Nitin Gupta is a researcher with affiliations spanning institutions like Google, Cornell University, and Carnegie Mellon University. His work bridges theoretical and applied computer science, focusing on database systems, data-driven applications, and knowledge graphs. Research interests include: Structured data on the web and semantic publishing Scalability in virtual environments and declarative programming Integration of large language models (LLMs) into scholarly workflows FAIR data principles and research data management Recent publications explore hybrid question answering datasets, LLM applications for literature reviews, and knowledge graph construction for software engineering. His contributions emphasize machine-actionable metadata, open science, and enhancing reproducibility through standardized research artifacts. Collaborations span institutions and disciplines, with coauthorships on topics like: Game development and data coordination Non-invasive brain stimulation analysis Neuro-symbolic approaches for digital libraries Ontology matching and FAIR digital objects
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.
Jason R. Falvey, DPT, PhD is an Associate Professor in the Department of Physical Therapy and Rehabilitation Science at the University of Maryland School of Medicine, with a secondary appointment in Epidemiology & Public Health. He serves as Director of the Center for Disability Justice and leads the ENhancing Rehabilitation to Improve Community Health (ENRICH) lab. Dr. Falvey is a board-certified geriatric physical therapist and clinician-scientist dedicated to improving aging in place for older adults living with disability. Dr. Falvey's research interests focus on rehabilitation epidemiology, rehabilitation health services research, home health care, disability, and health disparities among older adults. His work employs quantitative epidemiological and health services research methods, qualitative approaches, and community-participatory research to address critical issues in community mobility and rehabilitation access. His research particularly examines how neighborhood socioeconomic disadvantage affects recovery trajectories for older adults after hospitalization or injury. His recent publications reveal a strong emphasis on understanding how social determinants of health—particularly neighborhood deprivation—affect recovery outcomes after traumatic injuries like hip fractures and traumatic brain injuries among older adults. His work frequently analyzes Medicare claims data to identify disparities in rehabilitation access and outcomes, with special attention to populations with Alzheimer's disease and related dementias. 2019 Dorothy Brigs Memorial Scientific Inquiry Award, American Physical Therapy Association 2020 Rose Excellence in Research Award, Academy of Orthopedic Physical Therapy 2020 President's Award, American Physical Therapy Association Home Health Section 2022 New Investigator Award, Health and Aging Foundation/American Geriatrics Society 2022 Jack Walker Award, American Physical Therapy Association 2022 Stephen M. Levine Award, American Physical Therapy Association Maryland Chapter 2024 Eugene Michaels New Investigator Award, American Physical Therapy Association 2024 Irion Award for Best Publication in Journal of Acute Care Physical Therapy Dr. Falvey has secured significant grant funding including a $1.1 million Paul B. Beeson Emerging Leaders in Aging Career Development Award (K76) from the National Institute on Aging and serves as co-PI on a 5-year R01 grant with Dr. Jasmine Travers (NYU) examining neighborhood socioeconomic disadvantage and nursing home staffing. He actively mentors students through the Epidemiology of Aging T32 program and co-directs the Baltimore Hip Studies Program, a research collaboration focused on fall-related injury epidemiology and recovery for older adults. As Director of the Center for Disability Justice and leader of the ENRICH lab, Dr. Falvey works at the intersection of disability studies, rehabilitation science, and social justice. His team develops and tests interventions aimed at reducing participation and mobility inequities among older adults, particularly those living in disadvantaged neighborhoods. His approach emphasizes authentic community engagement and partnership with municipal stakeholders to create sustainable solutions for improving aging in place.
David Gomez is an Assistant Professor at the School of Medicine, University College Dublin, and a group leader at Systems Biology Ireland. His research integrates experimental proteomics, computational modeling, and systems biology to study signal transduction in cancer, with a focus on the Hippo pathway and its interactions with oncogenic networks like RAS/RAF and AKT. Prof Cert in University Teaching & Learning, UCD His recent work explores mitochondrial dysfunction in Barrett's oesophagus progression, ALS-related proteomic changes, and kinase-independent mechanisms in drug resistance. He employs multidisciplinary approaches spanning mass spectrometry, mathematical models, and cross-species validation. Key article trends include proteomic profiling of disease models (cancer, neurodegeneration), extracellular vesicle dynamics, and systems-level analysis of signaling crosstalk. His studies frequently involve pathway reconstruction and identification of therapeutic vulnerabilities. Gomez coordinates modules like Cell-Cell Signalling and Molecules in Medicine , and has served as a peer reviewer for journals including Nature Communications and Cancer Research . He leads a research team at Systems Biology Ireland and has secured grants such as the UCD Equip Scheme.
