جست‌وجوی استاد و پژوهشگر

• Genomics
• Genetics
• Animal Breeding
• +۳ مورد دیگر

Hendrik-Jan Megens is an Assistant Professor in Animal Breeding and Genetics at Wageningen University & Research (WUR), Netherlands, affiliated with the Wageningen Institute for Advanced Studies (WIAS). His dr.ir. title reflects a Dutch engineering doctorate, and he maintains an active research profile with over 200 publications and 51 datasets. His work integrates genomic analysis with conservation and aquaculture applications across vertebrate species. Research interests focus on: Genomic consequences of inbreeding in fragmented populations Environmental adaptation mechanisms in aquaculture species Structural variants in chromosome evolution Functional annotation of deleterious mutations Epigenetic regulation in reproductive transitions Genotype-environment interactions in growth traits Recent publications (2023-2025) reveal dual expertise in wildlife conservation (European wild boar, sharks) and aquaculture genomics (tilapia, seabream, oysters). Key trends include application of long-read sequencing (Pore-C) for structural variant detection, pCADD-based prioritization of causal mutations, and investigation of polyploidy effects in teleost fish. His work bridges fundamental evolutionary questions with practical breeding challenges. Megens has co-supervised 12 research projects including five PhD candidates: S. Ousley: Super corals project (reef restoration genomics) G. Kuguru: Black tipped reef shark diversity (Maldives) A. Blasweiler: AquaFAANG (fish health immunology) X. Yu: Nile tilapia adaptation architecture H. van Kruistum: Livebearing fish reproductive genomics He leads projects on genomic tools development (pCADD) and contributes to international consortia like the European Reference Genome Atlas. His team collaborates across WUR's Animal Breeding and Genetics group, focusing on translating genomic findings into conservation strategies and sustainable aquaculture practices through field studies and computational pipelines.

Lan Wangمشاهده پروفایل

استاد

• Internet Architecture
• Network Security
• Wireless Sensor Networks
• +۷ مورد دیگر

Lan Wang is a Professor in the Department of Computer Science at the University of Memphis, temporarily assigned as a Program Director at the NSF. She holds a PhD in Computer Science from UCLA (2004). Her research focuses on Internet architecture, network security, and wireless sensor networks, with major grants from NSF, NIST, and DoD, including a $15M NSF-funded 'Named Data Networking' project. She has served as Department Chair (2016-2023) and is an IEEE Senior Member. Dr. Wang's research emphasizes scalable, reliable, and secure Internet infrastructure. She has pioneered advancements in named-data networking (NDN), including protocols for adaptive forwarding, secure access control, and efficient traffic management. Her work extends to applications in smart cities, public safety, and healthcare data sharing. She has received prestigious awards including the Willard R. Sparks Eminent Faculty Award (2022) and Dunavant Professorship (2021). Her teaching spans courses like Networking and Information Assurance, Advanced Computer Networks, and Wireless and Mobile Computing. She actively promotes gender diversity in CS, co-organizing events like the 'Networking Networking Women' panel at SIGCOMM. Her grants total over $15M, including NSF’s NDN project and university-funded initiatives. She advises the Women in Computing student chapter and has served on over 50 conference committees.

• Research Integrity
• Scientific Misconduct
• Meta-Research
• +۳ مورد دیگر

Daniele Fanelli is an Assistant Professor in the School of Social Sciences at Heriot-Watt University, United Kingdom. He holds a PhD and is currently a Fellow at the London School of Economics and Political Science (26 Apr 2023 – 1 May 2026). His work contributes to UN Sustainable Development Goals, though specific goals are not detailed here. In terms of education, he has received several competitive fellowships including the Marie Curie Intra-European fellowship (2008) and Leverhulme Early-Career Fellowship (2010). His research focuses on meta-research, scientific integrity, and publication practices, with a particular interest in quantifying knowledge, assessing retractions’ epistemic impact, and analyzing predictors of misconduct. He has also explored the hierarchy of sciences and the unintended consequences of academic metrics. His scientific achievements include receiving the LSE Excellence in Education Award (2021). Recent activities highlight his engagement in talks about reproducibility, research integrity, and metascience, including an invited talk in 2025 titled 'Research integrity in context'.

