جست‌وجوی استاد و پژوهشگر

• Information Visualization
• Network Visualization
• Human-Computer Interaction
• +۴ مورد دیگر

Claudio Linhares is a Senior Lecturer at Linnaeus University within the Department of Computer Science and Media Technology , Faculty of Technology in Växjö, Sweden. His work bridges theoretical research with practical applications in visualization and human-computer interaction. Teaching: Masters courses in Computational Network Analysis, Information Visualization, and Data Analysis Projects; Bachelor thesis supervision; Industry-focused Visual Analytics training Research: Focuses on information/network visualization, visual analytics, and human-in-the-loop AI with cross-sector applications in forestry and healthcare Projects: Leads the Smart Dat initiative for industrial digitalization and collaborates with the Information and Software Visualization (ISOVIS) research group His recent publications demonstrate interdisciplinary applications of visualization techniques, including fairness-aware urban planning tools and temporal network analysis frameworks. Current work explores topological persistence methods and augmented reality training systems for manufacturing SMEs. Linhares contributes to academic collaboration through active involvement in research groups and industry partnerships, while maintaining a teaching-focused role in both undergraduate and graduate programs.

Mariam Adedoyin-Oloweمشاهده پروفایل

مدرس

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

Mariam Adedoyin-Olowe is a Lecturer and Programme Leader for the MSc Artificial Intelligence at Birmingham City University . Her research focuses on Data Mining, Data Science, and Artificial Intelligence, particularly in analyzing social media data for event detection and decision-making support. Doctorate in Computing Science from Robert Gordon University First degree from University of Portsmouth Research Interests center on applying data mining techniques to Twitter data for tracking real-world events, sentiment analysis, and customer segmentation. Her work bridges computational methods with practical applications in politics, sports, and healthcare domains. Key Publications include studies on: Transformer-based transfer learning for cross-lingual news events AI-driven mental fatigue detection systems Temporal clustering methods for social media event resolution Deep learning approaches for sound classification Rule dynamics frameworks for political event detection Academic Affiliations include membership in BCU's Data Mining Group and Data Analytics & Artificial Intelligence Research Group, as well as former involvement with RGU's Data Science and Information Retrieval groups. She regularly reviews for international conferences and journals.

Johannes Scholzمشاهده پروفایل

استاد

• Geospatial Artificial Intelligence (GeoAI)
• Geospatial Knowledge Graphs
• Semantics and Ontologies in Geography
• +۱۲ مورد دیگر

Johannes Scholz is a Full Professor for Geoinformatics at the Department of Geoinformatics (Z_GIS) at Paris-Lodron-University Salzburg. He leads the GeoAI, GeoKG, and GeoSemantics research group and holds secondary roles in academic governance, including membership in the Curricularkommission Geographie at Salzburg and the Austrian Standards TC 084 committee. He has held visiting positions at the University of California, Santa Barbara, and prior affiliations include Associate Professor at Graz University of Technology and Senior Researcher at Research Studios Austria - Studio iSPACE. His research interests span geospatial artificial intelligence, knowledge graphs, semantics, and numerical optimization, with applications in energy transition, digital tourism, and cyber-physical systems. Projects include Agent-based simulation for energy systems GeoHumanities integration Indoor geography analysis Selected scientific awards include the ISPRS Outstanding Reviewer Award (2020) and the Forschungspreis der Steiermark (2011). He has secured significant funding for projects such as "Virtual Shepherd" (FFG 2024) and "ABM4EnergyTransition" (FFG 2022).

• Knowledge Representation
• Answer Set Programming
• Non-monotonic Reasoning
• +۵ مورد دیگر

