Find Academic Supervisors

Sérgio NunesView profile

Assistant Professor

• Information Retrieval
• Web Technologies
• Entity-Oriented Search
• +4 more

Sérgio Nunes is an Assistant Professor at the Faculty of Engineering (FEUP) of the University of Porto, Portugal, and a Senior Researcher at INESC TEC's Information and Computer Graphics Systems Unit. He holds a MSc (2004) and PhD (2010) in Informatics Engineering from FEUP, focusing on Information Retrieval. His research spans Information Retrieval, Web Technologies, Entity-Oriented Search, and Natural Language Processing. Key research interests include entity-oriented search models (e.g., Hypergraph-of-Entity), low-resource language datasets, narrative extraction, and misinformation detection. His work often integrates graph theory, visualization tools (e.g., MediaViz), and collaborative platforms for text analysis. Publications emphasize innovations in search algorithms, dataset construction, and ethical AI applications. Notable projects include Labadain-30k+ for Tetun language resources and Text2Story for narrative analysis in European Portuguese news.

Martin ConnorView profile

Adjunct Professor

• Health Policy Analysis
• Healthcare System Reform
• Integrated Care Delivery
• +3 more

Martin Connor is an Adjunct Affiliate at Stanford University's Center for Health Policy and Department of Health Policy. He holds a doctorate from Durham University (2001) and has extensive experience in UK healthcare systems, including roles as Director of the Trafford Integrated Care Organisation Programme and Deputy Chief Executive at Trafford PCT. His research focuses on integrated care systems, health policy reform, and biomedical data standards. Connor is currently a Harkness Fellow studying the role of integrated care in US Health Reform. His technical work centers on semantic web technologies and metadata standardization, exemplified through projects like the CEDAR Workbench which improves biomedical metadata quality. His policy expertise includes transforming healthcare delivery in Northern Ireland through wait time reforms and clinical decision-making frameworks. Notable contributions include elevating Greater Manchester Strategic Health Authority from 'special measures' to 'high performing' status. Education: PhD in Classical/Linguistic Philosophy from Durham University Key Roles: Director (Trafford Integrated Care), Policy Advisor (Northern Ireland Department of Health) Awards: Commonwealth Fund Harkness Fellowship Connor's publications emphasize FAIR data principles, ontology-driven metadata systems, and rule-based clinical trial management. His work bridges healthcare policy implementation with advanced biomedical informatics solutions.

Sandra KüblerView profile

Professor

• Machine Learning of Natural Language
• Parsing Morphologically Rich Languages
• Dependency Parsing
• +5 more

Sandra Kübler is a Professor in the Department of Linguistics at Indiana University, part of the College of Arts and Sciences. Her research focuses on computational linguistics, machine learning applications in natural language processing, and parsing of morphologically rich languages. She has led projects such as the NSF-funded SATC initiative on unsubstantiated information analysis and contributed to initiatives like the TLT workshops and SPMRL conferences. Her work spans dependency parsing, abusive language detection, and cross-lingual NLP challenges. She advises numerous PhD and Master’s students, many of whom have gone on to academic and industry roles. Her contributions include developing tools like the IUCL system for stance detection and collaborating on corpora for languages like Old Occitan and Xibe. Education details are not explicitly stated in the provided texts, but her extensive academic career and publications indicate advanced training in computational linguistics. Her research interests emphasize leveraging machine learning for linguistic analysis, particularly in under-resourced languages and social media text processing. Projects include the development of the TüBa-D/Z treebank and contributions to parser evaluation frameworks. She has organized major workshops such as the SIGMORPHON and TLT conferences, reflecting her leadership in the field. In advising, she has guided over 20 students to completion, many securing academic positions (e.g., University of British Columbia, Rose-Hulman Institute) or industry roles (e.g., JP Morgan Chase, Microsoft). Her lab activities involve collaborations with institutions like Bosch and IntraFind. Current research includes multilingual coreference resolution and fusion of hard/soft data for information reliability assessment.

