Query Processing Professors and Supervisors in Netherlands

Luiz Boninoمشاهده پروفایل

دانشیار

University of TwenteNetherlands

Luiz Bonino is an Associate Professor at Leiden University Medical Center and an International Technology Advisor at GO FAIR International Support and Coordination Office. He holds a PhD in Computer Science from the University of Twente (2011), specializing in semantic service provisioning. His research focuses on ontology engineering, semantic interoperability, and FAIR data principles, with applications in healthcare and distributed data systems. Key research interests include ontology development, cybersecurity in data systems, service-oriented computing, and the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) principles across domains. He contributes to initiatives like the Personal Health Train architecture and the FAIR Data Point framework, emphasizing distributed data platforms and metadata standards. Recent publications highlight work on large language models for ontology creation, interoperability challenges in healthcare data, and methodological frameworks for FAIRification. Bonino has organized conferences like the 2024 FOIS workshop and contributed to datasets such as the FAIRDataTeam/FAIRDataPoint project. He actively promotes FAIR principles through workshops and collaborative projects.

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Evangelos Kanoulasمشاهده پروفایل

استاد

University of AmsterdamNetherlands

Evangelos Kanoulas is a Professor at the Informatics Institute, University of Amsterdam. He holds a PhD in Computer Science from Northeastern University, Boston, USA (2010). His research focuses on information retrieval, machine learning, natural language processing, and conversational systems. He has made significant contributions to topics such as adversarial attacks in retrieval systems, knowledge-enhanced recommendation, and large language model applications in legal and product search domains. Education: PhD in Computer Science (Northeastern University, 2010). His work often bridges theory and practice, addressing challenges in robust retrieval, conversational AI, and multimodal systems. He has organized workshops such as ALTARS (Augmented Intelligence in Technology-Assisted Review Systems) and KEIR (Knowledge-Enhanced Information Retrieval), highlighting his role in advancing interdisciplinary research. Research interests include adversarial machine learning, conversational search, and AI-driven systems for legal and e-commerce domains. His recent work explores efficient training of large language models, robustness against typos, and generative models for query rewriting. His publications span top venues like SIGIR, ECIR, and ACL, with a focus on practical applications of NLP and IR. Despite no explicit mention of awards, his prolific publication record and leadership in organizing conferences reflect his academic impact.

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Jan-Christoph Kaloمشاهده پروفایل

عضو هیئت علمی

Vrije University AmsterdamNetherlands

Dr. Jan-Christoph Kalo is a Visiting Fellow in Artificial Intelligence at Vrije Universiteit Amsterdam. His research focuses on language models for knowledge base construction and natural language processing. He co-organizes the LM-KBC Challenge and contributes to advancements in query processing systems.

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Ali Satvatyمشاهده پروفایل

پژوهشگر

University of GroningenNetherlands

A. (Ali) Satvaty is a PhD researcher at the University of Groningen's Faculty of Science and Engineering, affiliated with the Bernoulli Institute's Information Systems department. His research focuses on privacy and safety aspects of large language models (LLMs), particularly within the LESSEN project developing low-resource conversational assistants. He holds an MSc and conducts interdisciplinary work at the intersection of AI ethics, data privacy, and natural language processing. Education: MSc in Computer Science (specific institution unspecified). Research interests emphasize secure AI architectures, LLM memorization risks, and multimodal emotion recognition. His work bridges theoretical computer science with practical applications in conversational systems and privacy-preserving machine learning. Publications highlight trends in LLM memorization analysis, speech-to-text modality conversion for emotion recognition, and transformer-based dialogue systems. Collaborations include multi-disciplinary teams within the Bernoulli Institute. No scientific awards explicitly listed, though ongoing projects suggest potential future recognitions. Advising and grants: No formal student advisement listed. His doctoral work is part of the LESSEN project, funded by institutional resources. Engages in lab activities related to conversational AI and security-focused NLP research.

