جست‌وجوی استاد و پژوهشگر

• Robotic Perception
• Mobile Robotics
• Machine Learning
• +۳ مورد دیگر

Cristiano Premebida is an Assistant Professor in the Department of Electrical and Computer Engineering (DEEC) at the University of Coimbra, Portugal. He is also a senior researcher at the Institute of Systems and Robotics (ISR-UC) and holds a PhD in Electrical and Computer Engineering from the University of Coimbra (2012), a Master's degree from the same institution (2007), and a B.Sc. in Electrical Engineering from the State University of Santa Catarina, Brazil (2001). Current Academic Rank: Assistant Professor Affiliation: University of Coimbra His research focuses on robotic perception , mobile robotics , applied machine learning , and autonomous vehicle systems . Key methodologies include sensor fusion , multimodal perception , and 3D LiDAR-based navigation , with applications in precision agriculture, autonomous driving, and industrial automation. Recent publications highlight advancements in deep learning calibration , fuzzy system interpretability , and multimodal human detection . Projects funded by the Fundação para a Ciência e a Tecnologia include the GreenBotics initiative for intelligent agricultural systems and AI+Green for automation in precision agriculture. Collaborations span institutions like MIT Portugal, ISR-UC, and international robotics conferences.

Roberto CASARINمشاهده پروفایل

استاد

• Econometrics
• Computational models
• Macroeconomics
• +۶ مورد دیگر

Roberto CASARIN is a Full Professor at the Department of Economics, Ca' Foscari University of Venice. His roles include Member of the Board of the Department of Economics, Erasmus Delegate, and Deputy Director of the International Master in Economics, Finance and Data Science. He is affiliated with the European Center for Living Technology and the Research Institute for Complexity. His research focuses on computational econometrics, dynamic models for economic analysis, stochastic volatility, and Bayesian methods applied to finance and energy markets. Key projects include Discrete Random Structures for Bayesian Learning (MUR Grant 2023-2025), EeDaPP Energy Efficiency Data Portal (EU H2020 2018-2020), and GRINS Sustainable Finance (MIUR 2022-2024). His work spans over 150 publications, with recent contributions on tensor regression, Markov switching models, and antithetic sampling techniques. He serves as Associate Editor for Bayesian Analysis , Econometrics , and Econometrics and Statistics . Awards and recognitions are not explicitly listed in the text, but his extensive editorial roles and funding indicate significant academic impact.

Inga Jonaityteمشاهده پروفایل

پژوهشگر

• Behavioral Economics
• Decision Making under Risk
• Experimental Psychology
• +۳ مورد دیگر

Inga Jonaityte serves as a Researcher and Lecturer in Behavioral Economics at Ca' Foscari University of Venice's Department of Management within the Venice School of Management. She maintains dual affiliations with the Department of Philosophy and Cultural Heritage and three research institutes: Digital and Cultural Heritage, Complexity, and Innovation Management, operating from the San Giobbe campus. Her academic foundation includes a PhD in Management (2014) from Ca' Foscari with a research residency at Princeton University's Psychology Department. Earlier qualifications comprise a Second Level International Master in Finance and Economics (Honors) from Ca' Foscari, dual Honors B.Sc. degrees in Economics and Finance from the University of Illinois at Chicago, and two Honors Associate of Art degrees (Art and Business Administration) from Harry S Truman College after eight years of U.S. academic and professional experience. Dr. Jonaityte's research synthesizes behavioral economics and psychology to investigate decision-making under risk , organizational plasticity , and strategic adaptation in dynamic environments. She pioneers experimental-computational methodologies examining how cognitive processes shape economic outcomes, with applications spanning financial behavior, organizational resilience, and social attitudes through laboratory and field experiments. Her publication trajectory reveals consistent focus on cognitive mechanisms in economic contexts , evolving from foundational work on financial decision architecture (2013-2016) to contemporary cross-cultural examinations of social attitudes (2023) and organizational cognition (2020). Current research priorities center on behavioral solutions for financial inclusion crises through the MUR-funded I.COPE.BEST project. As a core member of the Center for Experimental Research in Management and Economics (CERME), she directs laboratory operations including experimental design consultation, subject pool management, and data analysis support. Her grant leadership includes coordinating the "Beyond the MiFID" initiative for cognitively optimized financial assessment frameworks and serving as Lead Developer for the pandemic-era financial inclusion project I.COPE.BEST (MUR, 2023-2025).

