جست‌وجوی استاد و پژوهشگر

Jinyang Zhengمشاهده پروفایل

استادیار

• AI for Business
• Moderating Content Platforms
• Managing Two-sided Platforms
• +۵ مورد دیگر

Jinyang Zheng is an Assistant Professor of Information Systems at Simon Business School, specializing in AI-driven business transformation and digital platform moderation. His research focuses on leveraging causal inference, structural modeling, and unstructured data analysis to address challenges in two-sided platforms and digital resilience. Education: Ph.D. in Business Administration, University of Washington Foster School of Business B.S. in Statistics, Fudan University Research Interests: His work spans AI for business, moderating content platforms, managing two-sided markets, and digital resilience strategies. Recent studies explore AI's role in shelf monitoring, information sharing in ride-hailing, and the impact of editorial reviews on UGC platforms. Publications: Zheng’s work appears in top journals like Management Science , Information Systems Research , and MIS Quarterly . His recent research investigates live commerce sustainability, autonomous vehicle impacts, and privacy policies in misinformation monitoring. Awards: 2023 Gordon Davis Young Scholar Award (INFORMS) Jay Ross Young Faculty Award (Purdue University) Simon School Teaching Honor Roll Outstanding Teacher at Purdue University Teaching & Advising: Known for excellence in teaching courses like social media analytics and machine learning for business. No formal advisee list is publicly disclosed. Labs/Teams: Active in platform economics and AI governance research clusters at Simon Business School.

Thierry Peynotمشاهده پروفایل

دانشیار

• Robotics
• Perception
• Sensor Data Fusion
• +۹ مورد دیگر

Associate Professor Thierry Peynot is affiliated with the Queensland University of Technology (QUT) , specifically within the School of Electrical Engineering & Robotics in the Faculty of Engineering . He holds a PhD from the Institut National Polytechnique de Toulouse , France. His research focuses on robotics, perception, sensor data fusion, computer vision, autonomous systems, planetary rovers, mining robotics, and medical robotics , with a strong emphasis on terrain traversability analysis and resilient navigation in challenging environments. His professional roles include serving as Associate Editor for the IEEE Robotics and Automation Letters (RA-L) and involvement in prestigious conferences such as IEEE International Conference on Robotics and Automation (ICRA) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . He has contributed to national robotics initiatives, including co-chairing the Resources section of Australia's National Robotics Roadmap (2018 & 2020). Thierry’s research has led to advancements in autonomous navigation, particularly in dense vegetation, underground mining, and planetary exploration. His work includes developing systems like ForestTrav for forest terrain analysis and LookUP for underground localization. He has supervised over 15 PhD and Master’s students, focusing on topics such as medical robotics, autonomous navigation, and sensor fusion. Key achievements include awards for conference organization, editorial contributions, and leadership in robotics standardization. His lab, the QUT Centre for Robotics , drives innovations in robotics for industry, space, and healthcare.

Dimitrios Kogiasمشاهده پروفایل

عضو هیئت علمی

• Blockchain and Distributed Ledger Technology
• Cloud Integration
• Security in the Internet of Things (IoT)
• +۳ مورد دیگر

Dimitrios Kogias is an Adjunct Lecturer and Senior Researcher at the Department of Electrical & Electronics Engineering, University of West Attica, Greece. He is affiliated with the CoNSeRT Research Lab, contributing to national and EU-funded projects like TRILLION, STORM, and FASTER HORIZON-2020. His expertise spans blockchain technology, cloud integration, IoT security, and privacy in networked environments. He holds a Ph.D. from the National and Kapodistrian University of Athens (2010), focusing on information dissemination algorithms in unstructured networks. Education Ph.D., National and Kapodistrian University of Athens (2010) M.Sc. in Electronics and Radioelectrology (2004) Diploma in Physics (2001) Research Interests His work emphasizes blockchain applications in next-gen networks, secure IoT systems, edge cloud performance, and decentralized identity management. He has co-authored publications in international journals, conferences, and book chapters, with a focus on practical implementations in smart cities, emergency response, and educational technologies. His projects include OPTORER (dynamic routing services) and MORSE (deep learning for search-and-rescue operations). Grants & Projects Contributed to HORIZON-2020 projects FASTER (emergency response tools) and STORM (cultural heritage IoT). Led research in OPTORER and DESMOS (smart infrastructure security). Collaborated on TRILLION (citizen security services) and Climate Change Communication initiatives. Labs & Teams Primary affiliation with CoNSeRT Lab at UniWA. Active in DESMOS and FASTER consortia, focusing on smart infrastructure and emergency response ecosystems.