• Evolutionary Genetics
• Indirect Genetic Effects (IGE)
• Parental Care in Beetles
• +۴ مورد دیگر

Kyle Benowitz is an Assistant Professor at Arizona State University's School of Applied Sciences and Arts. His research focuses on evolutionary genetics, particularly how social interactions influence evolution through indirect genetic effects (IGE). He uses burying beetles as a primary model organism to study genes associated with parental care and their evolutionary dynamics. Benowitz also collaborates on projects related to multilevel selection, insecticide resistance, and complex trait genetics in desert-adapted flies. Education: Ph.D. in Genetics, University of Georgia, 2017 B.A. in Biology, University of Virginia, 2012 Research Interests: Genomic and behavioral mechanisms of IGE Evolution of parental care in burying beetles Insecticide resistance in agricultural pests Genetic basis of social behavior transitions Recent work highlights trends in genomic analysis of burying beetles, comparative genomics of Drosophila species, and studies on Bt crop resistance. His lab combines behavioral studies with quantitative and population genomic approaches. Benowitz teaches courses in genetics and applied biological sciences at ASU. His research has been supported by grants focusing on IGE detection and evolutionary genomics.

• Software Engineering
• Developer Productivity
• IDE Interaction Analysis
• +۳ مورد دیگر

Andrea Mocci is a Lecturer at the Faculty of Informatics of the Università della Svizzera italiana (USI). His work focuses on software engineering methodologies, developer productivity, and IDE interaction analysis. He is affiliated with the Software Institute and actively contributes to academic events such as the IEEE International Workshop on Mining and Analyzing Interaction Histories (MAINT). His research explores empirical software engineering techniques, including developer behavior analysis, code documentation improvement, and the application of natural language processing to software artifacts. Key areas of investigation include: IDE interaction and navigation efficiency Code redundancy and quality metrics Video tutorial analysis for educational content Runtime systems and annotation APIs Defect prediction and software maintenance Publications from 2016-2020 highlight trends in developer-centric tools, holistic recommender systems, and visualization techniques for software evolution. His work often bridges theoretical formal methods with practical developer workflows, aiming to improve both software quality and developer productivity through empirical studies and tool development.

Gregory Gayمشاهده پروفایل

دانشیار

• Software Testing
• Search-Based Software Engineering
• AI for Software Engineering
• +۴ مورد دیگر

Gregory Gay is an Associate Professor in the Interaction Design and Software Engineering division within the Department of Computer Science and Engineering at Chalmers University of Technology and the University of Gothenburg, Sweden. His academic profile spans numerous software engineering conferences where he has served as committee member, program chair, and active researcher since at least 2018. Dr. Gay's research focuses on the intersection of software engineering and artificial intelligence, with particular emphasis on: Software Testing and Analysis Search-Based Software Engineering AI for Software Engineering (AI4SE) AI Engineering Automation of development tasks Software Carbon Footprint and sustainability His recent publications demonstrate a strong trend toward applying AI and optimization techniques to software testing challenges, with increasing focus on sustainability aspects of software development. Many studies take an industrial perspective, examining real-world applications in automotive software systems. His work blends theoretical foundations with practical applications, making significant contributions to both academic research and industrial practice in software engineering. Dr. Gay has been actively involved in numerous top software engineering conferences including ASE, ICSE, ESEC/FSE, ISSTA, and ICST, serving on program committees and organizing tracks. His research methodology typically combines optimization, artificial intelligence, and machine learning to help developers deliver complex systems in a safe, secure, and efficient manner.

