جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Distributed Learning
• +۷ مورد دیگر

Berta María Guijarro Berdiñas is a Researcher in the Department of Computer Science and Artificial Intelligence at the University of A Coruña , Spain. She is affiliated with the Laboratory for Research and Development in Artificial Intelligence and teaches courses like Machine Learning , Development of Intelligent Systems , and Programming at both undergraduate and postgraduate levels. Research Focus: Her work lies at the intersection of Artificial Intelligence , Machine Learning , and Knowledge-Based Systems . Key contributions include frugal learning (limited data), anomaly explanation , and distributed learning for edge devices. She applies these to areas like health informatics , forest fire management , and human-robot interaction . Recent Publications span explainable AI , anomaly detection , multi-agent systems , and low-power machine learning . Her articles appear in top venues like Expert Systems with Applications and IEEE Transactions on Neural Networks and Learning Systems . Grants & Projects include EU-funded initiatives, Spanish Ministry of Science grants, and regional collaborations. She focuses on AI for healthcare , smart systems , and distributed learning .

• Astrobiology
• Theoretical Physics
• Origin of Life
• +۳ مورد دیگر

Sara Walker is an Associate Professor at Arizona State University, serving as Deputy Director of the Beyond Center for Fundamental Concepts in Science, Associate Director of the ASU-Santa Fe Institute Center for Biosocial Complex Systems, and a member of the Board of Directors of Blue Marble Space. Her work bridges astrobiology and theoretical physics with a focus on the origin of life. School of Earth and Space Exploration Beyond Center for Fundamental Concepts in Science ASU-Santa Fe Institute Center for Biosocial Complex Systems Walker explores whether universal 'laws of life' exist, emphasizing how information structures physical systems. Her research spans exoplanet atmospheric chemistry, biochemical network analysis, and the application of assembly theory to quantify molecular complexity and evolutionary dynamics. Her recent publications highlight advancements in assembly theory for life detection, biochemical reaction modeling, and exoplanet habitability assessments. Key themes include chemical selection, information processing in biological systems, and the universality of biochemical patterns. Walker actively engages in public science communication through appearances at the World Science Festival, 'Through the Wormhole,' and NPR's Science Friday. She co-founded an astrobiology-themed social website and contributes to STEM education initiatives.

Juan Carlos Linares Calderónمشاهده پروفایل

استاد

• Ecology
• Climate Change
• Forest Management
• +۵ مورد دیگر

Juan Carlos Linares Calderón is a Full Professor at Pablo de Olavide University in the Department of Physical, Chemical and Natural Systems. His research focuses on Mediterranean relict forests' response to climate change through multidisciplinary approaches combining dendrochronology , ecophysiology , genomics , and epigenetics . PhD in Science (2008) from University of Jaén Principal Investigator in 10+ national/international projects Research Themes Specializing in climate change impacts on forest ecosystems , Linares leads the Forests Ecology and Global Change Lab . His work spans from individual tree responses to large-scale biogeographical patterns, challenging CO 2 -induced growth paradigms and emphasizing forest management as climate modulator. Scientific Contributions Over 162 publications with 82,704 reads and 9,074 citations Highly Cited Author status (Ioannidis et al., 2020) Developed SAPFLUXNET global transpiration database Email: jclincal@upo.es

• Astronomy
• Astrophysics
• Machine Learning
• +۵ مورد دیگر

Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.

Sandeep Reddivariمشاهده پروفایل

دانشیار

• Software Engineering
• Requirements Engineering
• Visual Analytics
• +۷ مورد دیگر

Sandeep Reddivari is an Associate Professor and Interim Graduate Director at the School of Computing, University of North Florida . Holding a Ph.D. in Computer Science and Engineering from Mississippi State University, his work focuses on software engineering , particularly requirements engineering , visual analytics , and software maintenance , with funding from the NSF, US Army Corps of Engineers, NSA, and UNF Foundation. Education : Ph.D. (2014, Mississippi State University), M.S. (2009, Texas A&M University), B.Tech. (2006, JNTU) Research Themes : Requirements Engineering, Visual Analytics, Data Mining, Machine Learning, GenAI, Software Security Teaching : Courses in Software Engineering, Data Science, and Database Systems Awards : NSF Grant Recognition (2024), Best Doctoral Symposium Poster (2013), Outstanding Graduate Teaching Award Nominee (2018) Publications span top venues like IEEE RE, ICSE, and COMPSAC, with a focus on combining visual analytics and machine learning to enhance software decision-making. His lab at UNF mentors students in directed independent studies, emphasizing code navigation , blockchain , and educational software tools .