Sonia Haiducمشاهده پروفایل

دانشیار

• Software Engineering
• Program Comprehension
• Source Code Search
• +۴ مورد دیگر

Sonia Haiduc is an Associate Professor in the Department of Computer Science at Florida State University (FSU). Her research focuses on software engineering, particularly software maintenance, evolution, program comprehension, and source code search. She holds a Ph.D. (2013) and M.Sc. (2009) from Wayne State University, and a B.Sc. (2006) from Babeș-Bolyai University in Romania. **Education:** Ph.D. in Computer Science, Wayne State University, 2013 M.Sc. in Computer Science, Wayne State University, 2009 B.Sc. in Computer Science, Babeș-Bolyai University, 2006 **Research Interests:** Software Engineering Methodologies Source Code Analysis Empirical Software Engineering Video Tutorials for Software Learning Developer Communications Human Factors in Software Development Her service contributions include organizing key conferences like IEEE International Conference on Program Comprehension (ICPC) and chairing roles in workshops such as Mining Unstructured Data (MUD). She has been recognized with awards including the Google Anita Borg Scholarship and multiple ACM SIGSOFT travel awards. **Grants & Labs:** Director of the SERENE Group at FSU National Science Foundation Award CCF-1526929 (2015–2018): Focuses on text retrieval in software engineering Teaching spans courses like Software Engineering II and Graduate Software Engineering, with extensive TA experience in foundational computer science courses.

Adam Celarekمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Physically Based Rendering
• Deep Learning for 3D Data
• +۴ مورد دیگر

Adam Celarek is a PreDoc Researcher and University Assistant at the Computer Graphics department (E193-02) within the Faculty of Informatics at Vienna University of Technology. He holds the position of Scientist in the Rendering and Modeling workgroup and serves as a PhD student. Celarek teaches courses including Computer Graphics, Fundamentals of Computer Graphics, Seminar in Visual Computing, and Rendering. His research interests span Physically Based Rendering, Deep Learning for 3D data, Point Clouds, Gaussian Mixture Models, and Terrain Rendering. Celarek's work focuses on the intersection of computer graphics and machine learning, particularly in processing unstructured 3D data. He is currently working on deep learning applications for Gaussian mixture models and developing AlpineMaps, a navigation aid for alpinists in collaboration with Manuela Waldner. His publication record shows a consistent focus on rendering techniques and 3D data processing, with recent work emphasizing the application of deep learning to Gaussian mixture models and terrain visualization. The research demonstrates progression from foundational work on light transport algorithms to more recent applications in geospatial visualization and deep learning for 3D data. OCG-FÖRDERPREIS 2018 (with Christoph Weinzierl-Heigl) Celarek has supervised multiple student projects including Johannes Eschner's work on real-time avalanche risk visualization and Stefan Fraiss's research on Gaussian mixture models from point clouds. He is involved in the EVOCATION training network as a former Marie Skłodowska-Curie fellow and currently leads the High-performance triangle-mesh streaming for unbounded datasets project funded by netidee Projektförderung. As a member of the Rendering and Modeling workgroup, Celarek contributes to the department's research in physically based rendering, 3D data processing, and visualization techniques, with particular expertise in light transport algorithms and Gaussian mixture models.

Martin Smitsمشاهده پروفایل

دانشیار

• Information Systems Management
• Business Process Analysis
• IT Strategy
• +۸ مورد دیگر

Martin Smits is an Associate Professor at the Tilburg School of Economics and Management (TiSEM) within Tilburg University, specializing in Information Systems and Operations Management. He is affiliated with CentER (Center for Economic Research) and Tranzo (Research Institute for Transformation of Care and Wellbeing). Active in cross-disciplinary research across business, healthcare, and government sectors Develops models for analyzing technology's impact on organizational performance His research investigates how IT innovations affect business processes in organizations and networks. Key areas include: Business process analysis and redesign Supply chain integration and networkability Electronic markets and intermediary development System dynamics modeling for predictive analysis Applications in E-Health, E-Government, and Fintech Publications show focus on technological architectures (SOA), enterprise content management strategies, and business network optimization. Notable work includes modeling FinTech's impact on financial services and analyzing service-oriented technologies in German banking networks. Supervises PhD students in topics spanning healthcare dynamics, IT risk management, and business network performance. Previously held roles include Program Manager at TIAS Business School and clinical positions at Groningen University.