Haipeng Caiمشاهده پروفایل

دانشیار

• Software Engineering
• Program Analysis
• Software Security
• +۵ مورد دیگر

Haipeng Cai serves as an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. His academic work spans software engineering, program analysis, and software security with particular emphasis on adaptive analysis techniques for mobile and distributed systems. His research interests center on adaptive/data-driven static and dynamic analysis for security applications targeting mobile apps, distributed systems, and multilingual software. Current work focuses on enhancing vulnerability detection, cross-language bug analysis, and automated security tooling through machine learning approaches. His lab produces tools like VinJ for vulnerability data generation and PolyFax for multilingual software characterization. Recent publications reveal strong trends in multilingual system security and AI-enhanced analysis , with 15+ papers since 2022 addressing cross-language vulnerabilities, Android security, and learning-based vulnerability detection. His work bridges theoretical program analysis with practical security applications in real-world software ecosystems. As an active academic contributor, he serves on program committees for major conferences including ASE, ICSE, and FSE, and will deliver a keynote at PROMISE 2025. His leadership includes journal-first paper chair roles and session chair positions at top software engineering venues. Dr. Cai maintains an active research presence through his personal website , GitHub repository ( github.com/chapering ), and academic social media profiles, with consistent contributions to the software engineering research community since 2018.

Guy Jacobsمشاهده پروفایل

پژوهشگر ارشد

• Evolutionary genetics
• Population genetics
• Human evolutionary biology
• +۱۲ مورد دیگر

Guy Jacobs is a Research Fellow at the University of Cambridge, Department of Archaeology, specializing in evolutionary genetics and microbiome ecology. His work combines large-scale genomic datasets with computational modeling to investigate human evolutionary history, archaic hominin interactions, and microbiome dynamics during subsistence transitions in traditionally hunter-gatherer communities across India and Indonesia. Primary focus on population genetics, human adaptation, and social network impacts Expertise in computational modeling of evolutionary processes Collaborations with C-CLEAR DTP and CREATES partnerships Research spans ancient DNA analysis, archaic introgression patterns, and the interplay between genetic ancestry, environment, and health outcomes. Key projects include studies of Denisovan ancestry in Island Southeast Asia, microbiome differentiation in lifestyle transitions, and sociocultural influences on genetic diversity. Recent publications highlight trends in human adaptation to malaria and high-altitude environments, microbiome evolution during urbanization, and computational methods for detecting selective sweeps. His work integrates genomic data with social and environmental variables to address questions in biological diversity and human phenotypic variation. As part of the Cambridge NERC Doctoral Landscape Awards, he supervises students on topics ranging from archaic introgression analysis to genetic disease mapping. He utilizes datasets from Indonesia, India, and the Indonesian archipelago, combining genetic, transcriptomic, and mobility data in his research.

• RNA Therapeutics
• Oligonucleotide Drug Development
• Neurodegenerative Diseases
• +۳ مورد دیگر