Torsten KiliasView profile

Researcher

• Database Systems
• Text Mining
• In-Database Analytics
• +3 more

Torsten Kilias is a Researcher at the Beuth University of Applied Sciences Berlin and the DATEXIS team, affiliated with the Data Science +X Graduate School. He holds a degree from Ilmenau University (2012) with prior internships at IBM and TU-Berlin. His research focuses on text mining in databases, particularly in-database relation extraction (INDREX) and span data models for shared-nothing architectures. Current work involves managing knowledge graphs in relational databases under the BMWi-funded Smart Data Web project. Key projects include APPL-FM (DFG), KIP-SDM (BMBF), and contributions to interdisciplinary initiatives like AnorexiaVR (BMG) and Vessel Segmentation. His technical expertise spans entity linking with neural embeddings, distributed systems for web analytics, and database acceleration using coprocessors. Publications highlight advancements in in-database analytics, with notable work in Information Systems journal (2015) and conference contributions on marketplace architectures for text annotation services (2014).

Christian HänigView profile

Professor

• Machine Learning
• Deep Learning
• Natural Language Processing
• +7 more

Prof. Dr. Christian Hänig is a Professor at the Department of Computer Science and Languages and a Temporary Lecturer at the Department of Electrical Engineering, Mechanical Engineering and Industrial Engineering at Anhalt University of Applied Sciences. He advises the Data Science (Full-Time Program) Master of Science degree and teaches courses such as Artificial Intelligence, Data Mining, and Deep Learning. His research focuses on Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Medical Imaging, Multimodal Document Processing, and Data Science. Recent work emphasizes applications in financial domains (e.g., German financial language models and corpus development) and agricultural sector benchmarking. Earlier research includes VR education analytics, unsupervised NLP techniques, and knowledge extraction from unstructured data. Key publications (2024) include developing benchmarks for Ukrainian language models, evaluating agricultural LLMs, and creating financial domain corpora. His contributions span over 20 years, addressing challenges in domain-specific NLP, clinical text mining, and industrial quality analysis. Prof. Hänig’s academic service includes roles as a degree program advisor and committee member. Office hours are Thursdays 4:30–6:00 PM (by appointment) at the Ratke Building, Room 23-114, Köthen campus.

Julaine ClunisView profile

Assistant Professor

• Library Science
• Knowledge Organization
• Metadata
• +5 more

Julaine Clunis is an Assistant Professor in the Department of STEM Education & Professional Studies at Old Dominion University (ODU), affiliated with the Darden College of Education & Professional Studies. Her research focuses on knowledge organization systems, metadata, linked data, semantic web technologies, health informatics, and data science applications in library and information science. Clunis holds a Ph.D. in Knowledge Organization (2022), and dual M.S. degrees in Library and Information Science (2016) and Health Informatics (2016), all from Kent State University. Her work bridges library science and healthcare through projects like semantic mapping frameworks for clinical coding schemes and pandemic-era health information exchange strategies. Recent publications address legislative impacts on reproductive health informatics and automated semantic integration in healthcare data systems. Clunis has received prestigious awards including the Eugene Garfield Dissertation Fellowship (2021) and multiple IMLS grants supporting LIS education and data science initiatives. Her expertise includes developing FAIR-compliant data systems, ontology design, and collaborative educational partnerships. Clunis' research emphasizes practical applications such as preschool-library collaborations for family engagement and spatial-temporal analysis of social media sentiment. She contributes to advancing interoperability standards in both library and healthcare domains through semantic web technologies.