Pedro Cabalar is Full Professor at the Department of Computer Science of the University of Corunna, Galicia, Spain, and current coordinator of the inter-university Master in Artificial Intelligence (Universities of A Coruña, Santiago de Compostela and Vigo). He also serves as Area Editor (Theory Foundations) for Theory and Practice of Logic Programming and as Standard Editor for the Artificial Intelligence journal. Education: PhD in Computer Science, University of Corunna, 2001 Master in Computer Science, Politéchnic University of Madrid, 1993 Bachelor in Computer Science (3-year degree), University of Santiago de Compostela / University of Corunna, 1989 Research interests revolve around Knowledge Representation & Reasoning , especially Answer Set Programming , non-monotonic reasoning , temporal and modal logics , and causal reasoning . He investigates theoretical foundations (equilibrium logic, temporal extensions, deontic operators) and practical systems (telingo, eclingo, aspBEEF), with applications ranging from planning and diagnosis to explainable AI and healthcare decision support. His recent articles (2023-2025) exhibit a clear trend toward temporal and metric extensions of ASP , explainability , and hybrid reasoning systems , often combining logic programming with deontic or probabilistic features. Scientific awards & recognition: University of Corunna Dissertation Award, 2003 Best Paper Award at LPNMR 2019 Best Student Paper at ICLP 2020 Best Student Paper at JELIA 2019 Grants & projects: He currently leads or co-leads nationally funded Spanish projects (GEISER 2024-2028, ARLEKIN 2021-2024) and has coordinated EU COST actions (DigForASP) as well as earlier MINECO projects on temporal ASP and medical reasoning (TARDIS, MERLOT, FEAST, etc.). PhD supervision: He has successfully supervised three PhD theses (Martín Diéguez, Jorge Fandiño, Brais Muñiz) and continues to advise students within the Information Retrieval Laboratory (IRLab) and the Spanish node of Potassco Solutions.

• Artificial Intelligence
• Strategic Reasoning in Multi-Agent Systems
• Formal Verification
• +۱۰ مورد دیگر

Aniello Murano is a Professor in Computer Science at the Department of Electrical Engineering and Information Technology of the University of Naples Federico II. He serves as Scientific Director of the ASTREA (Automated Strategic REAsoning) Laboratory and has been actively involved in numerous research projects including H2020-MSCA project SEAL as Principal Coordinator and PNRR Research Unit Coordinator on Resilient Strategic Reasoning in AI (2023-2025). His primary research interests focus on Artificial Intelligence, Formal Aspects for Strategic Reasoning in Multi-Agent Systems under Perfect and Imperfect Information, Specification, Verification, and Synthesis of Reactive Systems, Model Checking and Module Checking, Formal Languages, Automata Theory, Real-time Systems, Pushdown and Hierarchical Systems, Temporal and Modal Logics, Logics for Strategic Reasoning in AI, Game Theory, Parity Games, Solution Concepts, and Automated Mechanism Design. His work bridges theoretical computer science with practical applications in AI systems. Murano has published extensively in top-tier venues, with recent publications spanning KR, IJCAI, AAAI, AAMAS, and other premier conferences. His research shows strong trends in strategic reasoning frameworks, verification techniques for multi-agent systems, and applications of game theory to mechanism design. He has made significant contributions to Strategy Logic and its extensions. JPMorgan Faculty Research Award 2022 Best Paper Award PRIMA 2015 Vigevani Research Project Prize 2010 In KR Top 100, best AI-2000 world researchers Italian Scientific Abilitation as Full Professor in Engineering Computer Science (March 2018) Italian Scientific Abilitation as Full Professor in Computer Science (April 2017) Royal Society Award 2016 Murano has supervised numerous PhD students including Silvia Stranieri, Antonio Di Stasio, Vadim Malvone, and Giuseppe Perelli. He has served as Program Chair for major conferences including ECAI 2025 (Program co-chair), KR 2024 (Area chair), and CSL 2024. His research has been supported by significant grants including Horizon 2020 projects, JPMorgan funding, and Italian national research programs. He leads the ASTREA Laboratory focused on automated strategic reasoning and has been instrumental in establishing collaborative research initiatives with institutions worldwide.

François Briatteمشاهده پروفایل

استادیار

• Legislative networks
• Comparative health policies
• Sociology of social movements
• +۷ مورد دیگر

François Briatte is an Assistant Professor in Political Science at the Catholic University of Lille , affiliated with the European School of Political and Social Sciences (ESPOL). He serves as Co-Director of International Mobility and has previously taught at Sciences Po Paris, Grenoble, Reims, the University of Lille 2, and the University of Edinburgh. His research focuses on legislative networks in European parliaments and comparative health policies . He combines methodologies from network analysis, political sociology, and digital politics to study legislative collaboration patterns, electoral behavior, and healthcare system reforms. His work often addresses Political polarization Electoral turnout dynamics Open data governance Health policy analysis Recent publications include empirical studies on Voting indecision in the 2022 French presidential election Covid-19’s impact on 2020 French local elections Network visualization tools for political science Comparative analysis of legislative cosponsorship He has developed open-source software packages like GGally and ggnetwork for network analysis in R, and actively participates in academic conferences across Europe and North America.