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Silvia Stopponiمشاهده پروفایل

پژوهشگر

University of GroningenNetherlands

Silvia Stopponi is a PhD student at the University of Groningen's Faculty of Arts, working within the Computational Linguistics department under the supervision of Professor Malvina Nissim and Dr. Saskia Peels-Matthey. She holds an MA in Philology, Literature and Classical Tradition from the University of Bologna (2020), where she graduated with highest honors (110/110 e lode), and a BA in Humanities (Classics Curriculum) from the same institution. Her research focuses on the intersection of Digital Humanities and Computational Linguistics, specifically applying Natural Language Processing techniques to Ancient Greek language and texts. Stopponi's work centers on semantic change detection in ancient Greek, particularly within religious contexts, using computational methods and language models. She has developed significant research tools including AGALMA (Ancient Greek Accessible Language Models for linguistic Analysis), which allows non-programmers to query Ancient Greek language models, and contributed to AGILe , the first lemmatizer for Ancient Greek inscriptions. Stopponi is also an active organizer of academic events, notably the Computational Approaches to Ancient Greek and Latin workshop, now in its third edition (2024). Principal Investigator for AGALMA project Co-developer of AGILe lemmatization system Organizer of Computational Approaches to Ancient Greek and Latin workshop Her recent publications demonstrate a strong research trajectory in applying cutting-edge NLP techniques to classical languages, with particular emphasis on semantic analysis, lemmatization, and making computational tools accessible to humanities scholars without programming expertise.

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Peter Kleiwegمشاهده پروفایل

پژوهشگر

University of GroningenNetherlands

Peter Kleiweg is a researcher in the Computational Linguistics group within the Faculty of Arts at the University of Groningen, specializing in computational approaches to Dutch language analysis and dialectology. His primary research domains include: Computational Linguistics and Natural Language Processing Dialectology and Dialectometry Language Variation and Syntax Phonotactics and Parameter Setting Recent publications demonstrate a consistent trajectory in developing computational frameworks for linguistic research, particularly through tools like SPOD (Syntactic Profiler of Dutch) and AlpinoGraph for treebank analysis. His work bridges theoretical linguistics with practical tool development, emphasizing quantitative methods for dialect variation studies and syntactic profiling in Dutch. As an active member of Groningen's Computational Linguistics research team, Kleiweg contributes to collaborative projects advancing Dutch language processing through innovative computational methodologies and open-access tools.

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R. Haiمشاهده پروفایل

پژوهشگر

Delft University of TechnologyNetherlands

R. Hai is a researcher active in the fields of Machine Learning , Relational Databases , and Quantum Computing . Their work bridges the integration of large language models (LLMs) with database systems, focusing on optimizing query processing and data management through linear algebraic methods. Hai's research emphasizes seamless data-ML workflows and innovative applications of relational databases in emerging domains. Key Research Themes : LLM compilation to SQL, quantum circuit simulation via RDBMS, and convergence of data integration with ML. Collaborations : Active in international academic networks, with contributions to conferences like SIGMOD and IEEE journals. Scientific Awards: Veni grant AES2022 (2023) Publications demonstrate expertise in overcoming data barriers, enhancing database performance for ML tasks, and simulating quantum computations using relational database management systems.

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J.A. Pouwelseمشاهده پروفایل

استاد

Delft University of TechnologyNetherlands

J.A. Pouwelse is a Professor at the Data-Intensive Systems department within the Electrical Engineering, Mathematics and Computer Science school at Delft University of Technology . With 125 research outputs and 4 supervised works, his work focuses on Blockchain , Decentralized Systems , Federated Learning , and Peer-to-Peer Networks , particularly for Web3 applications. His recent publications analyze topics such as: Decentralized adaptive ranking Serverless federated learning Green smart contracts Search index optimization Zero-trust frameworks Notable recognition includes the LCN Best Paper Award 2021 . Research spans decentralized infrastructure design, privacy preservation, and scalable system implementation.

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