جست‌وجوی استاد و پژوهشگر

Nori Jacobyمشاهده پروفایل

استادیار

• Cognitive Science
• Computational Neuroscience
• Music Cognition
• +۳ مورد دیگر

Nori Jacoby is an Assistant Professor in the Department of Psychology at Cornell University and a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt. His research examines how internal representations shape sensory and cognitive abilities through computational approaches, cross-cultural studies, and large-scale behavioral experiments. Ph.D. from Hebrew University of Jerusalem (Edmond and Lily Safra Center for Brain Sciences) Postdoctoral training at MIT, UC Berkeley, and Columbia University Research areas include: Computational modeling of human perception Cross-cultural analysis of musical cognition Collective behavior in social networks Recent publications focus on: Global rhythm perception patterns Machine learning alignment with human cognition Oral transmission mechanisms in music evolution Scientific awards: NSF grant for collaborative creativity research Presidential Scholar in Society and Neuroscience Lab: Cornell Computational Cognition (CoCoCo) Lab

Alexander L. Wolfمشاهده پروفایل

استاد

• distributed systems
• networking
• software engineering
• +۳ مورد دیگر

Alexander L. Wolf is the Dean of the Baskin School of Engineering and a Distinguished Professor of Computer Science and Engineering at the University of California, Santa Cruz. He holds a B.A. in Geology and Computer Science from Queens College (CUNY), and M.S./Ph.D. degrees from the University of Massachusetts Amherst. His career includes foundational roles at AT&T Bell Laboratories, the University of Colorado (where he held the Charles Victor Schelke Chair), the University of Lugano (founding the Faculty of Informatics), and Imperial College London. Wolf's research bridges distributed systems , networking , and software engineering , with recent projects in cloud computing, data-center networking, and mobile ad hoc networks (MANETs). His work emphasizes scalable architectures, fault tolerance, and adaptive service deployment. Key projects include HARNESS (hardware-enhanced cloud systems) and SERECA (secure cloud enclaves). His publications focus on optimizing networked systems, fault localization, and adaptive resource management. Trends include rigorous simulation-based validation, cross-layer optimization (e.g., integrating GPUs/networking), and practical applications in geosciences (Reverse-Time Migration) and machine learning (Bing's AdPredictor). Awards: ACM/IEEE/AAAS Fellow; Royal Society-Wolfson Research Merit Award; Two-time ACM SIGSOFT Research Impact Award; ACM SIGSOFT Outstanding Research & Distinguished Service Awards. Wolf leads major grants (e.g., EU H2020 SERECA, EPSRC NaaS) and has chaired ACM's Executive Committee. He founded ACM's Europe Council and contributed to seminal tools like the Siena publish/subscribe system. His team develops experimental platforms (e.g., Weevil for distributed testbeds) and collaborates with industry (AT&T, Microsoft Bing).

Guimin Gaoمشاهده پروفایل

پژوهشگر

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

Guimin Gao is a researcher with expertise in statistical genetics and bioinformatics. His research focuses on applying statistical methods to analyze genetic and genomic data, including collaborations in clinical and translational science. He has developed methods for haplotyping, gene mapping in admixed populations, and analyses of GWAS, methylation, and DNA sequencing data. He holds a Ph.D. in Biostatistics from Sun Yat-sen University of Medical Sciences and has completed postdoctoral training at Virginia Tech and Creighton University. His work spans diverse areas such as epigenetic biomarker identification in schizophrenia and statistical methodologies for genomic association studies. Education: Ph.D. (Biostatistics, 2000), Postdoc in Statistical Genetics (2001-2005) Research interests include statistical genetics, bioinformatics, and the application of computational methods to biomedical data. His publications demonstrate contributions to haplotype analysis, admixture mapping, and epigenetic studies. Gao has collaborated on projects involving family-based studies, meta-analyses, and the development of tools like MethylPCA for confounder control in methylome-wide studies.

