جست‌وجوی استاد و پژوهشگر

Hussam N. Mahmoudمشاهده پروفایل

استاد

• Sustainable and Resilient Infrastructure
• Community Resilience
• Multi-Hazard Structural Engineering
• +۴ مورد دیگر

Hussam N. Mahmoud is the George T. Abell Professor in Infrastructure and Director of the Structural Laboratory at Colorado State University's Department of Civil and Environmental Engineering. He leads the SoPHIE Research Group , focusing on Sustainable and Resilient Infrastructure and Communities across three major research thrusts: community resilience quantification, multi-hazard structural performance, and deteriorated infrastructure lifecycle assessment. Key research areas include climate change adaptation , multi-hazard design , and life-cycle cost analysis for infrastructure subjected to earthquakes, wildfires, hurricanes, and climate-related deterioration. His work integrates machine learning (e.g., neural networks for wind damage prediction), hybrid simulation , and multi-resolution modeling of structural systems. Recent publications highlight interdependent recovery of healthcare/school networks , coastal community resilience to cyclones, and fatigue repair methodologies using fiber composites. Scientific Recognition Keynote speaker at international conferences (STESSA 2015, NEES Annual Meeting 2013) Invited to prestigious events: G7 One Health Summit , NASEM New Voices program Recipient of the George T. Abell Professorship, a distinguished academic honor Professional Leadership Chaired NASEM workshop on Natural Infrastructure Active in global collaborative frameworks through the InterAcademy Partnership Organizing committee member for triennial international academic conferences

• Action recognition
• Representational dynamics
• Conceptual knowledge
• +۳ مورد دیگر

Moritz Franz Nikolaus Wurm is a Researcher at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) at the University of Trento, Italy , where he leads the Action Concepts and Recognition Group since 2022. He completed his PhD in Psychology (magna cum laude) at the Max Planck Institute for Neurological Research and the University of Münster in 2011, followed by postdoctoral work at Harvard University and the University of Trento. Research Interests : Dr. Wurm specializes in action recognition , conceptual knowledge representation , and neural decoding using fMRI , MEG , and MVPA/RSA techniques. His work explores how contextual, social, and physical cues shape neural processing of actions and objects, with recent projects on dynamic RSA for temporal neural analysis. Scientific Awards : Fondo Italiano della Ricerca (FIS) Starting grant (2024-2029) Piano Nazionale di Ripresa e Resilienza (PNRR) PhD Grant (2023-2027) University of Trento Starting Grant Giovani Ricercatori (2021) DFG Research Fellowship (2014–2017) Best Abstract Award at CAOs Workshop (2014) Other Activities : He serves as a scientific advisor for the MEG Laboratory at CIMEC, organizes the Concepts, Actions, and Objects workshop series, and leads the CIMeC Colloquia Series. He is an ad hoc reviewer for journals like Nature Communications , NeuroImage , and Journal of Neuroscience .

Shanghong Xieمشاهده پروفایل

استادیار

• Machine Learning
• Network Analysis
• Precision Medicine
• +۱۲ مورد دیگر

Shanghong Xie is an Assistant Professor in the Department of Statistics at the University of South Carolina, College of Arts and Sciences. She is also a member of the Carolina Autism and Neurodevelopment (CAN) Research Center and the Institute for Mind and Brain (IMB), reflecting her interdisciplinary focus on statistical methods for neuroscience and public health. Dr. Xie earned her PhD in Biostatistics from Columbia University in 2019 and completed her postdoctoral training there. Her research centers on developing machine learning and generative models to tackle complex challenges in functional data analysis, network modeling, causal inference, and precision medicine. She applies these methods to neuroimaging (fMRI, DTI, EEG), genetic biomarkers, and public health data, particularly in mental health and neurological disorders. Her recent publications demonstrate a strong trajectory in methodological innovation with high-impact applications, including COVID-19 forecasting models adopted by the CDC, mediation analysis with neuroimaging, and personalized treatment regime estimation. The research trends highlight expertise in high-dimensional data, graphical models, and integrative learning across multi-modal biomarkers. American Statistical Association (ASA) Statistics in Imaging Section First Prize Student Paper Award American Statistical Association (ASA) Mental Health Statistics Section Best Student Paper Award International Conference on Health Policy Statistics (ICHPS) Student Travel Award Dr. Xie advises several graduate students and co-founded the Functional and Complex Data Analysis (FUNCODA) Working Group, fostering collaboration on advanced data modeling. She has been involved in significant grant-supported work, notably contributing to the CDC’s ensemble forecasting effort during the pandemic through her survival-convolution model. Her lab emphasizes computational statistics and open science, with code available on GitHub.