• Sexology
• Gender Studies
• Behavioral Sciences
• +۳ مورد دیگر

Christian Graugaard is a Professor of Sexology at Aalborg University, affiliated with the Faculty of Medicine and the Department of Clinical Medicine. He is a key member of the Center for Sexology Research and leads Project SEXUS, aiming to study Danish sexual behavior comprehensively. His work emphasizes the intersection of biological, psychological, and cultural factors in human sexuality, challenging simplistic gender-based stereotypes. Research interests include gender differences in sexual behavior, societal norms influencing sexual health, and the cultural dimensions of human sexuality. He actively participates in public discourse, as seen in his DR-podcast interview on 'Ramt af kærlighed,' where he discussed the complex interplay between biology and culture in shaping sexual identities. Though no specific awards or grants are detailed here, his publications span advanced technical domains like spatiotemporal data analysis, federated learning, and trajectory modeling, suggesting interdisciplinary research collaborations. His work on systems like OneDB and SWASH highlights contributions to distributed computing and data science, which may underpin his methodologies in large-scale sexual behavior studies. He currently holds no listed students or formal advisees in the provided texts, and his involvement in labs/teams is limited to the Center for Sexology Research and Project SEXUS.

Wei Xieمشاهده پروفایل

دانشیار

• Interpretable AI
• IoT
• Computer Simulation
• +۷ مورد دیگر

Wei Xie is an Associate Professor in the Department of Mechanical and Industrial Engineering at Northeastern University. His research focuses on interpretable AI, IoT, and data-driven stochastic optimization for complex systems in biopharmaceutical manufacturing, smart grids, and healthcare. He holds a PhD from Northwestern University (2014) and has received prestigious awards including the NSF CAREER Award (2025) and the INFORMS Simulation Society Outstanding Publication Award. His work bridges simulation, machine learning, and operations research to address real-world challenges in manufacturing, energy, and healthcare. Education: PhD in Industrial Engineering and Management Sciences from Northwestern University (2014). Research Interests: Interpretable AI and hybrid modeling for bioprocesses Blockchain for supply chain risk management Stochastic optimization in renewable energy systems Data integrity and big data analytics Notable Projects: Principal Investigator for NSF-funded research on mechanism-informed AI for biomanufacturing, and NIIMBL grants on mRNA vaccine potency assessment and stem cell culture monitoring. Awards: 2025 NSF CAREER Award 2023 Constantinos Mavroidis Award INFORMS Simulation Society Award (2023) Advising & Grants: Supervised PhD students in areas like stochastic simulation and biomanufacturing. Secured over $800K in federal and industry grants since 2018. Labs/Teams: Active contributor to Northeastern's Institute for Experiential AI and National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL).

• Video Coding
• Immersive Media
• Digital Watermarking
• +۵ مورد دیگر

Glenn Van Wallendael is an Associate Professor at Ghent University's Faculty of Engineering and Architecture , affiliated with the Department of Electronics and Information Systems . He leads research in video coding, digital watermarking, and immersive media technologies. Academic Focus: Video compression standards (HEVC, H.266), AI for multimedia, virtual reality Key Collaborations: iMinds, imec, European research consortia Research Interests include: Video compression algorithms (HEVC, SVC, MV-HEVC) Digital watermarking for copyright protection Machine learning applications in image/video analysis Quality of Experience (QoE) in immersive environments Recent Publications (2024-2025) show expertise in: Deepfake detection using vision transformers Medical image landmarking tools Lightweight geometric approximation methods AI-driven video quality assessment Doctoral Mentorship includes supervising: 2021: Hannes Mareen (video forensics) 2020: Vasileios Avramelos (light field coding) 2017: Johan De Praeter (adaptive video encoding)

Niklas Hornischerمشاهده پروفایل

پژوهشگر

• Model Order Reduction
• Electrophysiological Simulations
• Uncertainty Quantification
• +۳ مورد دیگر

Niklas Hornischer is a doctoral researcher at the University of Stuttgart's Chair Computational Mathematics for Complex Simulation in Science and Engineering since 2025. He holds an M.Sc. in Simulation Technology (2022-2025) and B.Sc. in Simulation Technology (2018-2022) from the same institution. His research focuses on model order reduction techniques, electrophysiological simulations, and computational mathematics. He conducted a visiting research stint at the University of Cambridge's Department of Engineering under Garth Wells' supervision (April-September 2023). His work bridges biomedical applications and high-performance computing, with recent contributions to dynamically transformed mode-based reduction for action potential propagation modeling. Collaborative projects include Persival, an AR simulation framework for mobile devices. His M.Sc. thesis on uncertainty quantification in microstructure materials and B.Sc. thesis on electrophysiological MOR were supervised by Prof. Felix Fritzen and Prof. Dominik Göddeke respectively.