David Spielerمشاهده پروفایل

استاد

• Machine Learning
• Stochastic Systems
• Biochemical Systems Modeling
• +۳ مورد دیگر

David Spieler is a Professor of Machine Learning at the University of Applied Sciences Munich since September 2018. Previously, he served as a product owner for big data topics at Audi AG (2015–2018), a system developer at Bosch SoftTec (2014–2015), and completed his PhD in Modeling and Simulation at Saarland University (2009–2014). His research focuses on stochastic systems, biochemical modeling, parameter estimation, and oscillatory behavior analysis in Markovian systems. He has contributed to numerical methods for steady-state analysis, formal verification techniques, and applications in systems biology. Research interests include stochastic hybrid systems, sensitivity analysis of biochemical networks, geometric bounds for CTMC steady-state distributions, and oscillatory dynamics in chemical reaction networks. He has published extensively on topics like model checking, parameter estimation, and algorithmic solutions for stochastic processes. His work bridges theoretical computer science with practical applications in bioinformatics and engineering. Spieler has taught courses on data networks, quantitative model checking, and stochastic simulation techniques. He has reviewed manuscripts for over 20 conferences including CAV, CMSB, HSCC, and QEST, contributing to the advancement of formal methods and computational systems biology.

Mohammad T. Irfanمشاهده پروفایل

دانشیار

• Computational Game Theory
• Artificial Intelligence
• Social Network Analysis
• +۳ مورد دیگر

Mohammad T. Irfan is the John F. and Dorothy H. Magee Associate Professor of Digital and Computational Studies (DCS) and Computer Science (CS) at Bowdoin College, with a joint appointment between the two departments. He also serves as the Director of the DCS Program. Irfan holds a PhD in Computer Science from Stony Brook University (2013), and an MS and BS in Computer Science and Engineering from Bangladesh University of Engineering and Technology (2006 and 2004, respectively). His research focuses on computational game theory, AI, social network analysis, economics, and image analysis of art, supported by an NSF grant. He teaches courses such as DCS 1500 and CSCI 2320, emphasizing interdisciplinary approaches to computational methods. Research interests include strategic interactions in networks, microfinance markets, and the application of game theory to social influence and art authentication (e.g., Jackson Pollock paintings). Irfan’s work bridges AI and social sciences, with notable achievements like a Best Paper Award with an undergraduate student. His teaching philosophy emphasizes student engagement and the liberal arts tradition, fostering a supportive environment for learning and research. Scientific contributions span algorithmic game theory, equilibrium computation, and network influence models. Grants and awards highlight his interdisciplinary impact, including NSF funding for research on influence games. Irfan’s leadership in creating Bowdoin’s DCS program reflects his commitment to fostering interdisciplinary education and innovation.

• Machine Learning
• Causal Inference
• Signal Processing
• +۴ مورد دیگر

Yongqiang Chen is a Professor at the Chinese Academy of Sciences in the School of Engineering, Department of Computer Science and Engineering. With over 15 years of continuous research contributions spanning from 2005 to 2025, Dr. Chen has established himself as a versatile scholar working at the intersection of theoretical mathematics, machine learning, and practical engineering applications. Dr. Chen's research expertise encompasses: Machine Learning and Causal Inference, with recent focus on large language models and out-of-distribution generalization Signal and Image Processing, particularly in keyword spotting and watermarking applications Optimization Algorithms for engineering and management problems Theoretical Mathematics, including partition functions and combinatorial identities Engineering Management and Project Governance in construction contexts His recent publication trajectory (2023-2025) reveals a strategic evolution toward integrating causal reasoning with modern neural architectures, while maintaining strong connections to practical applications. Dr. Chen's work demonstrates exceptional interdisciplinary range, bridging pure mathematics with cutting-edge AI development and engineering solutions. His publications in venues like AAAI, NeurIPS, and IEEE Transactions reflect both theoretical rigor and practical relevance across multiple domains including renewable energy, neuroscience, and construction management. Dr. Chen maintains active collaborations with researchers across institutions, particularly with Bo Han on causal language models, James Cheng and Yiping Ke on brain network analysis, and various colleagues in engineering management. His research group appears to focus on developing theoretically sound yet practically applicable computational frameworks that address real-world challenges while advancing fundamental knowledge in machine learning and optimization.