Elias N. Zoisمشاهده پروفایل

دانشیار

• Digital Signal Processing
• Image Processing
• Pattern Recognition
• +۴ مورد دیگر

Elias N. Zois is an Associate Professor in the Department of Electrical & Electronics Engineering at the University of West Attica, where he has taught since 2019. Previously, he held positions as Lecturer (since 2009), Assistant Professor (2015-2022), and Adjunct Professor at multiple institutions including the Hellenic Army Academy and Hellenic Police Academy. He received his B.Sc. (1994), M.Sc. (1997), and Ph.D. (2000) in Physics and Electronics Engineering from the University of Patras, Greece. His research focuses on digital signal processing , image processing , pattern recognition , and specialized applications in handwriting biometry and offline signature verification . Recent work extends to smart grid optimization , including load forecasting and non-technical loss detection using machine learning techniques. Analysis of his 15 most recent publications reveals strong interdisciplinary trends: 60% focus on advanced biometric verification using Riemannian geometry and metric learning, while 40% apply machine learning to energy systems. Key methodologies include sparse coding, manifold learning, and neural network ensembles, with consistent applications in security systems and smart grid resilience. He has led multiple funded projects including: BioControl (2021-2023): Experienced Researcher for biometric systems Ireact-NG (2018-2021): Experienced Researcher in smart grid technologies ESA SimSat Engine Enhancement (2011-2015): Theoretical Project Manager for aerospace simulations He directs research at the TELSIP Laboratory (Building Z, University of West Attica), specializing in signal processing and pattern recognition systems.

• Computational Neuroscience
• Robotics
• Machine Learning
• +۳ مورد دیگر

Florentin Wörgötter is a faculty member at the Department for Computational Neuroscience , Georg August University of Göttingen, Germany. His research bridges robotics , computational neuroscience , and machine learning , focusing on action prediction, neural networks, and human-robot interaction. Key Research Areas : Action segmentation, semantic decomposition of manipulation sequences, 3D object reconstruction, and sensor fusion for infant movement classification. Recent Trends : Combining task-dependent learning with optimal path search, using foundation models for graph-based action recognition, and improving CNN interpretability through influence functions. He collaborates extensively with researchers like Minija Tamosiunaite , Tomas Kulvicius , and Poramate Manoonpong , contributing to journals such as NeuroImage , Robotics and Autonomous Systems , and IEEE Transactions on Neural Networks . His work often integrates deep learning , semantic reasoning , and biologically inspired models for robotic applications.

Tzu-Wei Hungمشاهده پروفایل

استاد

• Philosophy of Cognitive Science
• Philosophy of Language
• Philosophy of Artificial Intelligence
• +۲ مورد دیگر

Tzu-Wei Hung is a Professor at the Institute of European and American Studies, Academia Sinica, Taiwan, since 2023. He serves as President of the Taiwan Philosophical Association (2024–2026) and has held roles as Assistant Research Fellow (2012–2017) and Associate Research Fellow (2017–2023) at the same institution. Education: PhD (2011) and MPhilStud (2007) in Philosophy from King’s College London; BA (1999) in Philosophy from National Taiwan University Academic Service: Editor-in-Chief for the Centennial Anthology of Taiwanese Philosophy Series (2018–present); Executive Editor of EurAmerica (2021–2022) Research Interests span: Philosophy of Cognitive Science Philosophy of Artificial Intelligence Taiwanese Philosophy Social Philosophy Philosophy of Language His article trends focus on predictive coding models, algorithmic fairness, cognitive warfare, and AI ethics. Collaborative works with Chun-ping Yen and others address equity, bias mitigation, and the intersection of technology with social policy. Scientific Awards include: Outstanding Research Award (2022–2023), National Science and Technology Council, Taiwan Special Outstanding Talent Award (2017–2023), Ministry of Science and Technology, Taiwan Taiwan Merit Scholarship (2005–2008), National Science Council, Taiwan

• RNA Processing
• Alternative Splicing
• Gene Expression Regulation
• +۵ مورد دیگر

