جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Qian WANG is a Lecturer at the Faculty of Law of Université de Montréal, contributing to both teaching and interdisciplinary research. Her work bridges legal education with advanced computational methods, though her recent publications primarily focus on artificial intelligence and computer science. Research interests span a broad spectrum including artificial intelligence, machine learning, natural language processing, and computer vision. Her work often intersects with systems-level challenges such as operating system control and cognitive modeling, demonstrating a unique interdisciplinary approach. Publications reflect a trajectory from foundational contributions in graph theory and saliency detection (2020-2021) to cutting-edge advancements in large language models and reasoning frameworks (2023-2025). Key themes include improving AI capabilities through dynamic reasoning mechanisms and exploring the ethical dimensions of autonomous systems. No academic awards or grants are explicitly noted in the provided materials, though her prolific publication record indicates active research engagement. She currently holds no listed advisees or doctoral supervision roles. Labs or collaborative teams associated with her research are not detailed in the available information.

• Software Engineering
• Data Analytics
• Mining Software Repositories
• +۵ مورد دیگر

**Ahmed Hassan** is a **Professor** and **Canada Research Chair (Tier 2) in Software Analytics** at the **School of Computing**, **Queen's University**, affiliated with the **Faculty of Arts and Science**. He holds the **NSERC/RIM Industrial Research Chair in Software Engineering for Ultra Large Scale Systems**. His research focuses on software systems, data analytics, and mining software repositories (MSR), leading the **Software Analysis and Intelligence Lab (SAIL)**. **Education**: PhD (2005), MMath (2001), BMath (1999) in Computer Science from the University of Waterloo, Canada. **Research Interests**: Software evolution, performance engineering, distributed systems debugging, cybersecurity, and AI-driven software solutions. SAIL explores tools for maintaining large-scale software systems, improving developer productivity, and integrating AI into software workflows. **Awards & Recognition**: ACM and IEEE Fellowships, patents in multiple jurisdictions, and leadership roles in MSR and ICSE conferences. Industrial experience includes RIM/BlackBerry, IBM Research, and Nortel Networks. **Current Projects**: Focus on foundation model-powered software (FMware), AIOps, and ethical AI applications. Teaching courses like CISC322: Software Architecture.

Petter Wallenténمشاهده پروفایل

مدرس ارشد

• Building Physics
• Energy Efficiency
• Moisture Management
• +۳ مورد دیگر

Petter Wallentén is a Senior Lecturer in the Division of Building Physics at Lund University , part of the Faculty of Engineering (LTH). His research focuses on heat and mass transfer in buildings, energy efficiency, and moisture safety. He emphasizes integrating research with teaching, advocating for balanced academic practices. Key areas include hygrothermal analysis, building materials performance, and sustainable construction methods. Wallentén contributes to UN Sustainable Development Goals related to climate action and affordable clean energy. His work spans scales from millimeter-level material analysis to district heating systems. He collaborates widely on Nordic water damage statistics and preventive measures, with projects funded by entities like the Swedish Energy Agency and FORMAS. He is affiliated with LTH Profile Areas in Aerosols and Circular Building Sector. Recent projects include improving sustainability by reducing water damage costs and advancing the Urban Arena initiative. No scientific awards are explicitly listed in the provided materials. His teaching and advising roles are integral to his work, though specific student names are not fully detailed here. Research projects span 2014 to ongoing, emphasizing holistic approaches to building safety and energy efficiency.

Matthew Larsonمشاهده پروفایل

دانشیار

• Criminal Justice Policy Evaluation
• Youth Justice
• Violence Prevention
• +۳ مورد دیگر