Stephanie Balzerمشاهده پروفایل

استادیار

• Programming Languages
• Program Verification
• Type Theory
• +۷ مورد دیگر

Dr. Stephanie Balzer is an Assistant Professor in the Principles of Programming Group at Carnegie Mellon University's School of Computer Science. Her research focuses on enabling failure-free software through formal methods like type systems and verification logics. She emphasizes compositional proofs for scalability and practical validation via software artifacts. Programming Languages Type Theory Program Verification Concurrency & Security Her recent work explores timed protocols, disentanglement logic, and multiparty session types. Articles demonstrate semantic logical relations for termination (2025), deadlock freedom in Rust embeddings (2022), and information flow control (2024). Key collaborative papers address cyclic process networks and separation logic frameworks. Scientific recognition includes: NSF CAREER Award (2025) ACM SIGPLAN Distinguished Paper (2022) ECOOP Distinguished Paper (2022) She supervises PhD candidates Yue Yao, Yinsen Zhang, and Zak Kent (with Guy Blelloch), plus Master's student Sonya Simkin. Former advisee Jules Jacobs received Cum Laude distinction at Radboud University. Active in academic service, Balzer chairs PLMW@POPL workshops and co-organizes Oregon Programming Language Summer School. She serves on program committees for LICS, POPL, and ICFP.

• Robust Machine Learning
• Machine Learning for Graphs/Networks
• Machine Learning for Temporal and Dynamical Data
• +۳ مورد دیگر

Leon Hetzel is a Researcher at the Technical University of Munich, affiliated with the TUM School of Computation, Information and Technology and the Department of Informatics - I26, located at Boltzmannstr. 3, 85748 Garching b. München, Germany, Room: 00.11.052. Research Interests Robust Machine Learning Machine Learning for Graphs/Networks Machine Learning for Temporal and Dynamical Data Bayesian (Deep) Learning / Uncertainty Efficient ML Code

Jukka Suomelaمشاهده پروفایل

دانشیار

• Distributed Computing
• Distributed Algorithms
• Local algorithms
• +۷ مورد دیگر

Jukka Suomela is an Associate Professor in the Department of Computer Science at Aalto University, Finland. His research focuses on the theoretical foundations of distributed and parallel computing, with a strong emphasis on locality and algorithmic complexity. Current roles: Associate Professor, Aalto University Research group: Distributed Algorithms Key conferences: PC Chair for DISC 2019, SIROCCO 2016, Local Chair for ALGO 2018 Steering Committee: Vice Chair, DISC Research Interests include distributed algorithms, local algorithms, parallel computing, graph algorithms, and computational complexity. His work explores fundamental limits of distributed systems and the role of locality in algorithm design. Notable Scientific Awards : FOCS 2019 Best Paper Award DISC 2012 & 2017 Best Paper Awards MSc Thesis Award 2006, University of Helsinki Best Junior Researcher 2008, University of Helsinki Nokia Scholarship 2008 Teaching includes Programming Parallel Computers (freely available), CS-E4510 Distributed Algorithms, and other courses in the Finnish Computer Science major/minor programs. His publications span distributed systems theory, graph algorithms, and interdisciplinary projects in linguistics and cultural analytics.

• Data Modeling
• Data Security and Privacy
• Healthcare Data Management
• +۵ مورد دیگر