Sherif Abou Elela is a researcher affiliated with the University of Sherbrooke and its Centre de recherche du CHUS . His work focuses on RNA processing, stability, and alternative splicing, with implications in cancer biology and gene expression regulation. Education: Postdoctorate, University of California, Santa Cruz (1997) PhD in Biology, University of Guelph (1994) BSc, University of Qatar (1987) Research Interests: RNA processing and stability in gene expression, splicing program modulation in cancer and stress, snoRNA biology, yeast RNA metabolism, and RNA-binding proteins. He explores how RNA decay and splicing mechanisms can inform mammalian models and human disease diagnostics. Article Trends: Recent work emphasizes snoRNA annotation tools (e.g., SnoBIRD), stress-induced splicing adaptations (cells resist starvation), yeast RNase III roles in gene regulation, and cancer-specific non-coding RNA interactions (e.g., H/ACA snoRNAs). Computational approaches (snoDB, SAPFIR, snoGloBe) and yeast as a model organism are recurring themes. Patents & Contributions: He holds patents for methods to reprogram splice site selection and cancer biomarker discovery. He organized the Ribo Club conference, indicating leadership in RNA research.

• Philosophy of Artificial Intelligence
• Cognitive Science
• Neuroscience
• +۳ مورد دیگر

Carlos Zednik is an Assistant Professor for Philosophy of Artificial Intelligence at Eindhoven University of Technology , affiliated with the Industrial Engineering and Innovation Sciences department. He leads the Eindhoven Center for Philosophy of AI and participates in the alignAI (ERC) and ROBUST AI (NWO) consortia. His work bridges philosophy with AI and neuroscience, focusing on explainable AI (XAI), mechanistic explanation, and cognitive modeling. Education: BSc in Computer Science and Philosophy, Cornell University MSc in Philosophy of Mind, University of Warwick PhD in Cognitive Science, Indiana University Bloomington Zednik’s research investigates philosophical questions about biological and artificial intelligence, emphasizing: Methodological principles in cognitive psychology and neuroscience Norms and best practices for XAI in machine learning Knowledge representation in transformer models and large neural networks His recent publications explore the integration of cognitive models into XAI, the role of Bayesian reverse-engineering in cognitive science, and the mechanistic explanation of network neuroscience. Zednik also contributes to international standardization efforts through ISO/IEC TS 6254 and DIN SPEC 92001 . Scientific Awards include fellowships from: DAAD Alexander-von-Humboldt Foundation StandICT Fellowship Zednik supervises PhD students Zeynep Kabadere , Michela Ghezzi , Céline Budding , Miriam Gorr , and Hannes Boelsen , while mentoring postdocs Manuel Barbosa de Oliveira and Philippe Verreault-Julien . His teaching spans philosophy of AI, ethics of machine learning, and decision theory, with innovation projects on generative AI in higher education.

• Audio and Speech Processing
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Serkan KESER is an Associate Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering and Architecture, Ahi Evran University, Turkey. He has been serving as a full-time faculty member since 2018 and previously served as Head of Department from 2018-2021. His educational background includes a PhD in Electrical and Electronics Engineering from Eskişehir Osmangazi University (2009-2018), a Master's degree in the same field from the same institution (2005-2008), and a Bachelor's degree in Electrical and Electronics Engineering from Mustafa Kemal University (1999-2005). Dr. KESER's research focuses on three main areas: Audio and Speech Processing : Including speaker identification, isolated word recognition, and speech coding techniques Signal Processing : With applications in fiber optic sensor systems and acoustic positioning Image Processing : Covering face recognition, image compression, and denoising techniques His recent publications demonstrate a strong trend toward integrating machine learning and deep learning approaches with traditional signal processing methods. He has made significant contributions in applying subspace methods to various domains including speech recognition, image processing, and sensor technologies. His work often bridges theoretical signal processing concepts with practical applications in areas like smart home systems, medical imaging, and environmental monitoring. Dr. KESER has successfully supervised five Master's students to completion, with thesis topics spanning deep learning applications for class attendance systems, photovoltaic systems, speaker identification, brain tumor classification, and speech-controlled robotic arms. He has led four research projects, including development of fiber optic motion sensors, smart home models using Arduino microcontrollers, and science outreach initiatives. His teaching portfolio includes advanced courses in digital image processing, artificial neural networks, digital signal processing, and machine learning at both undergraduate and graduate levels. Dr. KESER's research impact is reflected in his publication metrics: 30 total publications with 117 citations (h-index 5) through the UNIS system, 25 publications with 180 citations (h-index 6) on Google Scholar, and strong representation in Scopus and Web of Science databases.

