g., CBX5, EZH2), mitochondrial genomics in hematopoietic transplantation, and systems biology approaches combining germline/somatic mutations for tumor analysis. The work spans disciplines from molecular biology to clinical translation. Awards: Warren P. Knowles Endowed Chair Member, American Society of Clinical Investigation Advising & Grants: Dr. Urrutia has mentored over 50 investigators. His lab is funded by NCI grants, the CIBMTR Data Resource (U24), and philanthropic support like the Theodore W. Batterman Family Foundation. Research units include the Precision Medicine Simulation Unit and collaborations with global institutions. Labs & Teams: Leads the Urrutia Research Laboratory and the Mellowes Center, collaborating with experts in epigenetics, computational biology, and clinical genomics. Key lab members include Angela J. Mathison, PhD (Technology Director) and Gareth Pollin, PhD (Bioinformatics).

Roman Matuszewskiمشاهده پروفایل

دانشیار

• Automated Reasoning
• Formalized Mathematics
• Computer Science
• +۳ مورد دیگر

Roman Matuszewski is a retired Associate Professor at the University of Bialystok, affiliated with the Faculty of Philology's Department of Applied Linguistics. His research focuses on automated reasoning, formalized mathematics, and the Mizar Project, which he has been involved with since its inception in 1973. He holds a PhD in Computer Science from Shinshu University (2000) and has held academic positions at multiple institutions, including part-time roles at Bogdan Janski University. Education: PhD in Computer Science (2000), Master of Science in Mechanics (1975), Engineer (1973), all from Polish institutions. His work emphasizes formal proof systems, mathematical knowledge management, and education integration of automated reasoning tools. Research interests include automated deduction, formal proof verification, and the application of these methods to mathematics education. His contributions to the Mizar Mathematical Library and its 50-year history (celebrated in 2023) are foundational for interactive theorem proving. Key awards include the Silver Cross of Merit (2004) and multiple Rector’s prizes. He has organized major conferences like MKM2004 and served on program committees for events such as IJCAR and Tableaux. Grants include leadership roles in EU-funded projects like TYPES and CALCULEMUS. His work bridges computer science and mathematics through formalized systems, impacting both research and education.

• Gene Editing
• CRISPR Technology
• Genetic Engineering
• +۵ مورد دیگر

Scot Wolfe is a Professor at UMass Chan Medical School, affiliated with the Department of Molecular, Cell and Cancer Biology. He holds multiple academic roles across institutions including T.H. Chan School of Medicine and Morningside Graduate School of Biomedical Sciences. His research focuses on engineering CRISPR-Cas9 systems for gene therapy, targeting diseases like sickle cell anemia and muscular dystrophy. Wolfe's work emphasizes precision genome editing, delivery systems, and applications in hematopoietic stem cell therapy. Collaborations include projects on HIV latency, zebrafish genomics, and Neurofibromin gene therapy. His lab (wolfe-lab.org) innovates tools like Cas9-ZFP fusions and delivery methods for clinical applications. Education: B.S. from Caltech (1990), Ph.D. from Harvard (1996). Postdoc at MIT. Research spans protein-DNA recognition, zinc finger engineering, and transcription factor specificity. Over 150+ publications focus on gene editing mechanisms and therapeutic applications. Active in the NIH Somatic Cell Genome Editing program. Key projects include enhancing CRISPR specificity, ex vivo editing of HSPCs, and combating genetic disorders via base editing and prime editing. His team develops therapies for beta-hemoglobinopathies, limb-girdle muscular dystrophy, and Hermansky-Pudlak Syndrome. Ongoing work explores HIV cure strategies through proviral inactivation.

Ming Yuanمشاهده پروفایل

استاد

• High-dimensional statistics
• Machine learning
• Tensor methods
• +۴ مورد دیگر

Ming Yuan is a Professor in the Department of Statistics at Columbia University and serves as Associate Director of the Data Science Institute. His research focuses on high-dimensional statistics, machine learning, and statistical methodology with applications in genomics, finance, and imaging. Yuan holds a Ph.D. in Statistics from the University of Wisconsin-Madison (2004) and a B.S. in Electrical Engineering from the University of Science and Technology of China (1997). Education: 2004 Ph.D., Statistics, University of Wisconsin-Madison 2003 M.S., Computer Science, University of Wisconsin-Madison 2000 M.S., Probability and Statistics, University of Science and Technology of China 1997 B.S., Electrical Engineering, University of Science and Technology of China Research Interests: Dr. Yuan’s work bridges theoretical and applied statistics, emphasizing scalable methods for high-dimensional data. Key areas include tensor decomposition, covariance estimation, and statistical machine learning. His contributions to methods like sparse inverse covariance estimation and matrix/tensor completion have found applications in finance, genomics, and image analysis. Publications: His recent work explores tensor-based methods for high-dimensional analysis and develops optimal algorithms for compressed sensing. Articles often address statistical theory and computational challenges in modern data science, reflecting a balance between foundational and applied research. Awards: 2025 JASA Theory & Method Invited Discussion Paper 2024 William F. Sharpe Award (JFQA) 2018 Medallion Lecturer (Institute of Mathematical Statistics) 2014 Guy Medal in Bronze (Royal Statistical Society) 2007 Leo Breiman Junior Award Professional Activities: Yuan has served as Co-Editor of The Annals of Statistics (2019–2021) and Program Secretary for the Institute of Mathematical Statistics (2018–2021). His work integrates interdisciplinary collaborations, particularly in biomedical imaging and financial econometrics.

• Pattern Analysis
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Richard Charles Wilson is a Professor of Pattern Analysis in the Department of Computer Science at the University of York, where he leads the Artificial Intelligence research group and serves on the Departmental Research Committee. His work bridges theoretical and applied aspects of machine learning and computer vision, with a focus on structural pattern recognition using graphs and networks. Research Interests: His research spans Pattern Analysis , Machine Learning , Computer Vision , and Graph-based Pattern Recognition . He applies these to diverse domains including bioinformatics, navigation systems, and neural network design. His recent work explores deep learning without backpropagation, GNSS interference detection, and AI in drug discovery. The most recent publications reflect a strong trend in applying AI to real-world challenges in healthcare and signal integrity, combining deep learning with novel architectures and semi-supervised techniques. His work often appears in high-impact journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics and The Journal of Navigation. Scientific Awards: IAPR Fellow Award (2010) Wilson actively contributes to academic service, including PhD examination, editorial board membership for Pattern Recognition , and research evaluation for institutions like the Czech Academy of Sciences. He has led and contributed to multiple funded research projects, including those supported by EPSRC and The Royal Society. His leadership in the UKRI AI Centre for Doctoral Training in Safe AI Systems highlights his role in training the next generation of AI researchers. He is involved in significant research projects such as the Graphical Modeling of Brain project funded by The Royal Society and the UKRI AI Centre for Doctoral Training in Safe AI Systems (SAINTS) , where he serves as a co-investigator. These projects emphasize safe, interpretable, and biologically inspired AI systems.