Santiago Figueiraمشاهده پروفایل

استاد

• Theoretical computer science
• Computability theory
• Algorithmic randomness
• +۸ مورد دیگر

Santiago Figueira is a Professor at the Department of Computer Science, Faculty of Exact and Natural Sciences, University of Buenos Aires, and a Researcher at the Institute of Computer Science (ICC), CONICET (Argentine National Council for Scientific and Technical Research) in Buenos Aires, Argentina. He leads the Logic, Language and Computability Research Group (GLyC) and co-directs the Argentinian-French Laboratory SINFIN, a collaborative initiative between Université Paris-CNRS and Universidad de Buenos Aires-CONICET. Additionally, he is a researcher in the Quantum Information, Computation, and Communication team (QuICC). Dr. Figueira's research spans theoretical computer science with a strong emphasis on computability theory, algorithmic randomness, Kolmogorov complexity, and mathematical logic. His work extends to applications in database theory, quantum information, and cognitive modeling. He has made significant contributions to modal logics, model theory, and the theory of databases, particularly in the context of data trees and XPath query languages. His interdisciplinary approach bridges formal methods with practical applications in quantum computing and human cognition. His publication record demonstrates a consistent trajectory of high-impact research, with recent work focusing on modal logic extensions, quantum information theory, cognitive modeling of concept learning, and database query languages. His collaborations span international institutions, particularly with French researchers through the SINFIN laboratory, and with cognitive scientists studying human memory and concept formation. Dr. Figueira has supervised numerous PhD students and postdoctoral researchers, including Gabriel Goren-Roig, Santiago Cifuentes, Edwin Pin Baque, Sergio Romano, Gabriel Senno, and Sergio Abriola. His former postdocs and CONICET researchers include Guido Bellomo, María Emilia Descotte, and Ariel Bendersky, indicating an active and productive research group. He has developed lecture notes in Spanish on Logic and Computability (2020) and Computability Theory (2021), contributing to academic education in his field. His research group GLyC serves as a hub for theoretical computer science research in Argentina, fostering collaborations between Argentine and international researchers.

• Bioinformatics
• Computational Biology
• Algorithms
• +۵ مورد دیگر

Travis Wheeler is an Associate Professor in the Department of Pharmacy Practice & Science at the University of Arizona. His work spans bioinformatics, computational biology, and algorithm development for genomic sequence analysis. Developed tools like HMMER and Dfam Research focuses on transposable elements, sequence alignment, and epigenetics Co-author of key works with Robert Finn, Sean Eddy, and colleagues Research Interests include machine learning applications in biological sequence annotation, drug discovery, and evolutionary genomics. His work bridges computational methods with biomedical applications. Notable Contributions : Advancing profile Hidden Markov Model (HMM) methodologies Creating community resources for transposable element research Developing alignment algorithms for biological sequences Collaborations include institutions like Institute for Systems Biology, Harvard University, and Montana State University.

Brian D. Atheyمشاهده پروفایل

استاد

• Bioinformatics
• Pharmacogenomics
• Machine Learning
• +۸ مورد دیگر

Brian D. Athey is a Professor of Computational Medicine and Bioinformatics and Psychiatry at the University of Michigan Medical School. He serves as Michael Savageau Collegiate Professor & Chair of his department, leading interdisciplinary research in pharmacogenomics, epigenomics, and machine learning applications. His work bridges biomedical informatics with clinical insights in mental health, neurology, and drug response mechanisms. Ph.D. , Biophysics, University of Michigan (1990) B.S. , University of Michigan-Dearborn (1982) Dr. Athey’s research focuses on the pharmacoepigenome, high-throughput 4D imaging, and AI-driven pharmacogenomic pipelines. His lab develops tools for patient-specific drug response prediction, chromatin structure analysis, and next-generation sequencing assays. Collaborations span institutions like Assurex Health, tranSMART Foundation, and Johns Hopkins Medical School. His publications highlight innovations in pharmacogenomics, including AI integration for variant identification, 4D nucleome modeling, and adverse event ontologies. Recent projects address bipolar disorder treatment personalization, hypertension management, and generative AI workflows to enhance academic productivity. Scientific Awards : NIH Postdoctoral Fellowship 1990-1991 NIH Postdoctoral Fellowship 1991-1993 Advisees & Collaborations : His lab mentors PhD and Masters students in bioinformatics and biostatistics, with graduates like Ari Allyn-Feuer (GSK AI Products Director) and Alex Kalinin (Broad Institute). Collaborations include NIH-funded initiatives (O’Brien Kidney Core Center, VIOLIN 2.0) and industry partnerships.