Pablo Ruiz Fabo is a Senior Lecturer at the Department of Language Technologies and Digital Humanities of the University of Strasbourg since 2018. He is currently developing a research project at CiTIUS, funded by a prestigious Marie Skłodowska-Curie Postdoctoral Fellowship. His academic journey began with a PhD in Language Sciences at Paris Sciences et Lettres University (PSL) in 2017, where he focused on Natural Language Processing applications to Digital Humanities use cases. Dr. Ruiz Fabo's primary research interests include Natural Language Processing, Digital Humanities, Computational Literary Studies, and language technologies with specific applications to poetry and theater analysis. His work centers on developing NLP applications for literary analysis, automation of digital corpus development, and promoting digital visibility for less commonly studied literary traditions. He has made significant contributions to the computational analysis of Spanish and Galician literature through corpus development and linguistic annotation. His publication record shows a clear trajectory of increasingly sophisticated computational approaches to literary analysis, moving from foundational NLP applications to complex diachronic corpus studies and specialized analysis of poetic devices. Recent work demonstrates expertise in transfer learning, emotion analysis in historical corpora, and specialized theater text processing. His research bridges computational methods with humanities scholarship, creating valuable resources for both communities. Marie Skłodowska-Curie Postdoctoral Fellowship Dr. Ruiz Fabo has led several significant research projects including the MeThAL project (creating the first large public electronic corpus for theater in Alsatian), the Thealtres project (comparing social variables of 19th century theater characters), and the COMPEL project (computational analysis of literature in Galician). His work focuses on developing resources that increase digital visibility for less commonly studied literary traditions, adding diversity to Computational Literary Studies. He is also the creator of the Diachronic Spanish Sonnet Corpus (DISCO), a major resource for researchers in Spanish poetry. His laboratory work centers around the development of digital resources and computational tools for literary analysis, with particular emphasis on theater and poetry corpora. The DISCO project represents one of his most significant contributions to the field, providing a richly annotated corpus of Spanish sonnets spanning five centuries with specialized linguistic and literary annotations.
Pascal Gaillard is an Associate Professor at the University of Toulouse - Jean Jaurès, where he conducts research at the CLLE Lab (Cognition, Languages, Language, Ergonomics, UMR5263) in the "Language and Cognitive Processes" Team, while teaching in the Music Department at the National Higher Institute for Teaching and Education in Toulouse - Midi-Pyrénées (INSPE). His academic career spans over two decades, beginning as an Assistant Professor in Musicology at Université de Toulouse - Le Mirail from 1998 to 2000, before becoming an Associate Professor at the University of Toulouse since 2002. His educational background includes: PhD in Musicology and Auditory Perception (1996-2000) from Université de Toulouse - Le Mirail / Université de Paris - Jussieu Master (DEA) in Musicology - Ethnomusicology (1993-1994) from Université de Toulouse - Le Mirail Maîtrise in Musicology - Ethnomusicology (1989-1990) from Université de Toulouse - Le Mirail Licence in Musicology (1985-1989) from Université de Toulouse - Le Mirail Dr. Gaillard's research focuses on auditory perception and cognitive processes, particularly the categorization of sounds. His work spans multiple domains including musical timbre perception, speech perception in individuals with age-related hearing loss, environmental sound recognition, and auditory processing in deaf individuals with cochlear implants. He has pioneered studies on how humans organize their sound world through categorization, drawing on prototypical categorization theory developed by Rosch (1976). A key insight from his research is that auditory categorization is dynamic rather than fixed, varying according to listener needs, tasks, and action goals. His recent publications demonstrate a strong interdisciplinary approach, bridging music cognition, clinical audiology, and cognitive neuroscience. There's a clear trend toward applied research with clinical implications, particularly for deaf children with cochlear implants, as evidenced by multiple studies on humanoid robots for speech-language training. His work also shows increasing integration of computational approaches, including transfer learning for music preference prediction and ontology-based data management. Dr. Gaillard has secured numerous research grants from prestigious funding bodies including the French National Research Agency (ANR), Occitanie Regional Council, and ANSES. Current projects include "The hospital and its 'Beeps': evaluation of the hearing health of caregivers" (2025-2028), "SILENCE - Comparative acoustics: earth, planets and extreme environments" (2024-2026), and "Rehabilitation of age-related hearing loss: evolution of cognitive load in a 3D virtual environment - AgeHear" (2020-2024). He directs the "Cognition, Behavior and Use" facilities (CCU) which include specialized auditory booths for research. Since 2003, he has developed TCL-LabX, experimental software for conducting categorization studies. His research collaborations span international boundaries, working with labs in France, Canada, and the Netherlands, as well as industry partners in aeronautics and healthcare sectors.