Anastasia Khvorova is a Professor and Remondi Family Chair in Biomedical Research at UMass Chan Medical School, holding primary appointments in the RNA Therapeutics Institute within the T.H. Chan School of Medicine. She maintains extensive cross-appointments across the Morningside Graduate School of Biomedical Sciences in departments including Biochemistry and Molecular Biotechnology, Neuroscience, and the RNA Therapeutics and Biology Program. Education: BS in Biology, Moscow State University MS in Molecular Biology, Moscow State University PhD in Biochemistry, Russian Academy of Sciences Professor Khvorova's research focuses on RNA therapeutics development , specializing in oligonucleotide chemistry, siRNA design, and delivery systems for neurological and genetic disorders. Her laboratory pioneers chemically modified self-delivering RNAi compounds targeting Huntington's disease, ALS, and Alzheimer's, with emphasis on overcoming delivery barriers through novel backbone chemistries and conjugate strategies. Current work explores divalent siRNA scaffolds for enhanced CNS penetration and multi-gene modulation. Analysis of her 15 most recent publications reveals dominant themes in siRNA chemical optimization (backbone/ribose modifications), neurological disease targeting (Huntington's, ALS, MECP2 disorders), and delivery innovation (extended nucleic acid backbones, albumin-binding constructs). Key advances include preventing oligonucleotide neurotoxicity via cation formulation and achieving single-dose therapeutic effects in mouse models. Awards and recognition: Rosalind Franklin Society Award for Nucleic Acid Therapeutics (2023) Remondi Family Chair in Biomedical Research Her laboratory actively recruits postdoctoral fellows for projects in RNAi preclinical development, medicinal chemistry, and small RNA trafficking, collaborating with Victor Ambros, Silvia Corvera, and UMASS imaging groups. Current grants support work on Huntington's disease somatic instability, SOD1 silencing for ALS, and MECP2-targeted therapies. The lab emphasizes interdisciplinary training in nucleic acid chemistry, pharmacology, and preclinical development. Professor Khvorova leads a dynamic research team within the RNA Therapeutics Institute, utilizing advanced imaging, mass spectrometry, and in vivo modeling to develop next-generation oligonucleotide therapeutics. Her work bridges fundamental RNA biology with translational applications, particularly for orphan neurological indications with unmet therapeutic needs.

Shigang Chenمشاهده پروفایل

استاد

• Computer Networks
• Data Streaming
• Internet of Things
• +۴ مورد دیگر

Shigang Chen is a Professor in the Department of Computer & Information Science & Engineering at the University of Florida. His research focuses on intelligent computer networks, data streaming, RFID systems, IoT, and cyber-physical network security. B.S., University of Science and Technology of China (1993) M.S. and Ph.D., University of Illinois at Urbana-Champaign (1996, 1999) Research interests span network traffic measurement, RFID authentication, cyber-physical systems, and privacy-preserving protocols. His work addresses high-speed network monitoring, edge computing, and scalable IoT frameworks. Recent publications emphasize real-time spread estimation, compact data structures, and privacy in vehicular systems. Awards include IEEE Fellow, NSF CAREER, and multiple best paper recognitions. Advised: 12 PhD students, 5 Master's, 1 undergraduate Honors: IEEE Fellow (2016), ACM Distinguished Scientist (2017), University of Florida Term Professorship (2017-2020)

Dieter De Witteمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Science
• FAIR Data
• +۳ مورد دیگر

Prof. Dieter De Witte serves as a Professor at Ghent University, dedicating 50% of his time to the Internet Technology and Data Science Lab (IDLab) while simultaneously contributing 50% to the Royal Museums of Fine Arts Belgium (RMFAB) in Brussels through a FED-tWIN mandate from Belspo. At RMFAB, he spearheads the strategic overhaul of digital infrastructure toward FAIR-compliant and data-driven systems, while at Ghent University he collaborates with Prof. Steven Verstockt on applied AI projects across heritage, mental healthcare, and education domains. His academic foundation includes a Master's in Engineering Physics from Ghent University (2008) followed by doctoral research on Big Data technologies and FAIR data for life sciences. Prior to returning to academia in 2021, he gained industry experience as an AI consultant and team lead at Telenet and Ordina. De Witte's research centers on AI-driven transformation of cultural heritage through FAIR data publication , collection enrichment , and intuitive querying interfaces . His technical expertise spans multimodal algorithms, image segmentation, pose estimation, large language models (LLMs), and semantic technologies including SPARQL and IIIF. Current projects focus on human-in-the-loop AI systems that combine diverse AI building blocks for practical heritage applications. Analysis of his 15 most recent publications reveals a clear trajectory from early bioinformatics work (2007-2018) on genomic motif discovery and life sciences data infrastructure toward contemporary cultural heritage applications (2023-2024). Recent outputs demonstrate innovative fusion of pose estimation, linked data frameworks, and multimodal AI for museum contexts, highlighting increasing specialization in AI enrichment of digital collections while maintaining core expertise in FAIR data principles. His FED-tWIN grant enables critical knowledge transfer between academic research and cultural heritage institutions, supporting development of next-generation digital infrastructure at RMFAB. Current projects involve creating AI tools for intuitive collection exploration and systematic enrichment of heritage assets through advanced computational methods. De Witte operates within Ghent University's Internet Technology and Data Science Lab (IDLab), participating in interdisciplinary teams developing applied AI solutions. His work bridges technical innovation with practical implementation in cultural institutions, focusing on sustainable, interoperable systems that enhance public access to digital heritage collections through cutting-edge AI interaction paradigms.