• Radiation Oncology
• Gastrointestinal Cancers
• Head and Neck Cancers
• +۳ مورد دیگر

Shane Lloyd, MD, is an Associate Professor in the Department of Radiation Oncology at the University of Utah School of Medicine, affiliated with Huntsman Cancer Institute. He specializes in treating gastrointestinal, head/neck, and genitourinary cancers. His research emphasizes improving care quality through data analysis, clinical trials, and addressing health disparities in cancer survivorship. Education: M.D. & M.H.S. from Yale School of Medicine B.A. in Economics and Zoology from Brigham Young University Residency in Radiation Oncology at Yale New Haven Hospital Internship at University of Utah Affiliated Hospitals Research Focus: Dr. Lloyd investigates radiation therapy optimization, cancer survivorship outcomes, and socio-geographic health disparities. His work integrates population-based data analytics to evaluate treatment efficacy, mental health impacts, and equitable care access. Publications: Recent articles (2022–2025) highlight trends in prostate, bladder, and gastrointestinal oncology, with emphasis on immunotherapy combinations, survivorship disparities, and biomarker-driven recurrence detection. Machine learning applications in treatment decision-making and rural health inequities are recurring themes. Leadership: Chairs the Radiological Drug Research Committee (RDRC) and Human Use Subcommittee of the Radiation Safety Committee (HUS-RSC).

Narges Arastoueiمشاهده پروفایل

پژوهشگر ارشد

• Cybersecurity
• Network Security
• Wireless Communications
• +۶ مورد دیگر

Dr. Narges Arastouei serves as a postdoctoral researcher at the Chair of Mobile Business & Multilateral Security, Goethe University Frankfurt since 2019. With over 12 years of industry experience including leadership of security operations at Iran's largest mobile provider (MCI), she specializes in cybersecurity for next-generation mobile networks and critical infrastructure protection. Her educational background includes: Ph.D. in Computer System Networking and Telecommunications from Amirkabir University of Technology (AUT), Tehran Research focuses on network security, 5G/6G communications, IoT security, and Security Operations Center (SOC) frameworks. Current work bridges theoretical networking with practical incident handling, emphasizing human factors in cybersecurity and privacy-preserving healthcare applications. Her projects address evolving threats in mobile ecosystems through both technical solutions and policy frameworks. Publication trends reveal progression from foundational work in opportunistic network routing (2013-2019) to cutting-edge 6G security research (2022-2025), with consistent emphasis on real-world implementation challenges. Key themes include risk-aware protocols, botnet detection, and secure healthcare systems. Scientific recognition includes: First-place doctoral student award She leads coordination of EU-funded CyberSec4Europe and CyberSecPro projects while spearheading human factor components in the ECCO initiative. Secured Goethe-Corona-Fonds grant funding for longitudinal study on Germany's Corona Warning App adoption. Hosts the SECMGT workshop on information security management since 2023. Active within Goethe University's security research ecosystem, she contributes to multilateral security frameworks and mentors junior researchers through student assistant programs.

• Bayesian Statistics
• Expert Knowledge Elicitation
• Robust Analyses
• +۳ مورد دیگر

Professor John Paul Gosling is an applied statistician affiliated with the Department of Mathematical Sciences at Durham University . With a background in industry, academia, and the civil service, his work bridges statistical theory and real-world applications, particularly in criminal justice, toxicology, and climate science. Education: MMath in Mathematics (University of York, 1998–2002), PhD in Statistics (University of Sheffield, 2002–2005) Current Role: Professor in Statistics, focusing on human interaction with statistical information His research interests include: Bayesian Statistics : Developing models for complex systems Expert Knowledge Elicitation : Structuring expert input for risk assessment Uncertainty Quantification : Analyzing and communicating uncertainty in data Machine Learning Integration : Combining statistical inference with AI for decision-making Key trends from his recent articles include: Application of Voronoi Tessellations in Bayesian regression and classification Development of emulation techniques for computationally intensive models Focus on legal and public health domains Integration of copula methods for dependent variables He actively supervises PhD students in Bayesian theory and machine learning interfaces and contributes to Statistics research at Durham University.