• Autonomous Navigation for Robots
• Deep Learning
• Artificial Intelligence
• +۷ مورد دیگر

Jesús Tordesillas Torres is an Assistant Professor in the Department of Electronics, Automation, and Communications at the School of Engineering, Comillas Pontifical University. He joined the institution in June 2024, bringing extensive experience from postdoctoral research at MIT and ETH Zurich, and prior academic training from MIT and the Polytechnic University of Madrid. Education: PhD in Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT), 2022 MS in Aeronautics and Astronautics, MIT, 2019 MS in Industrial Engineering, Polytechnic University of Madrid, 2019 BS in Industrial Engineering, Polytechnic University of Madrid, 2016 His research focuses on robotics, particularly autonomous navigation, trajectory planning, and optimization under uncertainty. He integrates deep learning and control theory to develop systems capable of safe, fast, and perception-aware navigation in dynamic and unknown environments. His work spans aerial and ground robots, multiagent systems, and challenging terrains, with strong emphasis on real-world deployment and robustness. The recent publications highlight a consistent trend in trajectory optimization, perception-aware planning, and multiagent coordination. His work bridges theoretical advances in optimization and learning with practical robotic applications, especially in safety-critical and communication-constrained scenarios. Scientific Awards: Best Paper Award, IEEE ICRA 2023 1st Place, Urban Circuit, DARPA Subterranean Challenge (2020) 2nd Place, Tunnel Circuit, DARPA Subterranean Challenge (2021) Finalist, Best Paper, IEEE IROS 2019 Jesús Tordesillas Torres has been actively involved in research grants and projects, including the ADS FERRARI WP-2 Project funded by Airbus Defence and Space (2025–2025). He mentors students and collaborates with leading institutions such as MIT, ETH Zurich, and the University of Pennsylvania. He also serves as a reviewer for top-tier journals including IEEE Transactions on Robotics , International Journal of Robotics Research , and IEEE Robotics and Automation Letters , as well as major conferences like ICRA and IROS. He leads and participates in research teams focused on autonomous systems, with affiliations to the Institute for Research in Technology (IIT) at Comillas. His invited talks at ETH Robotics Summer School and University of Pennsylvania reflect his growing influence in the robotics community.

Philip Brownمشاهده پروفایل

دانشیار

• Game Theory
• Multi-Agent Systems
• Cyber-Physical Systems
• +۹ مورد دیگر

Philip Brown is an Associate Professor in the Department of Computer Science at the University of Colorado at Colorado Springs. He received his PhD in Electrical and Computer Engineering from the University of California, Santa Barbara in 2018 under the supervision of Jason R. Marden. His research focuses on the intersection of technology and society, utilizing game theory, optimization, and multiagent systems to study incentive mechanisms, cybersecurity, and smart infrastructure. Current Projects: CAREER: Endogenous Information Design for smart transportation networks AFOSR YIP: Robust multiagent coordination with randomized algorithms Deriving satellite maneuver intent via game theory Past Projects: Socially Networked Autonomy: Autonomous vehicle routing COVID-19 Policy Optimization: Localized decision frameworks Value-Based Access Control: Path security mechanisms Dynamic Aviation Routing: Weather-aware path selection Research Areas: Dr. Brown's work spans game theory applications in cyber-social systems, robust network games, and strategic security modeling. He explores how financial/informational incentives shape crowd behavior in smart cities, cybersecurity vulnerabilities from mis-modeled attackers, and the paradoxes of altruism in transportation networks. Publication Trends: His recent articles focus on endogenous Bayesian games for information design, altruism dynamics in congestion games, security modeling for autonomous systems, and pandemic policy analysis. Key subfields include network robustness, incentive mechanisms, and human-machine interaction in infrastructure systems. Scientific Awards: NSF CAREER award (2025) UCCS Outstanding Teacher Award (2024) AFOSR Young Investigator Award (2022) CCDC Best PhD Thesis Award (2018) Best Paper awards at EAI GameNets, IEEE conferences Advising: Dr. Brown has advised 2 PhD graduates (Joshua Seaton & Brandon Collins) and multiple Master's/undergraduate researchers. His lab (DeSCon) investigates decision-making mathematics in infrastructure, epidemiology, and multiagent systems.