Faiz Currim serves as Professor of Practice in Management Information Systems and Assistant Director of the INSITE: Center for Business Intelligence and Analytics at the University of Arizona's Eller College of Management. He joined the institution in 2011 after six years at the University of Iowa, having earned his PhD from the University of Arizona in 2004. His educational background includes: PhD in Management Information Systems, University of Arizona (2004) Dr. Currim's research focuses on data modeling, security, privacy, and specialized management of healthcare, temporal, and spatial data systems. His work bridges database theory with practical applications in urban mobility, patient care, and workplace wellbeing through advanced techniques including deep learning, network science, and big data analytics. Current projects address real-world challenges in healthcare analytics and smart city infrastructure. Analysis of his recent publications reveals strong trends in applying artificial intelligence to healthcare cost prediction and urban transportation systems, with consistent use of heterogeneous data sources and machine learning frameworks across diverse domains from patient monitoring to bike-sharing optimization. His scientific recognition includes: Best Paper Award at IEEE 2nd International Smart Cities Conference (2016) Dr. Currim directs the INSITE center's initiatives in business intelligence while teaching core courses including Enterprise Data Management and Business Data Communications. His academic leadership spans curriculum development in data security, XML schema, and spatial database applications, with active collaboration across healthcare and urban planning domains. He maintains leadership roles in professional organizations including the Association for Information Systems (AIS), INFORMS, and Association for Computing Machinery (ACM), driving interdisciplinary research through the INSITE center's industry partnerships and analytics projects.

Paul Boniolمشاهده پروفایل

پژوهشگر

• Time Series Analytics
• Anomaly Detection
• Machine Learning
• +۲ مورد دیگر

Paul Boniol is a researcher at Inria, affiliated with the VALDA project-team—a collaboration between Inria Paris, École Normale Supérieure, and CNRS. His work focuses on time series analytics, anomaly detection, and machine learning applications. Ph.D. in Computer Science and Applied Mathematics (University of Paris, EDF R&D) Visiting Ph.D. at University of Chicago Education: Grenoble INP ENSIMAG Engineering School Research interests span: Unsupervised anomaly detection in large time series Time series management systems Machine learning for predictive maintenance Graph-based time series analysis Explainable AI for temporal data Recent publications emphasize advancements in: Weakly supervised anomaly localization Graph embedding techniques Model selection frameworks Interactive visualization tools Smart meter data analysis Scientific recognition: Paul Caseau Thesis Prize 2022 Lambdamu Congress Research-Industry Prize 2022 BDA & INFORSID Ph.D. Prizes 2022

Mary Lauren Bentonمشاهده پروفایل

استادیار

• Computational Biology
• Gene Regulation
• Biomedical Informatics
• +۳ مورد دیگر

Dr. Mary Lauren Benton is an Assistant Professor in the Department of Computer Science at Baylor University's College of Engineering and Computer Science. She holds a Ph.D. and M.S. in Biomedical Informatics from Vanderbilt University (2020, 2018) and a B.S.I. in Bioinformatics from Baylor University (2015). Education: Ph.D. (Vanderbilt, 2020), M.S. (Vanderbilt, 2018), B.S.I. (Baylor, 2015) Her research focuses on computational biology and gene regulation, particularly how DNA sequences influence genome function and human disease risk through integrated datasets. Recent work explores enhancer-gene interactions, epigenetic mechanisms, and the application of graph neural networks to genomic problems. Selected publications highlight interdisciplinary trends across genomics (e.g., Cis-regulatory landscapes , CTCF motif accessibility ) and computer science (e.g., Dynamic graph attention , Node classification ).

Stephanie Balzerمشاهده پروفایل

استادیار

• Programming Languages
• Type Theory
• Program Verification
• +۶ مورد دیگر

Stephanie Balzer is an Assistant Professor in the Principles of Programming Group at Carnegie Mellon University's School of Computer Science. She received her PhD from ETH Zurich under Thomas R. Gross and focuses on developing rigorous type systems and verification logics to build failure-free, secure software through compositional and practical methods. Education: PhD (ETH Zurich), Master's (University of Zurich), Semester Thesis (University of Zurich) Her research spans session types , logical relations , and separation logic to ensure correctness and security in concurrent systems. Recent work includes verifying timed message-passing protocols and disentanglement in type systems. Key publication trends include session-typed concurrency , noninterference , and deadlock freedom across programming languages, formal methods, and security domains. She has authored multiple distinguished papers at ECOOP and POPL. Scientific Awards: NSF CAREER Award, ACM SIGPLAN Distinguished Paper, ECOOP Distinguished Paper She advises PhD students including Yue Yao, Yinsen Zhang, and Zak Kent, and has supervised former PhD students like Jules Jacobs (now at Cornell). Her grants include NSF funding for IoT verification , heterogeneous applications , and real-time protocols .