• Blockchain Technology
• Cryptocurrency Forensics
• Decentralized Finance (DeFi)
• +4 more

Bernhard Haslhofer is a Professor at the University of Vienna, affiliated with the Department of Information Systems within the Faculty of Computer Science and Mathematics. His research focuses on blockchain technology, cryptocurrency analytics, and digital libraries, with a particular emphasis on forensic applications of blockchain, decentralized finance (DeFi), and semantic web technologies. He co-leads the Cryptoasset Analytics Workshop (CAAW) and contributes to projects like GraphSense, a cryptoasset analytics platform. His work spans academic collaborations with institutions worldwide, including contributions to standards like ResourceSync and Open Annotation Collaboration (OAC) models. Research interests include machine learning applications in finance, decentralized governance mechanisms, and improving the interoperability of digital resources. Publications highlight trends in DeFi composability, blockchain forensics for crime mapping, and ethical considerations in AI-driven cryptocurrency analysis. He has organized major workshops at venues like The Web Conference (WWW) and Financial Cryptography (FC), fostering interdisciplinary dialogue between academia and industry. No notable scientific awards are explicitly listed in the provided text, though his extensive publication record reflects significant contributions to the field.

Dengsheng ZhangView profile

Senior Lecturer

• Artificial Intelligence
• Big Data
• Image Classification
• +5 more

Dr. Dengsheng Zhang is a Senior Lecturer at Federation University Australia (formerly Monash University) and a Guest Professor at Xi'an University of Posts & Telecommunications, China. He holds a PhD in Computing (2002) and a GCHE (2006). His expertise spans over 25 years in artificial intelligence, big data, image processing, and music classification. He has published over 100 refereed papers (10,000+ citations) and authored the award-winning book Fundamentals of Image Data Mining (Springer, 2019). His research focuses on image classification, object detection, deep learning, and feature extraction. Dr. Zhang leads the Computational Science and Mathematics Group, contributing to projects like SIRBOT (Semantic Image Retrieval) and VFR (Visiting Friends and Relatives Travel Research). He serves as an Associate Editor for World Scientific's Transactions on Signal Processing. His teaching spans calculus, web design, computer networks, and project management. He has supervised 8 completed PhD students and actively engages in grants, including two ARC Discovery projects. His lab explores innovations in image retrieval, music classification, and machine learning applications.

Irene Ruano BenitoView profile

Researcher

• Forest Management
• Ecosystem Services
• Biodiversity Conservation
• +5 more

Irene Ruano Benito is a Senior Researcher at the INSTITUTE FOR RESEARCH IN SUSTAINABLE FOREST MANAGEMENT, specializing in forest ecosystems and silvicultural strategies. She holds a Doctorate from Universidad de Valladolid (2016) with a thesis on Mediterranean pine regeneration. Her research focuses on forest management, biodiversity conservation, and climate resilience in Mediterranean ecosystems. She currently leads the Bosque Modelo Palencia project (BF154), funded by the Spanish Ministry for Ecological Transition and the European Union’s NextGenerationEU program. Her work integrates advanced methodologies like GIS technologies, artificial intelligence, and socio-semantic systems (e.g., Educawood) to address environmental challenges. Key research interests include mixed forest carbon sequestration potential, drought resilience in pine species, and biosecurity in mountain national parks. She has collaborated on projects in Spain, Vietnam, and Northern Vietnam’s Acacia plantations, emphasizing interdisciplinary approaches. Publications highlight studies on seedling density effects, stand management diagrams, and post-fire forest recovery. Her contributions span experimental design (Nelder wheel methodology), predictive modeling, and policy-informed management strategies.