Manuel Quesada Martinez is a researcher at the University of Murcia, affiliated with the Tecnomod research group focused on Modeling, Processing, and Knowledge Management Technologies. He earned his PhD in 2015 with a dissertation titled "Methodology for the enrichment of biomedical knowledge resources" under the supervision of Dr. Robert David Stevens and Dr. Jesualdo Tomás Fernández Breis. University: University of Murcia Research Group: Tecnomod Education: PhD in Biomedical Informatics (2015) Email: manuel.quesada@um.es His research interests center on biomedical knowledge resource enhancement, leveraging semantic web technologies and data modeling frameworks. While specific publications and awards are not detailed in the provided text, his work aligns with interdisciplinary approaches in healthcare data integration and knowledge management systems.
Nicolas HIOT is a Post-doctoral fellow at the University of Orleans affiliated with the LIFO laboratory (Laboratoire d'Informatique Fondamentale d'Orléans) and the Pamda project. His research bridges database systems, natural language processing, and medical informatics with a focus on text-to-database integration and consistency maintenance. His research interests center on: Database Systems for medical applications with emphasis on consistency and evolution Natural Language Processing for clinical text analysis and relation extraction Knowledge Graph construction from unstructured textual data Medical Informatics applications for healthcare data management Analysis of his 15 most recent publications (2020-2024) reveals a cohesive research trajectory at the intersection of databases and NLP. Key thematic clusters include automated medical database construction from clinical texts, consistency management in evolving RDF/property graph systems, and clinical entity/relation extraction for knowledge graphs. His work consistently addresses real-world challenges in healthcare data integration through tools like DataFix and ArchiTXT, demonstrating strong translational potential. Nicolas HIOT actively contributes to the LIFO research laboratory at the University of Orleans, collaborating extensively with Jacques CHABIN, Mirian HALFELD-FERRARI, and Dominique LAURENT. His technical output includes multiple software systems for database evolution management and clinical text processing, reflecting both theoretical contributions and practical implementations in semantic data management.
Chris Cummins is Professor of Experimental Pragmatics in the Department of Linguistics and English Language at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences (PPLS). His academic career spans multiple institutions with significant contributions to experimental semantics and pragmatics research. His research interests focus on experimental semantics and pragmatics , particularly how speakers choose to use specific linguistic forms to communicate about quantity, and how hearers interpret these forms to make decisions in high-stakes contexts such as financial and medical interactions. He investigates how listeners infer additional features of situations, including speaker knowledge states and potential argumentative agendas, from linguistic utterances, and how this information influences decision-making processes. His work also explores speech act recognition and the production/comprehension of non-asserted content. Analysis of his recent publications reveals a strong trend toward interdisciplinary research combining linguistic theory with practical applications in medical communication, particularly in emergency contexts like cardiac arrest resuscitation. His work increasingly examines how numerical expressions function argumentatively in social media and medical contexts, with growing attention to cross-linguistic and developmental perspectives on pragmatic reasoning. Professor Cummins has collaborated extensively with researchers including Gareth Clegg, Hannah Rohde, Holly Branigan, and Ernisa Marzuki on medical communication projects, and with Michael Franke, Alex Lorson, and others on experimental pragmatics research. He has received support for his work through research studentships and collaborative projects. Beyond his formal academic role, Cummins actively engages with the public through the Cabaret of Dangerous Ideas at the Edinburgh Fringe (discussing topics like misleading language and slurs in 2023-2024) and Bright Club Edinburgh. He previously co-presented the New Books in Language podcast series as part of the New Books Network.