Morteza Zihayatمشاهده پروفایل

دانشیار

• Data Analytics
• Human-centered AI
• Decentralized AI
• +۶ مورد دیگر

Morteza Zihayat is an Associate Professor and Canada Research Chair (Tier 2) in Human-Centered Artificial Intelligence at Toronto Metropolitan University. He holds dual appointments in the Faculty of Engineering and Architectural Science (Department of Electrical, Computer, and Biomedical Engineering) and the Ted Rogers School of Management. Additionally, he serves as an Adjunct Professor at the University of Waterloo in Management Sciences and is a Faculty Fellow at IBM's Centre for Advanced Studies. Dr. Zihayat's educational background includes: PhD in Computer Science from York University (2016) MSc in Computer Engineering from University of Tehran (2011) Postdoctoral Research Fellowship at University of Toronto's Faculty of Information (2017) His research lies at the intersection of AI, security, and society with a focus on building fair and transparent AI systems. Dr. Zihayat's expertise spans human-centered AI, fair information retrieval systems, and blockchain-enabled AI infrastructures. His work emphasizes creating AI systems that are accountable and designed to serve the public good, with applications in healthcare, digital media, and social networks. Dr. Zihayat has received numerous accolades including the Canada Research Chair (Tier 2) in Human-Centered AI (2024), Dean's Outstanding Scholarly, Research, and Creative Activity Award (2023), Best Short Paper Award at ECIR (2023), and IBM CAS Faculty Fellowship (2021). His research has attracted over $1.7 million in external funding from agencies such as NSERC, Mitacs, and multiple industry partners including Toronto Transit Commission, The Globe and Mail, AT&T, and IBM. Dr. Zihayat serves as Associate Editor of the Computational Intelligence Journal and is an active reviewer for top-tier venues. He is also Co-director and Co-founder of the Digital Enterprise Analytics and Leadership (DEAL) Research Center.

Jignesh M. Patelمشاهده پروفایل

استاد

• Database Systems
• Query Optimization
• Data Analytics
• +۳ مورد دیگر

Jignesh M. Patel is a Professor in the Computer Science Department at Carnegie Mellon University, where he leads research on efficient data analysis methods. His work focuses on improving both system efficiency (e.g., high-performance data algorithms) and human efficiency (e.g., user productivity with data systems). Research Focus: Patel's group specializes in database systems, query optimization, hardware acceleration, and human-data interaction. Their interdisciplinary work spans: Transactional processing and real-time analytics Query optimization techniques Hardware-algorithm co-design Natural language interfaces for data systems Memory-efficient data processing Professional Activities: Co-founded four technology companies (Paradise, Locomatix, Quickstep, DataChat). Serves on program committees for premier conferences including SIGMOD and CIDR (as co-chair). Teaches database systems courses at CMU. Awards: Received Best Paper Award at DaMoN 2010 for work on cluster efficiency.

Alba Huidobroمشاهده پروفایل

پژوهشگر ارشد

• Comparative Politics
• Political Behavior
• Gender and Politics
• +۳ مورد دیگر

Alba Huidobro is a political scientist with a PhD from Pompeu Fabra University (2022). She currently serves as a Research Fellow at the Chair of Political Behavior at Humboldt University of Berlin, following a postdoctoral role at Stanford Impact Labs and Stanford University's Political Science Department. Her academic journey includes visiting research positions at the European University Institute, Nuffield College (Oxford), and UC Berkeley's Haas School of Business. Education: PhD in Political Science (Pompeu Fabra University, 2022), Master's in Political Science Research (Pompeu Fabra University) Her research explores intersections of comparative politics, political behavior, and gender dynamics. Key findings demonstrate how government negotiation processes perpetuate gender gaps in leadership roles, impacting policy representation for diverse groups. Publications include high-impact work in The Journal of Politics and European Journal of Political Research , with ongoing projects examining affirmative action effects, feminist movements, and gendered governance patterns in India and Europe. Collaborations span institutions like Stanford Impact Labs, European University Institute, and Barcelona Institute of International Studies (IBEI), where she contributes to projects analyzing local political leaders in Spain.

• Computational Biophysics
• Machine Learning
• Molecular Dynamics

Dr. Matteo Degiacomi is a Visiting Associate Professor in the Department of Physics at Durham University. His research focuses on integrative computational methods combining machine learning and molecular dynamics simulations to model biomolecular systems at near-atomistic resolution. Education: MSc in Computer Science (2008), PhD in computational biophysics (2012) from EPFL. His work leverages ion mobility , cross-linking , SAXS , and electron microscopy data to study protein assembly mechanisms. Recent publications highlight applications in virology , nanomaterials , and membrane protein dynamics . He develops open-source tools like ClayCode and JabberDock . Scientific awards include a Swiss National Science Foundation Early Postdoc Mobility Fellowship (2013-2017) and an EPSRC Junior Research Fellowship (2017-2020). He supervises postgraduate researchers Ajeeth Kanagarajan , Breanna Voss , and Listra Ginting .