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +۱ مورد دیگر

Giacomo Vitali is a Ph.D. candidate in Computer and Systems Engineering at the Politecnico di Torino , Department of Control and Computer Science (DAUIN), while also serving as a Lecturer at the same institution. His research focuses on Quantum Computing , Machine Learning , and Parallel and Distributed Systems . Education: M.Sc. in Physics of Fundamental Interactions (2018) from the University of Pisa Research: Pioneering hybrid quantum-classical algorithms for industrial applications, including BBQ-mIS and DEN models for graph problems and quantum hardware optimization Teaching: Contributing to courses on Quantum Hardware Design and Quantum Computing at the M.Sc. level, as well as undergraduate courses in Computer Science

Alireza Mohammadinodooshanمشاهده پروفایل

پژوهشگر ارشد

• Social Media Analysis
• User Engagement Dynamics
• Data Mining
• +۳ مورد دیگر

Alireza Mohammadinodooshan is a Postdoctoral Fellow at Linköping University's Department of Computer Science (IDA), Sweden, working within the Database and Information Technology (ADIT) research group. He contributes to the Wallenberg AI, Autonomous Systems and Software Program (WASP) – Sweden's largest individual research initiative – focusing on data-driven analysis of social media engagement dynamics across Twitter, Facebook, and Instagram platforms. His research centers on quantifying how political bias, news reliability, and content-agnostic factors shape temporal user engagement patterns. Key interests include social media analysis, user engagement dynamics, data mining, information systems, network science, and artificial intelligence, with emphasis on cross-platform comparative studies and algorithmic amplification effects in news consumption. Analysis of his 15 most recent publications reveals consistent focus on temporal modeling of engagement decay, multi-format content interaction (photos/videos/albums), and the interplay between news source characteristics and user behavior. His methodological approach combines large-scale dataset analysis with network theory to identify virality predictors and platform-specific engagement mechanics. No scientific awards were documented in available sources. No advising roles or research grants were referenced in the provided materials. He operates within the ADIT research group at Linköping University, which specializes in advanced database and information systems for the digital society. This group forms part of IDA's broader WASP-affiliated ecosystem focused on AI-driven autonomous systems, enabling interdisciplinary collaboration on large-scale data challenges in social computing.

• Representative method
• non-random samples
• public statistics
• +۲ مورد دیگر

Dr. Maciej Beręsewicz serves as a Professor in the Department of Statistics at Poznan University of Economics and Business (UEP), holding key institutional roles including Member of the Competition Committee for "Mini-grants for Research," University Evaluation Team, and Rector's Committee for Academic Teacher Awards. His office is located in Building C, Room 406, with contact email Maciej.Beresewicz@ue.poznan.pl and phone 61 854 36 80. His research centers on representative methods, non-random samples, public statistics, big data applications, and statistical package development. He specializes in methodological innovations for non-probability surveys, capture-recapture modeling, and integrating administrative/online data sources into official statistics frameworks. Recent publications demonstrate a cohesive trajectory in survey methodology, particularly calibration techniques for probability/non-probability sample integration, quantile estimation, and job vacancy analysis using online advertisements. His R packages ( nonprobsvy , singleRcapture ) operationalize these methods for practical statistical implementation. Prof. Beręsewicz maintains significant external engagements through the Central Statistical Office of Poland (Real Estate Price Statistics Team, Quality Group), Baltic-Nordic-Ukrainian Network on Survey Statistics (Scientific Committee), and international bodies including the International Association of Official Statisticians and International Association of Survey Statisticians.

• Organic Computing
• Evolutionary Algorithms
• Learning Classifier Systems
• +۶ مورد دیگر

Professor Jörg Hähner holds the Chair of Organic Computing at the University of Augsburg's Faculty of Applied Computer Science within the Institute of Computer Science. He leads a research team focused on evolutionary computation, self-organizing systems, and intelligent computing approaches. His educational background includes computer science studies at TU Darmstadt. His academic career progression shows steady advancement in the field of organic and self-organizing computing systems. Prof. Hähner's research spans multiple interconnected domains in computational intelligence. His primary focus is on Organic Computing, which involves developing systems that can adapt and self-organize in complex environments. Within this framework, he has made significant contributions to Evolutionary Algorithms, particularly Cartesian Genetic Programming and Learning Classifier Systems. His work explores how these techniques can be applied to real-world problems such as predictive maintenance, energy systems optimization, and industrial automation. The research demonstrates a strong emphasis on both theoretical foundations and practical applications of self-adaptive systems. An analysis of his recent publications reveals a strong concentration on evolutionary computation techniques, particularly Cartesian Genetic Programming variants and Learning Classifier Systems. His research group has been actively developing frameworks like CRust_GP and GRAHF to advance modular construction of evolutionary algorithms. There's a clear trend toward applying these techniques to industrial problems including predictive maintenance, resource allocation in networks, and energy management systems. The publications show consistent exploration of fundamental questions about algorithm behavior while maintaining strong connections to practical applications. Prof. Hähner leads an active research group with numerous PhD students and collaborators, including Karen Poloczek, Henning Cui, Victor Gerling, Dr. Michael Heider, Marco Hüller, Neele Kemper, Helena Stegherr, Jonathan Wurth, and Roman Sraj. His team regularly publishes in top-tier conferences and journals in evolutionary computation, intelligent systems, and industrial applications. The Organic Computing research group maintains a strong presence in both theoretical and applied research, with projects spanning from foundational algorithm development to industrial applications in manufacturing, energy systems, and network optimization. The group's work demonstrates a cohesive research vision centered on creating adaptive, self-organizing computational systems that can operate effectively in complex real-world environments.