Matthew Larson is an Associate Professor and Director of Implementation at the Center for Behavioral Health and Justice (CBHJ) within Wayne State University's School of Social Work. He holds a Ph.D. from Arizona State University (2013) and specializes in criminal justice policy evaluation, youth justice, and violence prevention. His research has been funded by entities like the National Institute of Justice and National Science Foundation, focusing on topics such as recidivism, mental health integration in criminal justice systems, and community-based interventions. Dr. Larson leads the CBHJ's implementation science initiatives, ensuring projects align with evidence-based frameworks. He co-founded JUST POETRY, an annual event fostering dialogue on justice through poetry, and spearheaded the Inside-Out Prison Exchange Program at Detroit Reentry Center. His teaching includes courses like 'Violence Prevention and Intervention' and 'Lifespan Development in the Social Context.' Education: Ph.D., Arizona State University, 2013 Awards: CLAS Excellence in Teaching Award, Early Career Excellence Award (ASU), and multiple diversity-focused recognitions Grants: NIJ, NSF, Public Welfare Foundation, Michigan Justice Fund His work bridges academia and practice, emphasizing data-driven solutions for communities impacted by mental illness, substance use disorders, and systemic inequities within the criminal/legal system. He collaborates with law enforcement, policymakers, and grassroots organizations to advance behavioral health and justice reform.

• Natural Language Processing
• Computational Linguistics
• Information Extraction
• +۳ مورد دیگر

Gábor Recski is a computational linguist and postdoctoral researcher at TU Wien's Faculty of Informatics, affiliated with the Data Science Research Unit. He holds a PhD and previously served as an assistant professor at the Budapest University of Technology. His research focuses on natural language processing (NLP), particularly computational semantics and transparent information extraction. He teaches courses such as Natural Language Processing and Information Extraction, and supervises students at BSc, MSc, and PhD levels. His work includes over 50 peer-reviewed publications and projects like BRISE-Vienna (2019–2025) and Honeypot LLM: Creation of a Scam Conversation Dataset. Roles: PostDoc Researcher, Substitute Member of Faculty Council, Substitute Member of Curriculum Commission for Business Informatics Education: PhD (previous role at Budapest University of Technology) Research Interests: Transparent information extraction, semantic modeling, legal text analysis, and explainable AI His research projects span legal corpus construction (e.g., BRISE-plandok), offensive text detection, and AI applications in legal research. He actively contributes to conferences like ACL, EMNLP, and SIGIR. Supervised students have explored topics ranging from explainable prediction models to graph-based relation extraction.

El Mahdi El Mhamdiمشاهده پروفایل

استادیار

• Robust Distributed Learning
• AI Safety
• Cybersecurity of AI
• +۵ مورد دیگر

El Mahdi El Mhamdi is an Assistant Professor of Mathematics and Data Science at École Polytechnique, where he co-chairs the Master of Science program in Data Science and Machine Learning. His research focuses on the robustness of distributed learning systems and AI safety, with notable contributions to Byzantine-resilient algorithms like Bulyan and Krum. These algorithms are deployed in industrial settings such as WeBank and IBM's Federated Learning Library. He has authored four papers featured in the US NIST 2024 report on Adversarial Machine Learning as state-of-the-art defenses. Education: Grew up in Morocco with a bachelor-level background in physics, mathematics, and philosophy. Pursued studies in France, Germany, and Switzerland through scholarships, including a PhD in Computer Science from EPFL. His thesis on Robust Distributed Learning received the 2020 Best Computer Science PhD distinction and was shortlisted for a cross-departmental award. Research Interests: Robustness of biological networks (e.g., neural, gene-regulatory systems) and distributed machine learning systems under adversarial conditions. Advocates for ethical AI governance and has published a book on AI safety with Lê Nguyên Hoang, translated into multiple languages. His work addresses societal impacts of AI, including misinformation and data poisoning. Awards: Includes France’s top 100 scientific inventors (2025), VentureKick award (2020), and recognition from Global Voices Online, Thomson Reuters, and Google for freedom of speech advocacy. Legal actions ongoing against Moroccan authorities due to threats and harassment. Grants & Service: Co-authored research plans totaling $1.2M in grants. Served as a reviewer/PC member for top conferences (NeurIPS, ICML, ICLR). Supervised multiple master’s theses at EPFL, fostering talent in distributed computing and AI safety. Labs/Teams: Active in collaborative projects like Tournesol (trustworthy human judgments) and Aksel (Byzantine-resilient SGD). Engages in public outreach through podcasts, radio interviews, and science communication initiatives.