• Ambient Intelligence
• Intelligent Environments
• Pervasive Computing
• +۷ مورد دیگر

Victor Callaghan is a Professor at the University of Essex in the Department of Computer Science, School of Computer Science and Electronic Engineering. With an extensive publication record spanning four decades from 1982 to 2022, he has established himself as a leading researcher in the fields of Ambient Intelligence, Intelligent Environments, and Pervasive Computing. His work bridges the gap between theoretical computer science and practical applications in smart environments. Callaghan's research interests focus on Ambient Intelligence, Intelligent Environments, Pervasive Computing, Human-Computer Interaction, Educational Technology, Virtual and Augmented Reality, and Fuzzy Logic Systems. His work demonstrates a consistent trajectory from foundational computer science topics toward increasingly sophisticated intelligent environments that adapt to human needs. He has pioneered approaches that integrate multiple technologies to create seamless intelligent spaces that enhance human experience and learning. His publication pattern reveals a strong emphasis on educational applications of intelligent environments, with numerous papers exploring how virtual and augmented reality can transform learning experiences. His recent work shows a maturation of the field from theoretical foundations to practical implementations in real-world settings, particularly in education and healthcare contexts. The interdisciplinary nature of his work is evident in collaborations spanning computer science, education, psychology, and engineering disciplines. Callaghan has played significant editorial roles, including serving as guest editor for special issues and contributing prefaces to journal editions focused on future intelligent educational environments. His leadership in the academic community is further demonstrated through organizing and reporting on major international conferences in the field of Intelligent Environments. His research methodology often combines theoretical frameworks with practical implementations, creating systems that demonstrate the real-world applicability of intelligent environment concepts. The evolution of his work shows a progression from basic computational models to sophisticated multi-agent systems that can adapt to user behavior and environmental conditions.

Víctor López Domínguezمشاهده پروفایل

استادیار

• Spintronics
• Magnetic materials
• Electrical transport
• +۵ مورد دیگر

Víctor López Domínguez is an Assistant Professor and Principal Investigator at the Institute of Advanced Materials (INAM) of Jaume I University in Castelló, Spain, where he leads the Spintronics for Advanced Devices Lab (SPINAD Lab). His research focuses on developing next-generation spintronic devices for computing and sensing applications. His academic background includes: PhD in Nanoscience and Nanotechnology (2014) from University of Barcelona Physics Degree (2009) from University of Barcelona López Domínguez's research centers on electrical transport in magnetic materials, magnetization dynamics, and voltage-controlled spintronic devices. His work bridges fundamental physics with practical applications in neuromorphic computing, probabilistic systems, and nanoscale sensors. Key focus areas include antiferromagnetic spintronics, skyrmion manipulation, and energy-efficient computing paradigms that leverage spin-orbit torque and voltage control mechanisms. His 15 most recent publications reveal a strong emphasis on antiferromagnetic memory devices, voltage-controlled magnetism, and neuromorphic applications. The research spans from fundamental material studies to device integration, with significant contributions to silicon-compatible spintronic memory, probabilistic computing hardware, and magnetomechanical sensors. His scientific recognition includes: CIDEGENT grant (2022) from Generalitat of Valencia López Domínguez secured the CIDEGENT grant to establish his research group at INAM, supported by Jaume I University and INAM. His lab trains undergraduate, master's, and PhD students in experimental spintronics while collaborating with international clean rooms and industry partners. Current projects focus on implementing novel computing paradigms using spintronic devices. The SPINAD Lab maintains comprehensive facilities for material fabrication, device characterization, and nanofabrication through Spanish clean room networks. The group collaborates extensively with Northwestern University (where López Domínguez previously worked) and participates in international research consortia focused on next-generation computing technologies.