Sara MigliettiView profile

Senior Lecturer

• Intellectual History
• Renaissance Studies
• Translation Studies
• +6 more

Dr Sara Miglietti is a Senior Lecturer in Cultural and Intellectual History at the Warburg Institute, part of the School of Advanced Study, University of London. She holds dual PhDs from Scuola Normale Superiore (Pisa) and the University of Warwick. Her research focuses on Renaissance and early modern Europe, with expertise in intellectual history, political thought, book history, and environmental humanities. She specializes in classical reception, climate theories, and self-translation practices in multilingual contexts. Her current Leverhulme Trust-funded project Writing Bilingually 1465–1700 explores self-translated works between Latin and vernacular languages in Italy and France. She has co-edited volumes such as Governing the Environment in the Early Modern World (2017) and Reading Publics in Renaissance Europe (2016). Her monograph The Power of Place: Climates and Characters in Early Modern Thought is under contract with Johns Hopkins University Press. Miglietti’s research integrates interdisciplinary approaches, analyzing how climate theories shaped early modern environmental ethics and political discourse. She has supervised numerous PhD students on topics ranging from climate historiography to Renaissance art and scientific instruments. Her work bridges philosophical, scientific, and literary sources, emphasizing the role of translation and multilingualism in cultural transmission. She serves on editorial boards for journals like Rinascimento and advisory panels for initiatives such as the Archaeology of Reading . Her linguistic proficiency in French, Italian, Latin, and other early modern languages supports her engagement with primary sources across Europe.

Christopher OhgeView profile

Senior Lecturer

• Digital Humanities
• Textual Scholarship
• Book History
• +5 more

Dr. Christopher Ohge is a Senior Lecturer in Digital Approaches to Literature at the Institute of English Studies (IES), University of London. He holds a PhD from Boston University and has held academic roles at institutions including the University of Maine and the University of California, Berkeley. His research focuses on the intersection of digital humanities with textual scholarship, book history, and literary studies. He serves as Associate Director of the Herman Melville Electronic Library and contributes to Melville’s Marginalia Online. Key research interests include computational methods for analyzing literary texts, digital editing, and the environmental impact of digital research. Notable projects include the digital edition of Mary Anne Rawson’s The Bow in the Cloud (funded by an NEH-Mellon Fellowship) and the AHRC-DFG-funded 'Project StoryMachine' exploring AI and spatial hypertext in folklore studies. He co-leads the Green Digital Humanities Toolkit initiative under the Digital Humanities Climate Coalition. Ohge has taught at digital humanities summer schools globally and is a core faculty member of e-Laboratories’ Fundamentals of Editing course. His publications span monographs, edited volumes, and articles in journals like Leviathan and Textual Cultures . Awards include the Boydston Essay Prize (2020) for his work on Melville’s incomplete manuscripts. Education: PhD and MA in English from Boston University. Professional roles include editorial positions at the Mark Twain Papers Project and teaching at institutions across the US and UK.

• Temporal Information Extraction
• Computational Linguistics
• Natural Language Processing (NLP)
• +3 more

Marc Verhagen is a computational linguist and programmer affiliated with Brandeis University's Computer Science Department. He holds a PhD in Computer Science (2004) and MA degrees in Computational Linguistics (University of Utrecht, 1991) and Social Geography (1985). His roles include Senior Research Scientist (2007-2008) and Postdoctoral Fellow (2004-2006). He co-founded LingoMotors Inc. (1997-2002), leading software development for natural language processing (NLP) tools. Research Focus: Temporal information extraction, TimeML standards, and computational linguistics infrastructure. Key Projects: TARSQI toolkit for temporal processing, LAPPS Grid, ISO-Space spatial annotation, and Medstract biomedical NLP. He has expertise in programming languages (Python, Perl), database systems (Oracle), and tools like Dreamweaver. His work bridges academia and industry, emphasizing NLP tool development and semantic interoperability. Beyond technical roles, he coordinated large-scale events (300–800 attendees) and served as a free-lance DJ and theater participant. Research interests span temporal semantics, event modeling, and spatial NLP, with contributions to TimeML, annotation frameworks, and semantic visualization. Over 30 publications since 1990, including his 2004 PhD thesis Times Between the Lines .