Mihai Surdeanuمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۲ مورد دیگر

Mihai Surdeanu is an Associate Professor in the Department of Computer Science at the University of Arizona. His academic work focuses on advancing natural language processing and machine learning techniques, with a particular emphasis on large language models, information extraction, and model efficiency. He can be reached at msurdeanu@arizona.edu. Research Interests: Natural Language Processing Machine Learning Deep Learning Information Extraction Artificial Intelligence Scientific Trends: His recent work explores critical challenges in large language models, including data contamination detection, adversarial perturbation defense, quantization methods, and reasoning robustness. Publications highlight techniques like prompt chaining, layerwise optimization, and speculative generation to improve model performance and interpretability.

• Responsible AI
• Software Engineering
• Machine Learning
• +۳ مورد دیگر

Mr. Boming Xia is a Research Fellow at the Responsible AI Research Centre (RAIR) and the Australian Institute for Machine Learning (AIML), University of Adelaide. He holds a position within the Faculty of Sciences, Engineering and Technology. His research focuses on advancing responsible and safe AI through a software engineering lens, particularly exploring the integration of system-level practices with machine learning approaches. His work emphasizes ethical AI development, including frameworks for risk assessment, ESG (Environmental, Social, Governance) integration, and blockchain-based accountability mechanisms. Key areas of interest include AI safety, privacy protection in generative AI, and the design of transparent software supply chains using tools like SBOM (Software Bill of Materials). Xia's contributions span empirical studies on SBOM adoption, AI system evaluation frameworks, and tools like CDCAT for cross-document entity and event coreference. His research bridges theoretical AI foundations with practical software engineering methodologies to ensure AI systems are both innovative and ethically grounded.

• Property Law
• International Private Law
• Real Estate Law
• +۵ مورد دیگر

Dr. Katarzyna Dadańska is an Assistant Professor at the University of Szczecin's Faculty of Law and Administration, specializing in Property Law and International Private Law. She holds a doctoral degree in civil and commercial law from the same institution (2004), focusing on 'The Action of a Legal Person in Civil Law Relations.' Her academic contributions include a monograph on corporate legal actions and co-authorship of the 'Civil Code Commentary.' Education & Academic Roles: PhD in Civil & Commercial Law (2004), University of Szczecin Assistant Professor since 2005 Head of Research Team for Legal Protection of the Family Member of University Quality Education Team and Law Department Team Research Interests: Focuses on property rights, real estate transactions, international inheritance law, family law conflicts, and legal aspects of construction investments. Her work bridges national and EU legal frameworks, particularly in cross-border property disputes and succession law harmonization. Professional Engagement: Legal Counsel since 2005 Notarial Chamber trainer (Szczecin) Former Vice-Dean for Full-Time Studies (2012-2016) Member of Polish Economic Society's Board and Higher Vocational School Oeconomicus (2005-2012) Teaching: Leads courses in Property Law, Family Law, Real Estate Law, and International Private Law at both undergraduate and postgraduate levels. Labs/Teams: Oversees the Legal Protection of the Family research team and participates in interdisciplinary projects through the German Law School Team and University's Legal Analysis Center.

• Privacy-Preserving Machine Learning
• Reinforcement Learning
• Data Privacy and Security
• +۵ مورد دیگر

Associate Professor Kee Siong Ng is affiliated with the School of Computing at the Australian National University (ANU). His research focuses on privacy-preserving technologies, reinforcement learning, distributed systems, and blockchain applications. He has contributed extensively to areas such as privacy-preserving machine learning, federated learning, entity resolution, and scalable database systems. His work emphasizes balancing computational efficiency with privacy guarantees in data-driven environments. Key research contributions include methodologies for secure data processing in federated learning frameworks, privacy-preserving reinforcement learning for population-level systems, and blockchain-based digital identity solutions. He has led projects like Integrated Graph Analytics and contributed to initiatives involving the Australian Medicare dataset. His research often intersects theoretical foundations with practical implementations, addressing challenges in scalability and real-world applicability. Ng has published over 24 peer-reviewed articles, with notable works appearing in venues like IEEE Transactions on Parallel and Distributed Systems and Transactions on Machine Learning Research . His articles frequently explore cutting-edge topics such as differential privacy, approximation algorithms, and multi-agent systems. Collaborations include industry partnerships and interdisciplinary efforts involving health informatics and financial intelligence. His projects include Integrated Graph Analytics (2018–2021): Focused on scalable graph-based data analysis. Translational Fellowship (2018–2022): Bridging theoretical research with practical applications. Research on Data Sets for Health and Pharmaceutical Schemes (2020): Analyzing Medicare and pharmaceutical data with privacy safeguards. Ng's work prioritizes ethical AI and privacy-by-design principles, with a focus on real-world deployment challenges in distributed and federated systems.