Mathias Klierمشاهده پروفایل

استاد

• Big Data Analytics
• Data Quality
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Mathias Klier holds the Péter Horváth Endowed Professorship for Business Administration with a Focus on Business Information Management at the University of Ulm's Department of Business Analytics. His research focuses on big data analytics, data quality, AI explainability, and social impact of information systems. Klier has held previous academic roles at the Universities of Augsburg, Innsbruck, and Regensburg, where he contributed to data quality metrics and enterprise systems research. He has authored over 100 peer-reviewed articles in journals like MIS Quarterly and Decision Support Systems, and serves as a track chair for ICIS and ECIS conferences. Education: PhD in Business Administration (2008), University of Augsburg (Dissertation: 'Designing Customer-Centric Information Systems') MSc in Business Mathematics (2005), University of Augsburg Research Interests: Klier’s work bridges technical data quality challenges with societal impacts. Key themes include probabilistic metrics for data currency/consistency, ethical AI design, and leveraging peer networks for unemployment support. His recent projects apply explainable AI to public services and workforce development. Key Achievements: Recipient of Research Prize of the Swabian Economy (2008) Winner of Vodafone Foundation Award (2005) Awarded Ciborra Award (2018) for innovative research on event-driven duplicate detection Advising & Grants: Klier’s team has secured funding for projects on future skills forecasting and refugee integration via digital peer groups. He advises on AI literacy initiatives in K-12 education and collaborates with industry partners like German car manufacturers. Labs/Teams: Leads the Business Analytics Institute at Ulm, focusing on data-driven decision making and AI ethics. Active in interdisciplinary research networks including the German Information Quality Management Initiative.

Hadi Işık Aybayمشاهده پروفایل

استاد

• Computer Engineering
• Neural Networks
• Distributed Systems
• +۴ مورد دیگر

Prof. Dr. Hadi Işık Aybay is a distinguished Professor of Computer Engineering at Eastern Mediterranean University (EMU), North Cyprus. He has held academic roles including Department Chairman of Computer Engineering (1994–2004 and 2013–present) and Director of EMU's Distance Education Institute (2000–2013). He earned his PhD in Electrical and Electronic Engineering from METU (1989) and served as an Assistant/Associate Professor before becoming a full Professor in 2013. His research spans neural networks, distributed systems, and e-learning technologies. Education: PhD, Electrical and Electronic Engineering, Middle East Technical University (1989) M.Sc., Electrical and Electronic Engineering, METU B.Sc., Electrical and Electronic Engineering, METU Research Interests: Prof. Aybay's work focuses on computer engineering innovations, including neural network hardware, distributed multimedia systems, and wireless communication protocols. He pioneered EMUOnline, a blended learning platform, and contributed to science park development in North Cyprus. His research also addresses challenges in video streaming optimization and adaptive resource allocation in cellular networks. Key Achievements: He led over 15 projects, including EU-funded initiatives like 'Deep Farm' (2024–2025). His publications (80+ papers) span IEEE journals and conferences, with 281 Google Scholar citations. Awards include the 1973 National Project Contest First Prize and the 1990 Best Thesis Award (supervised). Grants and advising: Supervised 3 PhD and 28 MSc students. Current projects include AI-driven agriculture (Erasmus+). Grants include EU funding (€1M) and Turkish Republic of Northern Cyprus initiatives. Labs/Teams: Active in the EMU Computer Engineering Department's research groups, focusing on distributed systems and e-learning infrastructure.