Dr. Ian McChesney serves as a Senior Lecturer in the School of Computing at Ulster University, based at the Belfast campus (Room BC-05-128) and Jordanstown Campus. His research spans Human Activity Recognition, Process Mining, and Transfer Learning with significant contributions to Autonomic Computing and Open Data initiatives. Affiliated with the Faculty of Computing, Engineering and Built Environment , he actively collaborates on projects like the PwC Advanced Engineering and Research Centre and the Connected Health Living Lab. His research interests focus on Human Activity Recognition (91% fingerprint match), Process Mining (57%), and Transfer Learning (45%), with applications in smart homes, business processes, and healthcare. Key methodologies include semi-Markov models for IoT device management, synthetic data generation for autonomic systems, and semantic enrichment of HAR datasets. His recent work shows increasing emphasis on educational frameworks for competency-based computing education in the UK. Among his 49 research outputs and 3 datasets, notable contributions include the InSync dataset and research on dyslexia in programming. He received the Best Paper Award ICAS 2025 for work on synthetic data generation. His projects include the TRAXX Fusion consultancy (2014-2016) and current involvement in the PwC Advanced Engineering Centre (2021-2026). Supervision: Mentored 4 students through supervised research work Grants: Contributed to KTP Programme with MJM Marine Limited (2022-2025) and Connected Health Living Lab (2018) His work supports UN Sustainable Development Goals through applications in healthcare optimization, educational innovation, and industrial process improvement. Current projects focus on few-shot learning, large language models, and human activity recognition in connected health environments.
Hartwig Frimmel is a Professor and Chair of Geodynamics and Geomaterials Research at the Institute of Geography and Geology, University of Würzburg. With an extensive academic career spanning over three decades, he has held positions at the University of Cape Town and the University of Vienna before his current appointment since 2007. His research focuses on economic geology, mineral resources, and Precambrian geology, with particular emphasis on gold deposit genesis and geodynamic processes. PhD in Geology and Petrology, University of Vienna (1987) Professor Frimmel's research interests span multiple domains of economic and Precambrian geology. His work on the genesis of the Witwatersrand gold deposits has significantly contributed to the ongoing debate about one of the most economically significant gold districts in history. He has developed a modified paleoplacer model that explains the available data on these deposits. His research extends to sediment-hosted base metal deposits, geodynamic evolution of southwestern Gondwana, Precambrian palaeoclimate reconstruction, and high-grade metamorphic terranes in Antarctica. His recent work increasingly incorporates machine learning techniques for mineral exploration and resource evaluation. An analysis of Professor Frimmel's recent publications reveals a strong focus on gold deposit genesis across different geological settings and time periods, with particular attention to the Witwatersrand Basin in South Africa. His work combines traditional geological methods with advanced geochemical and isotopic techniques, including detailed studies of fluid inclusions, trace element analysis, and zircon geochronology. There's also a growing trend toward integrating machine learning algorithms with traditional geological methods for resource estimation and exploration targeting. Member of the Academy of Geosciences and Geotechnologies, Germany Founding member of the Bavarian Georesources Centre (BGC) President of the Society for Geology Applied to Mineral Deposits (SGA) 2006-2007 Voting member of the Cryogenian subcommission of the international Commission on Stratigraphy (ICS) Goodwill ambassador of the Geological Society of Africa (GSAf) 2011-2017 Professor Frimmel has served in numerous advisory capacities, including as Advisor to the European Commission's European Innovation Partnership on Raw Materials (2013-2017) and as Dean for student affairs at the University of Würzburg (2013-2016). His research has been supported through various international collaborations and projects, including participation in the South African National Antarctic Programme and the DFG-supported priority programme on Antarctic research. He has coordinated international field workshops and short courses, demonstrating his commitment to advancing geological knowledge globally. As Chair of Geodynamics and Geomaterials Research, Professor Frimmel leads a research group focused on understanding the formation and evolution of mineral deposits within their broader geodynamic context. His team has conducted field studies across multiple continents, including Africa, Antarctica, South America, and Asia, contributing to our understanding of global geologic processes and resource distribution.
Giorgos Stamou is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), and a Visiting Professor at the MIT Sloan School of Management and MIT Open Learning. He directs the Artificial Intelligence and Machine Learning Systems Laboratory (AILS Lab) and has been a senior researcher at the Institute of Communications and Computer Systems (2000-2008) and an academic visitor at Oxford University (2011-2012). His research spans Deep Learning , Explainable AI , and Knowledge Representation , with a focus on Large Language Models and Multimodal Learning . He has coordinated over 60 funded projects and published 150+ papers. Recent work highlights trends in LLM Evaluation , Gender Bias Mitigation , and Multimodal Music Analysis , reflecting his interdisciplinary approach to AI challenges. Stamou has served on steering committees for W3C working groups (Rule Interchange Format, Web Ontology Language) and contributed to cultural heritage metadata enrichment through the CrowdHeritage projects. He founded NTUA's MSc program in Data Science and Machine Learning (2018-2022) and has organized conference tracks on riddle-solving frameworks and hallucination detection.