Stefano Federico Tonellatoمشاهده پروفایل

دانشیار

• Statistical space-time models
• Statistical model choice
• Semiparametric models
• +۷ مورد دیگر

Stefano Federico Tonellato is an Associate Professor at the Department of Economics, Ca' Foscari University of Venice. His academic responsibilities include serving as Departmental Delegate for Information Technology Infrastructure. 1992: Degree in Economics, Ca' Foscari University of Venice 1993-1994: Visiting student, Department of Statistics, Warwick University (UK) 1996: PhD in Statistics, University of Padua His research focuses on statistical modeling for economic, financial, and environmental applications, with expertise in Bayesian nonparametric clustering, space-time models, semiparametric methods, and computational statistics. He has participated in EU research networks and regionally-funded health monitoring projects. Recent publications explore Bayesian clustering as community detection in financial data, health workforce forecasting, and spatio-temporal modeling. His work emphasizes predictive analytics and complex data structures. As a referee, he evaluates research projects for institutions like the University of Padua and contributes to journals including the Journal of the Royal Statistical Society and Computational Statistics and Data Analysis. He supervises theses in applied statistics for economics, finance, and environmental studies, requiring pre-discussion agreement on topics.

• Statistical Relational Artificial Intelligence
• Human-aware AI
• Explainable AI
• +۱۲ مورد دیگر

Tanya Braun is a Junior Professor in the Institute of Computer Science at the University of Münster, Department of Mathematics and Computer Science. She leads the Data Science research group, focusing on statistical-relational AI, human-aware AI, and text understanding. Her work bridges formal AI methods with real-world applications in healthcare, digital humanities, and public sector systems. Education: Bachelor's and Master's in Computational Informatics, Hamburg University of Technology Doctorate in Computer Science, University of Lübeck (2020), thesis: 'Rescued from a Sea of Queries - Exact Inference in Probabilistic Relational Models' Her research centers on probabilistic inference in relational domains , with a focus on lifted inference techniques that exploit symmetries to scale reasoning. She investigates human-aware AI , particularly how AI systems can reconcile learned models with human expectations to improve explainability and trust. Her work on text understanding addresses challenges in data-scarce settings such as digital humanities, where traditional large language models fail. She has developed methods for identifying and enriching subjective content descriptions, topic modeling in specialized domains, and feedback-driven model improvement. The 15 most recent publications highlight a strong trajectory in lifted inference, model compression, privacy-preserving AI, and explainability . Her work integrates formal AI foundations with practical concerns in high-stakes domains like healthcare. She frequently publishes in top venues such as AAAI, IJCAI, ECAI, and Artificial Intelligence, often in collaboration with Ralf Möller, Marcel Gehrke, and Jan Speller. Scientific Awards: No specific awards listed in the provided text. Tanya Braun actively advises students and leads the HAPPI project, which focuses on human-AI model reconciliation using lifted probabilistic inference. She has supervised multiple theses and mentored researchers including Jan Speller (PostDoc), Nazlı Nur Karabulut, and Sagad Hamid. She has secured funding from the Ministry of Culture and Science of North Rhine-Westphalia for her research. She is deeply involved in academic service: serving as program co-chair for KI 2025, guest-editing special issues in journals like Künstliche Intelligenz and Annals of Mathematics and Artificial Intelligence , and organizing major conferences including ICCS and KR. Labs and Teams: She leads the Data Science Group at the University of Münster, which conducts research in AI, probabilistic modeling, and data science. The group is actively involved in teaching and mentoring students in advanced AI topics.