Prateek Jainمشاهده پروفایل

مدرس

• Knowledge Graphs
• Natural Language Processing
• Machine Learning
• +۶ مورد دیگر

Prateek Jain is a Lecturer at the School of Information, San José State University, where he teaches courses in Big Data Analytics and Python programming. He holds a Ph.D. in Computer Science and Engineering from Wright State University and has over a decade of industrial experience in data science and artificial intelligence at leading institutions such as IBM T.J. Watson Research Center, Nuance Research Labs, and Liveperson. His research interests include Knowledge Graphs, Natural Language Processing, Machine Learning, and Big Data, with over 30 peer-reviewed publications and patents in these areas. His academic and professional background bridges advanced research and practical deployment of AI-driven systems. Ph.D. (Computer Science and Engineering), Wright State University (2007–2012) Ph.D. (Computer Science), University of Georgia (2006–2007, transferred) BS (Information and Communication Technology), Dhirubhai Ambani Institute of ICT (2002–2006) Prateek's research publications focus on the development and application of Knowledge Graphs, particularly in areas like NLP, enterprise search, healthcare, and financial services. His work emphasizes scalable, explainable, and practical AI solutions, with recurring themes in graph embeddings, semantic reasoning, and large-scale data integration. He has served as an Adjunct Instructor at Chabot College and Northwestern Polytechnic University, and currently contributes to academic instruction at SJSU while maintaining an active role in industry as Principal Data Scientist at Liveperson. His industrial roles have spanned: Principal Data Scientist, Knowledge Graphs – Liveperson Inc. (2021–Present) Engineering Manager, Machine Learning – AppZen Inc. (2018–2021) Principal Research Engineer – Nuance Inc. (2016–2018) VP/Data Scientist – BlackRock Inc. (2015–2016) Data Scientist – Ignition One (2015) Research Staff Member – IBM T.J. Watson Research Center (2012–2015) There are no listed scientific awards or advisees in the provided information.

• Complex Networks
• Gene Regulatory Networks
• Nonlinear Dynamical Systems
• +۶ مورد دیگر

Enrico Borriello serves as a Research Assistant Professor in Arizona State University's School of Complex Adaptive Systems and holds a concurrent appointment as Senior Global Futures Scientist. His interdisciplinary work bridges theoretical physics with complex systems science, focusing on network dynamics and astrophysical phenomena across ASU's research initiatives including the Complex Systems Research Group and Biosocial Complexity Initiative. Borriello's research centers on the controllability of complex networks—particularly gene regulatory systems—and non-linear dynamics in biological modeling. He equally investigates theoretical particle physics and astrophysics, specializing in neutrino behavior within supernovae and dark matter signatures through cosmic ray interactions. His expertise spans Network Science, Nonlinear Dynamical Systems, Neutrino Astrophysics, and Information Theory, with applications ranging from transcriptional regulation to galactic magnetic field phenomena. Analysis of his publication record reveals two dominant research streams: network science (focusing on Boolean network controllability, attractor landscapes, and evolutionary frameworks) and particle astrophysics (addressing neutrino oscillations, supernova modeling, and dark matter detection). This dual focus demonstrates his ability to apply theoretical physics principles to both biological complexity and cosmic-scale phenomena. Scientific Awards: No awards or fellowships were mentioned in the source materials. Advising and Grants: The provided information does not specify doctoral students, postdoctoral researchers, or grant funding details. His teaching portfolio indicates extensive course development in complex systems methodology rather than direct research supervision. Labs and Teams: Borriello actively contributes to ASU's Complex Systems Research Group and Biosocial Complexity Initiative, interdisciplinary hubs that facilitate collaboration between computational modelers, biologists, and social scientists studying emergent phenomena in adaptive systems.