Adam VanSertima serves as an Adjunct Professor in the Core Division's General Education department at Champlain College, where he has been teaching courses on Canadian, Quebec, and Montreal culture for 11 years through Champlain Abroad. Born in the UK, he has spent much of his life in the Montreal area, bringing both personal experience and academic expertise to his students. His academic background combines Art History and Philosophy with professional experience in film and video production, creating a unique interdisciplinary perspective. His research interests span Culture Studies, Film Studies, Montreal history and culture, Phenomenology, and the philosophy of craft. VanSertima's scholarly work reveals a distinctive approach that connects philosophical concepts with everyday material practices. His publications explore the intersections between phenomenology, cultural studies, and embodied experience, often using creative analogies drawn from baking, carpentry, and writing implements to illuminate complex philosophical concepts. Francine Page Award (2022) While specific details about his advising and grant activities aren't provided in the available information, his blog content suggests a strong commitment to exploring the philosophical dimensions of everyday practices and material culture. His work demonstrates how philosophical inquiry can emerge from and inform practical engagement with the world, bridging theoretical concepts with lived experience in ways that likely enrich his teaching approach.
Prof. Dr. Kurt Stockinger is a Professor of Computer Science at ZHAW School of Engineering and holds a doctorate at the University of Zurich . He serves as Head of the MAS Data Science program and co-leads the ZHAW Datalab . His research focuses on Intelligent Information Systems , bridging information systems, natural language processing, and machine learning. Affiliated with the University of Zurich, he contributes to Quantum Machine Learning and Open Data Exploration initiatives. Stockinger's educational background includes a PhD in Computer Science (University of Vienna & CERN), a Master in Business Informatics (University of Vienna), and a CAS in Didactics & Methodology (ZHAW). He has taught courses in Quantum Computing , Big Data for Natural Sciences , and Data Science programs at ZHAW and University of Zurich. His research spans Data Science , Big Data , Natural Language Query Processing , Knowledge Graphs , and Quantum Machine Learning . Recent publications focus on quantum autoencoders , hybrid quantum neural networks , and prompt engineering for knowledge graph question answering. He has developed frameworks like ScienceBenchmark for real-world NL-to-SQL evaluation and NQuest for natural language query exploration. Scientific awards include the Best Paper Award at 7th Swiss Conference on Data Science (2020) He leads major projects such as DataGEMS (Data Discovery Platform, Horizon Europe) Digital Health Zurich (Clinical Innovation Lab) INODE4StatBot.swiss (NL-to-SQL Translation) GraphQueryML (Graph Database Optimization) ScienceBenchmark (NL-to-SQL Evaluation) Stockinger's work intersects with computer vision , biomedical data , and industrial applications , demonstrated through collaborations with institutions like Lawrence Berkeley National Laboratory, CERN, and University of Washington. He has contributed to establishing QuantumBasel and ZHAW Datalab as research hubs.
Prof. Dr. Andreas Harth holds the Chair of Business Information Systems, especially Technical Information Systems, at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where he has been a faculty member since 2018. He also serves as a department head at the Fraunhofer IIS-SCS in Nuremberg. His academic work spans both theoretical research and practical applications in decentralized information systems, with strong connections to industry through numerous collaborative projects. Harth completed an apprenticeship as a banker before studying computer science. He earned his doctorate from the Digital Enterprise Research Institute at the National University of Ireland, Galway, and completed his habilitation at the Karlsruhe Institute of Technology. His academic journey included teaching and research stays at the universities of Heidelberg, Innsbruck, Stanford, and Southern California, providing him with a global perspective on information systems research. His research focuses on developing methods and technologies for decentralized information systems found in the World Wide Web and blockchain environments, with applications in companies. He investigates data integration using Semantic Web and Linked Data technologies, process modeling languages, and their applications in the Internet of Things, Web of Things, and Industry 4.0 contexts. His work bridges theoretical computer science with practical business applications, particularly in data sovereignty and decentralized architectures. Analysis of his recent publications reveals a strong trend toward Solid protocol applications, knowledge graph technologies, and the integration of large language models with semantic web technologies. His research increasingly focuses on practical implementations in enterprise settings, healthcare data management, and manufacturing systems, demonstrating the real-world applicability of his theoretical work. As a member of FAU's research focus on Digitalization and Innovation, Harth collaborates with strategic partners including the Fraunhofer Institute for Information Systems (IIS) and major German industrial companies. His work contributes significantly to FAU's position as one of Germany's most research-intensive universities, particularly in the fields of business informatics and decentralized systems.