Catherine Brinsonمشاهده پروفایل

استاد

• Advanced Materials
• Polymers
• Nanostructured Materials
• +۵ مورد دیگر

Catherine Brinson is the Sharon C. and Harold L. Yoh III Distinguished Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University. She holds the Pratt School of Engineering affiliation and has served in academic leadership roles, including Department Chair and Associate Dean at Northwestern University. Her research focuses on advanced materials, with an emphasis on polymer-based nanostructured systems, interfacial mechanics, and integrating data science into materials discovery. Brinson earned her B.S. from Virginia Tech (1985), and M.S. and Ph.D. from Caltech (1986, 1990). Her work bridges experimental and computational methods, leveraging atomic force microscopy (AFM) and machine learning to study material behavior at nanoscale to bulk levels. Key projects include developing FAIR (Findable, Accessible, Interoperable, Reusable) data frameworks for materials research and optimizing 3D-printed metamaterials. She has pioneered methods like Dynamic Scanning Indentation (DSI) for polymer characterization and contributed to the MaterialsMine initiative for data-driven material design. Brinson's awards include the A.C. Eringen Medal (2022), AAAS Fellowship (2020), and Nadai Medal (2014). Her lab’s innovations span from smart textiles to computational modeling of nanocomposites. Collaborative efforts in materials informatics, such as the MaRDA initiative, underscore her commitment to interdisciplinary and open-science practices. Her grants include NSF CAREER Awards and industry collaborations. The Brinson Lab at Duke trains researchers in materials science, data science, and advanced characterization techniques, emphasizing FAIR data principles and AI integration.

Xuan Wangمشاهده پروفایل

استادیار

• Natural Language Processing
• Data Mining
• AI for Sciences
• +۷ مورد دیگر

Xuan Wang is an Assistant Professor in the Department of Computer Science at Virginia Tech, affiliated with the Sanghani Center for Artificial Intelligence and Data Analytics. She holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (UIUC), with additional M.S. degrees in Statistics and Biochemistry from UIUC, and a B.S. in Biological Science from Tsinghua University. Her research focuses on Natural Language Processing (NLP), Data Mining, AI for Sciences, and AI for Healthcare, emphasizing applications in complex reasoning with LLMs, multi-modal science foundation models, and healthcare informatics. Her work has been recognized through awards including the Nvidia Academic Grant (2025), Cisco Research Award (2025), and NSF NAIRR Pilot Award (2024-2025). She has organized workshops at ACL, VL/HCC, and ICDM, and serves on program committees for top conferences like NeurIPS, EMNLP, and KDD. Xuan's research spans scientific text mining (e.g., knowledge extraction from biomedical literature), multi-agent LLM systems for clinical triage, and foundational models for multi-omics data analysis. Her lab actively collaborates with institutions like Children’s National Hospital and the Fralin Biomedical Research Institute, with funding from NSF, CCI, and industry partners. Education: Ph.D. in Computer Science, UIUC (2022) M.S. in Statistics, UIUC (2017) M.S. in Biochemistry, UIUC (2015) B.S. in Biological Science, Tsinghua University (2013) Grants & Awards: NVIDIA Academic Grant (2025) – Small LLM Agent Systems Cisco Research Award (2025) – Complex Reasoning with LLMs NSF NAIRR Pilot (2024-2025) – Multi-omics Analysis Lab & Teams: Wang Lab focuses on AI-driven biomedical research, including single-cell omics analysis, brain signal interpretation, and LLM-based scientific discovery. Collaborations include the Virginia Tech Presidential Postdoctoral Fellowship program and industry initiatives like the Amazon + VT Center for Efficient ML.