Mark Baileyمشاهده پروفایل

استاد

• Computer Security
• Computer Architecture
• Embedded Systems
• +۲ مورد دیگر

Mark Bailey is the Robert and Pamela (Craig) Delaney Professor of Computer Science at Hamilton College, where he has served as Chair of the Department of Computer Science since 2011. He teaches foundational courses including Introduction to Computer Science, Data Structures, and Computer Organization, and pioneered the innovative course Secrets, Lies, and Digital Threats that pairs Hamilton students with high school classes for cybersecurity education. His educational background includes: Ph.D. in Computer Science from the University of Virginia M.C.S. from the University of Virginia B.S. from the University of Massachusetts Dr. Bailey's research bridges theoretical computer science and practical applications, with primary focus areas in computer security , embedded systems optimization , and compiler design . His work on mobile encryption architectures and fault-tolerant distributed systems demonstrates interdisciplinary innovation, while his educational initiatives like the high school cybersecurity outreach program reflect commitment to real-world impact. Recent publications show increasing emphasis on mobile security and interactive optimization tools for embedded environments. His publication trends reveal consistent exploration of security vulnerabilities across computing layers—from low-power mobile encryption to server protection models—with growing attention to educational applications of security research since 2008. The interdisciplinary nature of his work connects hardware architecture, software engineering, and pedagogical innovation. Key recognitions include: Three competitive National Science Foundation grants Two Microsoft Research grants National Research Council/Air Force Research Laboratory Faculty Fellowship Hamilton College's Richardson Award for Faculty Innovation Dr. Bailey has secured over $1.2M in external funding through NSF and Microsoft Research grants, and provided consultancy for the Air Force Research Laboratory and Assured Information Security. His academic service includes editorial leadership as Editor-in-Chief of ACM Inroads and membership on the Barry Goldwater Scholarship review committee. Campus leadership roles span the Information Security Review Board, High Performance Computing Advisory Committee, and multiple college governance bodies since 1997. He actively shapes academic infrastructure through committee work including the Committee on Information Technology (chaired 2003–2005) and Science Facilities Faculty Committee, while maintaining strong industry connections through conference organization for SIGPLAN and NYCWiC.

Mario Marques Freireمشاهده پروفایل

استاد

• Computer Systems and Networks
• Cloud Computing
• Computer Security and Privacy
• +۳ مورد دیگر

Mário Marques Freire is a Full Professor at the University of Beira Interior, where he serves as President of the Faculty of Engineering and Professor in the Department of Computer Science. He is also a Senior Researcher at Instituto de Telecomunicações, leading the Secure and Intelligent Networked Software Systems Lab. His academic qualifications include a Dr. habil. in Computer Science (2007) and Ph.D. in Electrical Engineering (2000) from the University of Beira Interior, complemented by an M.Sc. in Systems and Automation and B.Sc. in Electrical Engineering from the University of Coimbra. Freire's research spans Computer Systems and Networks, with specific expertise in Cloud Systems, Computer Networking, Security & Privacy, and AI applications. His work focuses on infrastructure virtualization, encrypted traffic classification, DDoS attack detection, and malware analysis. Recent publications demonstrate strong emphasis on cloud security, AI-enhanced defect prediction, and IoT security frameworks. He has received several scientific awards including multiple Conference Best Paper Awards and an ACM Certificate of Appreciation for his long-term contributions. Freire has supervised over 35 graduate students (10 PhD graduates) and led numerous research projects such as 'Towards the assurance of SECURity by dESIGN of the Internet of Things' (FCT/COMPETE/FEDER) and 'Cloud Computing Competence Center'. At the University of Beira Interior, Freire has held significant administrative roles including Vice-Rector (2020-2021), Director of Computer Science Services (2009-2013), and multiple terms as President of the Faculty of Engineering. He leads the Network Applications and Services research group at Instituto de Telecomunicações, focusing on secure networked systems.