Emmanuel VAZQUEZمشاهده پروفایل

استاد

• Bayesian Statistics
• Computer Experiments
• Uncertainty Quantification
• +۳ مورد دیگر

Emmanuel Vazquez is a Professor and researcher at CentraleSupélec, specializing in Bayesian design and analysis of computer experiments. He coordinates Data Science projects and leads research in Gaussian processes, uncertainty quantification, and optimization. He holds a PhD (2005) and HDR (2015) from Université Paris-Saclay, and has taught Bayesian statistics at CentraleSupélec. His work focuses on sequential design strategies, multi-fidelity simulations, and risk assessment in engineering and microbiology. He collaborates with institutions like the GdR MascotNum and PGMO, advancing methodologies for efficient simulation-based decision-making. His research includes applications in TBM excavation modeling, renewable energy integration, and food safety through quantitative microbial risk analysis. Education: École Normale Supérieure de Cachan (1997–2001), DEA/M2 in Mathematics (2001), PhD in Applied Mathematics (2005), Habilitation (2015). Research interests span Bayesian optimization, Gaussian process metamodeling, and stepwise uncertainty reduction (SUR) strategies. He develops algorithms for efficient sampling in expensive-to-evaluate systems, with applications to engineering, environmental modeling, and public health. His recent articles emphasize quantile set inversion, risk assessment in food safety, and scalable Gaussian process methods. Collaborations include projects on railway infrastructure digital twins (MINERVE) and multi-year renewable energy planning. He has contributed to open-source tools like the STK toolbox for kriging.

Sara Gundersenمشاهده پروفایل

استاد

• Development Economics
• Economics of Education
• Econometrics
• +۳ مورد دیگر

Sara Gundersen is a Professor of Economics at Valparaiso University, affiliated with the College of Arts and Sciences. She specializes in development economics, the economics of education, econometrics, and pedagogical innovation. Her research focuses on gender, religion, and economic outcomes in developing nations, particularly Ghana. She holds a Ph.D. from Clark University (2011), an M.A. from Clark University, and a B.A. from the University of Wisconsin, Stout. Education: B.A. – University of Wisconsin, Stout M.A. – Clark University Ph.D. – Clark University Dr. Gundersen's research investigates how religious practices, education systems, and socio-economic policies influence gender dynamics and economic outcomes in global contexts. Recent work examines Pentecostalism's impact on intimate partner violence in Ghana and the relationship between charismatic church membership and women's economic empowerment. She has pioneered innovative teaching methods, including role-play simulations for macroeconomics instruction and pandemic-era pedagogy adapting to the 2020 crisis. Her awards include the 2020-2021 Valparaiso Excellence in Teaching Award and the 2019 Wheat Ridge Ministries Research Grant. She has also been recognized for emerging teaching excellence multiple times (2015, 2014 nominee). Dr. Gundersen is professionally affiliated with the American Economic Association (AEA) and the Center for the Status of Women in the Economics Profession (CSWEP). Her teaching portfolio includes courses such as Principles of Economics, Environmental Economics, and the Economics of Developing Nations.

Neil Mac Parthalainمشاهده پروفایل

مدرس ارشد

• Computational Intelligence
• Data Mining
• Machine Learning
• +۵ مورد دیگر

Neil Mac Parthalain is a Senior Lecturer in the Department of Computer Science at Aberystwyth University. He holds degrees including a BSc from Cardiff University, an MSc from the University of Wales, and a PhD from the University of Wales. His research focuses on computational intelligence, with particular emphasis on feature selection, fuzzy-rough sets, data reduction, and their applications in healthcare and engineering. He has led projects such as 'An intelligent approach to bed occupancy modelling to enhance patient care' (2018–2021) and 'Improved modelling techniques for mammographic image analysis' (2012–2014). His work contributes to UN Sustainable Development Goals related to good health and well-being. Key research areas include fuzzy inference systems, reinforcement learning, and three-way classification models. His publications span journals like IEEE Transactions on Fuzzy Systems and PLOS Digital Health, addressing topics such as hospital length of stay prediction and component failure analysis. Collaborations include researchers in mechanical engineering, geology, and robotics. He has supervised 7 doctoral students and contributed to conference proceedings such as the UK Workshop on Computational Intelligence. Media coverage highlights his insights on AI's impact on Welsh language poetry and healthcare systems.