• Invasive Plant Ecology
• Forest Management
• Extension Education
• +۳ مورد دیگر

Christopher W Evans serves as a Forestry Extension and Research Specialist within the Department of Natural Resources and Environmental Sciences at the University of Illinois, focusing on practical solutions for natural resource challenges across the Midwestern United States. His research expertise encompasses: Invasive plant ecology and management (garlic mustard, cogongrass) Forest regeneration dynamics, particularly Quercus alba (white oak) Extension education methodologies including KAP surveys Tickborne disease awareness among agricultural workers Seed viability assessment of invasive species Risk assessment frameworks for invasive plants Analysis of his publication history (2006-2024) reveals a consistent emphasis on field-applicable research, with recent work addressing tickborne disease knowledge gaps among extension professionals and herbicide timing for invasive species control. His collaborative approach is evident in projects with state agencies like the Georgia Invasive Species Task Force. No scientific awards are documented in the available materials. Information regarding student mentorship or grant funding remains unspecified in the provided documentation. While specific laboratory affiliations aren't mentioned, his work demonstrates strong partnerships with state-level natural resource management entities.

Øystein Linneboمشاهده پروفایل

استاد

• Philosophical Logic
• Philosophy of Mathematics
• Metaphysics
• +۷ مورد دیگر

Øystein Linnebo is Professor of Philosophy at the University of Oslo, affiliated with the Department of Philosophy, Classics, History of Art and Ideas (IFIKK) within the Faculty of Humanities. He has held previous academic positions at Birkbeck College, University of London, the University of Bristol, and research fellowships at Oxford and Oslo. He received his PhD from Harvard University in 2002 and an MA in Mathematics from the University of Oslo in 1996. Professor of Philosophy, University of Oslo (2012–present) Professor, Birkbeck, University of London (2010–2012) Lecturer and Reader, University of Bristol PhD, Harvard University (2002) MA, Mathematics, University of Oslo (1996) His research centers on philosophical logic, philosophy of mathematics, metaphysics, and philosophy of language, with a particular focus on abstractionism, plural logic, the nature of infinity, and Fregean semantics. Linnebo’s work investigates the ontological status of mathematical objects, the logic of plural reference, and the philosophical implications of potential versus actual infinity. He employs a broadly Fregean methodology, connecting metaphysical questions to logical and linguistic analysis. His recent publications and books, such as The Many and the One and Thin Objects , have significantly advanced debates on plural logic and abstractionism. His article 'Actual and Potential Infinity' was recognized as one of the ten best philosophical articles of 2019. His research projects include the ERC-funded C-FORS and the RCN-funded 'Infinity and Intensionality', reflecting his sustained engagement with foundational issues in logic and metaphysics. Linnebo has received several major honors: ERC Advanced Grant (2022) for C-FORS Nansen Prize for Excellence in Science (2022) University of Oslo Research Prize (2023) Member of Academia Europaea and the Norwegian Academy of Science and Letters (since 2014) He has served in academic leadership roles, including Head of Research at IFIKK (2021–2023) and member of the Department Board (2013–2020). He is an editor of the Bulletin of Symbolic Logic and serves on the editorial boards of Inquiry , Philosophia Mathematica , and SATS . His research group, Logic at the University of Oslo, fosters collaboration in philosophical logic and related fields. He has supervised numerous graduate students and continues to lead cutting-edge research on the intersection of logic, metaphysics, and intentionality.

• Financial analysts' forecast accuracy
• Real estate investment
• Accounting quality
• +۳ مورد دیگر

Associate Professor Chee Cheong is affiliated with the University of Adelaide as an Associate Professor and Head of Finance & Banking Discipline at the Adelaide Business School . He has extensive teaching experience in Finance courses at both undergraduate and postgraduate levels across Adelaide, China, and Singapore. Research Interests His research focuses on financial analysts’ forecast accuracy , real estate investment , and accounting quality , with publications in top-tier journals such as the Journal of Financial and Quantitative Analysis and Urban Studies . Recent work explores sustainability in automobility, biodiversity risk, fintech impacts, and corporate governance. Scientific Awards 2011 Awards for Excellence Publications Analyzed 15 most recent publications (2006–2025) reveal trends in financial forecasting, real estate dynamics, fintech, corporate social responsibility, and risk management. Articles frequently intersect finance, accounting, and environmental/social policy.