Mahdi Imaniمشاهده پروفایل

استادیار

• Machine Learning
• Control Theory
• Learning Theory
• +۳ مورد دیگر

Mahdi Imani is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, with a courtesy appointment in the Khoury College of Computer Sciences. He holds a PhD in Electrical Engineering from Texas A&M University (2019), and MSc and BSc degrees in Electrical and Mechanical Engineering from the University of Tehran (2014 and 2012, respectively). His research focuses on machine learning, control theory, Bayesian statistics, and signal processing, with applications in gene regulatory networks, network security, and human-AI collaboration. Dr. Imani has received prestigious awards, including the NIH NIBIB Trailblazer Award (2022), the NSF CISE Career Award (2020), and the Outstanding Associate Editor Award from IEEE Transactions on Neural Networks and Learning Systems (2023 and 2024). He serves as an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Vehicular Technology, and is a Senior Member of IEEE. His research projects include DARPA-funded work on verified probabilistic reasoning in mixed reality systems, NSF-funded statistical inference methods, and ONR-funded studies on human-AI team synergy. He leads a lab focused on developing scalable Bayesian methods and reinforcement learning techniques for complex systems.

• Natural Language Processing (NLP)
• Computational Linguistics
• Artificial Intelligence
• +۱۱ مورد دیگر

Prof. Dr. Gülşen Cebiroğlu Eryiğit is a Professor at Istanbul Technical University (ITU) in the Department of Artificial Intelligence and Data Engineering under the Faculty of Computer and Informatics. As the founder and director of the ITU Natural Language Processing Group , she leads Turkey's foremost research team in Turkish-language NLP. Her work has achieved global impact through the first software export from ITU in NLP, with 6,000+ Google Scholar citations as of 2023. Education: MSc & PhD, Computer Engineering, ITU (2002-2007) BSc, Computer Engineering, Marmara University (1995-2000) High School: Saint-Michel (French curriculum) Her research focuses on natural language processing for morphologically complex languages like Turkish, with specializations in: Dependency parsing and treebank development Multilingual transfer learning systems Abstract meaning representation Language technology infrastructure Coreference resolution in agglutinative languages Gamification of linguistic education Recent publications show active research trends in: Transforming financial document analysis with BiLSTM-CRF architectures Advancing Turkish language models through ViBERTgrid implementations Developing multilingual frameworks under EU COST Actions Creating semantic search engines for job matching platforms Optimizing automotive demand management through dialogue systems Building large language models (LLMs) for Turkish Scientific recognition includes: Siemens Excellence Award (2007) for doctoral research Above Threshold Award (TÜBİTAK, 2015) EU 7th Framework Certificate of Appreciation (2012) ITU Thank You Plaque (2017) Current leadership roles: Senior Action Editor, ACL RR Director, ITU TÖMER (Turkish Language Teaching Center) Coordinator, ITU NLP Group Co-Chair, EU UniDive COST Action WG3 Principal Investigator on 3 active projects

Rémi Allègreمشاهده پروفایل

دانشیار

• Geometric Modeling
• Appearance Modeling
• Texture Synthesis
• +۶ مورد دیگر

Rémi Allègre is an Associate Professor in Computer Science at the Institute of Technology Haguenau (IUT Haguenau), affiliated with the University of Strasbourg (France). He conducts research at the ICube CNRS laboratory within the Geometric and Graphical Computing (IGG) group. Department: Multimedia and Internet Professions (Internet and multimedia technologies) Research Lab: ICube - UMR 7357, CNRS Contact: remi.allegre@unistra.fr | +33 (0)3 88 05 34 39 His research focuses on Geometric Modeling , Appearance Modeling , and Texture Synthesis , with applications in 3D data processing, procedural modeling, and biomedical imaging. Key trends include: Developing differentiable point process models for inverse procedural modeling Creating GAN-based data augmentation techniques for histopathological images Advancing semi-procedural texture synthesis methods Improving dynamic surface reconstruction algorithms Investigating hybrid representations (implicit surfaces, meshes, point sets) Multiscale label-map extraction for structured texture synthesis Scientific recognition includes: AFIG 2005 Best Article Award He supervises doctoral students such as Pascal Guehl, Florian Allender, Guillaume Baldi, Steve de Rose, and Maximilien Nowak. Collaborations span the ICube laboratory and biomedical imaging projects.