Giovanni Maria Farinellaمشاهده پروفایل

استاد

• First Person (Egocentric) Vision
• Computer Vision
• Pattern Recognition
• +۱ مورد دیگر

Giovanni Maria Farinella is a Full Professor at the Department of Mathematics and Computer Science, University of Catania, Italy. He is the Founder Member of the IPLAB Research Group at University of Catania since 2005, an Associate Member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006, and an Associate Member of the Italian National Research Council since 2018. He serves as Scientific Advisor of the NVIDIA AI Technology Centre and board member of the CINI Laboratory of Artificial Intelligence and Intelligent Systems. Dr. Farinella obtained his degree in Computer Science (summa cum laude) from the University of Catania in 2004 and was awarded a Doctor of Philosophy (Computer Vision) from the same institution in 2008. He has obtained the National Scientific Qualification to Associate Professor in 2013-2014 and to Full Professor in 2018. His primary research interests focus on First Person (Egocentric) Vision, Computer Vision, Pattern Recognition, and Machine Learning. Dr. Farinella has pioneered research in egocentric video analysis, object interaction detection, activity recognition, and scene understanding from a first-person perspective. His work bridges theoretical computer vision with practical applications in industrial settings, healthcare, and cultural heritage sites. His recent publications demonstrate a clear trajectory toward more sophisticated, real-time egocentric vision systems capable of understanding complex human activities, anticipating actions, and detecting procedural mistakes through integration of visual analysis, gaze tracking, and large language models. Dr. Farinella has published extensively in top-tier computer vision venues, with his most recent work focusing on egocentric action anticipation, mistake detection in procedural tasks, and the integration of multimodal large language models with visual understanding. His research shows strong emphasis on practical industrial applications while advancing fundamental computer vision techniques. PAMI Mark Everingham Prize 2017 Intel's 2022 Outstanding Researcher Award Dr. Farinella has served as Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition - Elsevier, and International Journal of Computer Vision. He has held leadership roles as Area Chair for CVPR 2020/21/22/23, ICCV 2017/19/21/23, ECCV 2020, and as Program Chair of ECCV 2022. He founded and directs the International Computer Vision Summer School (since 2006) and the Medical Imaging Summer School (since 2014). As PI of the EGO4D project, he helped create one of the largest egocentric video datasets with over 3,670 hours of footage from 923 participants across 74 locations worldwide. His IPLAB research group leads multiple significant projects including VALUE, ENIGMA, and FIPEVIS, with strong industry collaborations.

• Autonomous Driving
• Computer Vision
• Robotics
• +۵ مورد دیگر

Holger Caesar is a tenured Assistant Professor at Delft University of Technology (TU Delft) in the Intelligent Vehicles Lab . He leads research on scalable approaches for autonomous vehicle perception, prediction, and data annotation, with a focus on sensor fusion, domain adaptation, and minimal supervision. His work has been cited over 15,000 times. Education PhD in Computer Vision, University of Edinburgh Prior studies at KIT Karlsruhe, EPF Lausanne, and ETH Zurich Research Interests span autonomous driving perception, weakly supervised learning, novel view synthesis (NeRFs), diffusion models, and collaborative perception. He emphasizes reducing reliance on manual annotations through active learning and partial labeling techniques. Recent Publications include work on 4D Gaussian Splatting, camera-radar fusion, open-set scene graph generation, and safety benchmarking. These reflect trends toward multi-modal perception, robust sensor fusion, and foundation models for scalable autonomous systems. Scientific Awards ELLIS Europe Scholar (2024) TU Delft Cohesion Grant (100k EUR, 2024) Climate Action Grant (30k EUR, 2024) TKI High Tech Systems Grant (502k EUR, 2022) AiNed XS Grant (80k EUR, 2023) Argoverse Scene Flow Challenge Winner (unsupervised track, 2024) Advising & Grants include EU Horizon funding for the MOSAIC project (1 PhD and 1 Postdoc, 2024), EU KDT Cynergie4MIE grant (450k EUR, 2024), and industrial collaborations with Bosch, Motional, and partners across Europe. Labs & Teams include the Intelligent Vehicles Lab at TU Delft and founding roles in Motional's Data Annotation, Autolabeling, and Data Mining teams. He co-organizes workshops at ICCV, CVPR, and NCCV, and leads the ELLIS Delft Unit seminar series.