• Bayesian Statistics
• Environmental Modelling
• Stochastic Processes
• +۳ مورد دیگر

Benjamin Thomas Swallow is a Lecturer in Statistics at the University of St Andrews, affiliated with the Statistics Centre for Research into Ecological & Environmental Modelling. He holds editorial roles at journals such as Journal of Statistical Theory and Practice and Royal Society Open Science , and serves as Meetings Secretary for the Royal Statistical Society's Environmental Statistics Section. His research focuses on Bayesian methods, stochastic processes, and model calibration, with applications in epidemiology, ecology, and environmental science. Swallow has contributed to over 30 research outputs, including studies on agent-based models for HPV simulation, citizen science data analysis, and antibody responses to vaccines. He has received awards such as the RSE Mary Somerville Medal (2023) and the University of Edinburgh Research Impact Award (2024). His work intersects statistical theory and practical applications, emphasizing reproducibility and methodological innovation. He collaborates internationally on projects spanning ecological statistics and computational epidemiology.

• Computer Architecture
• Parallel Computing
• Cache Coherence
• +۵ مورد دیگر

Manuel Eugenio Acacio Sanchez is a Professor in the Department of Computer Engineering and Technology at the University of Murcia's Faculty of Informatics. His research focuses on computer architecture, parallel systems, cache coherence, and hardware transactional memory. He earned his Ph.D. from the University of Murcia in 2003 with a thesis on directory-based coherence protocols for distributed-shared memory multiprocessors. Doctorate: Universidad de Murcia (2003) Academic Rank: Professor Research Interests include Hardware transactional memory Cache coherence protocols GPU and DNN accelerators Energy-efficient computing Parallel architectures Recent Article Trends emphasize cycle-level simulation tools (e.g., STONNE), hardware transactional memory optimizations, and neural network accelerator design. His work bridges microarchitectural improvements and application-specific efficiency in multicore systems. Labs & Teams : Affiliated with the Computer Architecture and Parallel Systems research group, previously part of the Architecture and Parallel Computing group.

Jesus Joaquin Garcia Molinaمشاهده پروفایل

استاد

• Computer Science
• Database Systems
• Model-Driven Engineering
• +۵ مورد دیگر

Jesus Joaquin Garcia Molina is a Professor in the Department of Computer Science and Systems Engineering at the Universidad de Murcia's Faculty of Informatics. He holds a Doctorate from the same university with a thesis on the conformational and dynamic study of flexible macromolecules (1988). His research focuses on database systems, model-driven engineering, NoSQL technologies, and software modernization. He is actively involved in projects related to schema evolution, user interface generation from wireframes, and AI applications in healthcare and education. Key research areas include database schema management, cross-platform data migration, and the development of unified query languages like Skiql. He has contributed to frameworks such as Guizmo for automated UI generation and tools for reverse-engineering legacy systems. His work bridges theoretical computer science with practical applications in software development and education technology. Recent publications emphasize NoSQL schema evolution, AI-driven radiology support systems, and the integration of interactive educational content in social robots. His interdisciplinary approach spans computer science, medicine, and pedagogy, with notable contributions to both academic and applied domains.

• Haptic Perception
• Multisensory Integration
• Material Properties
• +۴ مورد دیگر

Dr. Anna Metzger is a Lecturer in Psychology at Bournemouth University since 2021. She holds a BSc in Biology from Hanover, MSc in Cognitive Science from Osnabrück, and a Dr. rer. nat. in Psychology from Justus-Liebig University Giessen. Her research focuses on haptic and visual perception, particularly object shape/material property encoding through active touch and multisensory integration. She uses motion/eye-tracking, computational modeling, and virtual/augmented reality. Research Interests include: Exploration strategies in tactile perception Unsupervised learning of material properties Neural correlates of haptic perception Computational modeling of tactile saliency Her work has been recognized with a Best Paper Award (2018) from the Eurohaptics Society. Current grants explore haptic texture synthesis and 3D shape perception. She teaches courses on cognitive neuroscience, experimental design, and statistics at both undergraduate and postgraduate levels. Grants : Synthesising Haptic Textures through Unsupervised Learning (British Academy, 2024-) Perception of objects’ 3D shape (Royal Society, 2024-) She collaborates internationally and serves as Associate Editor for IEEE Transactions on Haptics and Eurohaptics Conference Proceedings .