Rafael Valencia GarciaView profile

Professor

• Computer Science
• Knowledge Management
• Natural Language Processing
• +2 more

Rafael Valencia Garcia is Full Professor in the Department of Computer Science and Systems Engineering at Universidad de Murcia's Faculty of Informatics. His research develops modeling, processing and knowledge management technologies through semantic approaches. He leads the Tecnomod research group focusing on knowledge extraction and semantic technologies. His 2005 PhD thesis 'Un entorno para la extracción incremental de conocimiento desde texto en lenguaje natural' pioneered incremental knowledge extraction methods under Dr. Jesualdo Tomás Fernández Breis and Dr. Rodrigo Martínez Béjar's supervision. His recent publications demonstrate strong focus on NLP applications for social good: Advanced hate speech detection using multi-task learning Multimodal emotion recognition in Spanish Few-shot learning strategies for low-resource scenarios AI moderation systems for inclusive communication The research consistently integrates transformer architectures with linguistic features across diverse tasks including author profiling, persuasion detection, and emotion analysis. He regularly contributes to SemEval and IberLEF evaluation campaigns, developing state-of-the-art systems for detecting harmful content and analyzing emotional patterns in digital communication.

• Semantic Web Services
• B2B Integration
• Workflow Management
• +3 more

Christoph Bussler is a prominent researcher with extensive contributions to Semantic Web Services B2B Integration Cloud Computing Workflow Management Enterprise Application Integration His work focuses on semantic technologies, data engineering, and optimization frameworks. Recent publications analyze Cloud storage tier optimization Graph-based cost modeling Taxonomy for cloud storage costs Serverless-container hybrid systems SQL for NoSQL databases These studies emphasize scalable solutions and semantic interoperability. He has collaborated with experts like Dumitru Roman, Radu Prodan, and Dieter Fensel on projects involving Triple Space Computing WSMX Architecture Peer-to-Peer Service Discovery Rule-Based Classification

Sai Kumar DwivediView profile

Researcher

• Computer Vision
• Human Pose Estimation
• 3D Human Pose and Shape Estimation
• +3 more

Sai Kumar Dwivedi is a PhD candidate and Doctoral Researcher at the Max Planck Institute for Intelligent Systems (MPI-IS) in Tübingen, Germany, working under the supervision of Dr. Michael Black and Dr. Dimitrios Tzionas in the Perceiving Systems department. He closely collaborates with Dr. Cordelia Schmid and has established himself as a leading researcher in computer vision, with multiple first-author publications in top-tier conferences. His educational journey includes: PhD at International Max Planck Research School for Intelligent Systems (2021-Present) Master's and Bachelor's in Computer Science and Engineering from National Institute of Technology, Rourkela (2011-2016) Dwivedi's research focuses on human perception in in-the-wild scenarios and human-object interactions. His work bridges 2D image understanding and 3D scene reconstruction, with particular emphasis on estimating human pose and shape from monocular images. He has pioneered approaches that leverage foundational models to address challenges in human-object contact estimation, creating methods that significantly advance the state-of-the-art in 3D human-object interaction understanding. His publication trajectory shows a clear evolution from basic human pose estimation to sophisticated reasoning about human-object interactions using vision-language models. Recent work demonstrates how large foundational models can be adapted to understand and reconstruct 3D interactions from single RGB images, with applications spanning autonomous vehicles, robotics, and augmented reality systems. Notable scientific achievements include: Outstanding Reviewers Award for CVPR 2025 InteractVLM winning the Human Contact Challenge at CVPR 2025 Outstanding Reviewers Award for ECCV 2024 IMPRS-IS Scholar (2022) RA Fellowship (2021) While not currently supervising PhD students, Dwivedi has mentored junior researchers through his work at MPI-IS and previously at Mercedes-Benz where his research was deployed in production vehicles (EQS 2021 and S-Class 2021). His research has been supported by the International Max Planck Research School for Intelligent Systems and the Max Planck ETH Center for Learning Systems. As a key contributor to the Perceiving Systems department, Dwivedi's work on human-object interaction has practical applications in automotive safety systems, demonstrating the real-world impact of his research. His GitHub repository for InteractVLM has garnered significant attention with 111 stars, reflecting the community's interest in his innovative approaches to 3D interaction reasoning.