• Economics
• Monetary Policy
• Machine Learning in Economics
• +۴ مورد دیگر

Dr. Stephen Hansen is a Professor of Economics at University College London's Department of Economics. His research focuses on leveraging unstructured data to create novel economic measures, particularly in organizational economics and monetary policy. He co-organizes the AMLEDS webinar series exploring machine learning applications in economics and maintains a GitHub repository for methodologies in unstructured data analysis. His work is supported by an ERC Consolidator Grant. Research interests include text algorithms, large language models in economics, policy uncertainty, and remote work dynamics. He emphasizes high-resolution transaction data and computational linguistics for policy analysis, with a strong focus on central bank communication and its macroeconomic effects. Key contributions include studies on monetary policy lags, firm-level responses to shocks, and AI-driven regression techniques. His recent work explores the integration of machine learning with traditional economic frameworks, addressing ethical and methodological challenges. Awards include the prestigious ERC Consolidator Grant. He actively collaborates through initiatives like AMLEDS and shares tools via GitHub, fostering open methodology adoption in the field. His research bridges theoretical economics with practical applications in policy and organizational behavior.

Melissa Dellمشاهده پروفایل

استاد

• Development Economics
• Political Economy
• Economic History
• +۳ مورد دیگر

Melissa Dell is the Andrew E. Furer Professor of Economics at Harvard University's Department of Economics, part of the Harvard Faculty of Arts and Sciences. She holds affiliations with the National Bureau of Economic Research (NBER) as a faculty research fellow and the Canadian Institute for Advanced Research (CIFAR) as a Global Scholar in the Institutions, Organizations, and Growth program. Her research focuses on the interplay between state structures, non-state actors, and economic development, particularly in Latin America and Southeast Asia. Education includes a Ph.D. in Economics from MIT (2012), a Bachelor's degree summa cum laude from Harvard University (2005), and an M.Phil. with Distinction from the University of Oxford (as a Rhodes Scholar). Her research interests span Development Economics, Political Economy, and Economic History, with notable studies on drug violence in Mexico, colonial economic legacies in Peru and Vietnam, and the impact of historical state policies on current economic trajectories. Her work often integrates large-scale historical datasets and computational methods, such as digitizing archives and applying machine learning to analyze economic patterns over time. Recent research trends include developing frameworks for robust inference with unstructured data, historical news analysis, and computational tools for economic history (e.g., EfficientOCR, LinkTransformer). These projects emphasize bridging historical and modern data to understand long-term economic dynamics. Awards and honors include the Rhodes Scholarship and Harvard Society of Fellows Junior Fellowship. Her contributions span academic leadership, interdisciplinary collaborations, and policy-relevant economic analysis.

• Database Systems
• Information Extraction
• User Interface Design
• +۲ مورد دیگر

Dr Richard Cooper serves as an Honorary Research Fellow within the School of Computing Science at the University of Glasgow, maintaining an office at R403 Level 4, 10 Lilybank Gardens. His position signifies active research collaboration without full-time employment obligations, with contact facilitated through Richard.Cooper@glasgow.ac.uk. His research centers on database systems innovation, particularly: Context-aware information extraction from constrained textual sources (SMS, emails) Model-driven user interface development for object databases Integration of unstructured data with structured database schemas These efforts bridge theoretical database concepts and practical applications in natural language processing and interactive systems engineering. Publication analysis (2001-2005) reveals consistent focus on transforming informal communications into structured database inputs. His work avoids heavyweight NLP in favor of lightweight, domain-specific extraction techniques—enabling efficient data population in resource-constrained environments where traditional approaches would be impractical. Collaborative patterns indicate participation in multi-institutional projects like the Teallach framework development. While current grant funding isn't documented, his honorary status suggests ongoing contributions to the university's research ecosystem through specialized expertise rather than conventional academic service.