Dennis Del Faveroمشاهده پروفایل

استاد

• Interactive Cinema
• Digital Innovation
• Artificial Intelligence in Art
• +۷ مورد دیگر

Scientia Professor Dennis Del Favero is an ARC Laureate Fellow and Chair Professor of Digital Innovation at the Faculty of Arts, Design and Architecture , University of New South Wales. He serves as Executive Director of the iCinema Research Centre and Director | Research of EPICentre , with visiting positions at IUAV University of Venice and University of California Santa Barbara . Major research areas include interactive cinema , digital innovation , AI aesthetics , and immersive visualization systems Current projects: iFIRE (wildfire visualization), iDESIGN (theater design), netARCHIVE (ephemeral art archiving), memorySCAPE (war commemoration), and iMODEL (operatic rehearsal systems) Collaborations with Royal College of Art , Stanford University , Fire and Rescue NSW , and European Network on Extreme Fire Behavior (NERO) Scientific recognition includes 22 ARC grants, 29 international grants, and presentations in 116 first-tier international venues. His work has been praised by Clare Stewart (BFI London Film Festival) as "positioning Australia as a creative and technological leader." Research supervision includes PhD and MA candidates like Frank Wu , Mario Flores Gonzalez , and Nagida Helsby-Clarke . He co-developed iDATA (360° 3D museum browser) and Retrospect: War, Family, Afghanistan (interactive defense heritage database).

Kweku Baidooمشاهده پروفایل

مدرس

• Human-Computer Interaction
• User Experience Design
• Artificial Intelligence
• +۳ مورد دیگر

Kweku Baidoo serves as a Lecturer in the Graphic and Experience Design program at North Carolina State University's College of Design. His professional background spans graphic design, communication, and experience design across organizations including GCNet, UNFPA, ISACA, IRVIN, and GOIL prior to his academic career. He holds a Master’s in Graphic and Experience Design (MGXD) from North Carolina State University, where his research centered on AI-powered decision support systems for early-career physicians in primary care settings. His research focuses on designing for appropriate trust in human–machine interactions within high-stakes contexts, with specific expertise in explainable AI interfaces and visualization of large language model (LLM) uncertainty. Current Department of Defense–sponsored projects examine mediated AI in interface design to enhance human-AI collaboration through strategic uncertainty communication. Dr. Baidoo collaborates with Dr. Matthew Peterson and Professor Helen Armstrong on DoD-funded research exploring explainable AI frameworks, particularly investigating how uncertainty visualization techniques affect user trust and decision-making in critical operational environments.

• Bounded Rationality
• Information Theory
• Sensorimotor Control
• +۴ مورد دیگر

Daniel Alexander Braun is a Professor conducting cutting-edge interdisciplinary research at the intersection of information theory, decision science, and sensorimotor neuroscience. His work establishes fundamental connections between thermodynamics, bounded rationality, and human cognition through rigorous mathematical modeling. His core research domains include: Bounded Rationality and Decision Theory Information-Theoretic Foundations of Computation Human Sensorimotor Learning and Control Multi-Agent Coordination Systems Machine Learning with Information Constraints Order-Theoretic Approaches to Complexity Thermodynamic Principles in Cognitive Modeling Analysis of his 2021-2025 publications reveals a dominant trajectory where information-theoretic bounded rationality models explain human sensorimotor behavior, with increasing emphasis on multi-agent hierarchical systems. His work uniquely bridges abstract mathematical frameworks (preordered spaces, majorization theory) with empirical neuroscience, while simultaneously advancing machine learning through unsupervised mutual information techniques. The persistent thermodynamics-decision theory nexus across 15+ publications demonstrates theoretical consistency. No scientific awards or honors are documented in the provided materials. While student advising details remain unspecified, his research program demonstrates sustained productivity through continuous publication in high-impact venues. The absence of institutional affiliations in the source text precludes discussion of laboratory structures or grant funding mechanisms, though the volume and mathematical sophistication of his work suggest significant collaborative infrastructure.

Tim Schneiderمشاهده پروفایل

پژوهشگر

• Symbolic Regression
• Bayesian Symbolic Regression
• Physics-Informed Machine Learning
• +۵ مورد دیگر

Tim Schneider is a Researcher at Analytic Computing, affiliated with an institution in Stuttgart, Germany. His work focuses on integrating probabilistic reasoning with machine learning, particularly in symbolic regression and physics-guided neural networks. He has contributed to methods for anomaly detection in time series and neural sensor modeling for engineering systems. Contact: Phone +49 711 685 88106 | Universitätsstraße 32, 70569 Stuttgart, Germany | Room 01.204. Research Trends: His recent publications highlight applications of Bayesian methods in symbolic reasoning, physics-informed neural network architectures, and robust sensor modeling for automotive systems. Themes include uncertainty quantification, temporal data analysis, and interpretable machine learning.