Sara Beeryمشاهده پروفایل

استادیار

• Computer Vision
• Artificial Intelligence
• Environmental Science
• +۳ مورد دیگر

Sara Beery is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Electrical Engineering and Computer Science and the Computer Science and Artificial Intelligence Laboratory (CSAIL). Her research focuses on leveraging computer vision for environmental sustainability and conservation challenges. Beery's work spans computational vision, self-supervised learning, and multimodal AI systems. She has contributed to advancements in neural latent dynamics, face recognition bias analysis, and spatio-temporal dataset creation for autonomy. Her recent publications emphasize computer vision applications in conservation, medical imaging, and robotics. Notable topics include synthetic image generation, denoising low-SNR video, and cell segmentation using foundational AI models. Scientific Awards Resnick Graduate Scholar

Johan Lithnerمشاهده پروفایل

استاد

• Mathematics Education
• Problem-Solving Strategies
• Cognitive Science
• +۷ مورد دیگر

Johan Lithner is a Professor in the Department of Science and Mathematics Education at Umeå University, Sweden. He is affiliated with the Umeå Mathematics Education Research Centre (UMERC) and leads the Learning by Imitative and Creative Reasoning (LICR) research group. His work focuses on mathematical reasoning, problem-solving strategies, and their cognitive and educational implications. Key research areas include analyzing how students engage with algorithmic vs. creative reasoning, the role of formative assessment, and the neurobiological basis of learning through studies using fMRI and eye-tracking technologies. He has contributed extensively to textbook analysis, teacher professional development, and curriculum design, emphasizing the importance of fostering deep understanding over rote learning. Dr. Lithner’s research spans over two decades, involving collaborations across disciplines such as cognitive psychology, neuroscience, and educational policy. His projects include evaluating the impact of national educational reforms, designing effective mathematics tasks, and investigating how teaching methods influence brain activity and long-term retention. He has led major grants addressing formative assessment mechanisms and the cognitive benefits of creative reasoning for students of varying abilities. Research Projects: Combatting detrimental lack of understanding in mathematics via formative assessment (2024–2028) LEARNING TO ENGAGE THE BRAIN (2014–2025) Podcasting in School (2008) His publications span peer-reviewed journals like Educational Studies in Mathematics and Frontiers in Psychology , focusing on empirical studies of learning processes and their applications in educational practice. Awards: No specific awards listed, though his sustained contributions to mathematics education research are widely recognized. Grants: Multiple grants from Swedish Research Council and EU frameworks, including projects on cognitive neuroscience and teacher training. Lithner’s work bridges theory and practice, influencing both academic discourse and classroom methodologies globally.

Richard Crowleyمشاهده پروفایل

استادیار

• Financial Accounting
• Text Analysis
• Voluntary Disclosure
• +۹ مورد دیگر

Richard Crowley is an Assistant Professor of Accounting at the School of Accountancy (SOA), Singapore Management University (SMU). He joined SMU in 2016 as full-time faculty, specializing in financial accounting research using archival and analytical methods, particularly leveraging high-powered computing for unstructured textual data analysis. His work addresses challenges in financial reporting, disclosure strategies, and market behavior. Education: PhD in Accountancy, University of Illinois Urbana-Champaign Bachelor's degrees in Accountancy, Finance, and Theoretical Mathematics, University of Illinois Urbana-Champaign (2012) Research Focus: Financial stability, investor behavior, stock market anomalies, text analysis, voluntary disclosure, and the intersection of accounting with artificial intelligence/machine learning. His interdisciplinary work spans corporate governance, auditing, econometrics, and social media regulation. Key Contributions: Pioneering use of NLP for detecting financial misreporting, analyzing social media's impact on corporate strategy and traditional media, and exploring CSR reputation management through Twitter analytics. Awards: Fellow of the Lindau Nobel Laureate Meetings (2014) University Fellowship, University of Illinois (2014, 2015) Professional Service: Reviewer for AAA Annual Meeting, Illinois International Journal of Accounting Symposium, FARS midyear meeting, and University of Illinois Symposium on Audit Research. Discussed at IAS midyear meeting (2014). Labs/Teams: Engaged in cross-disciplinary projects at SMU's School of Computing and Information Systems, focusing on AI applications for financial information scrutiny on platforms like Twitter.