Find Academic Supervisors

Oscar CorchoView profile

Professor

• Semantic Web
• Linked Data
• Ontological Engineering
• +3 more

Oscar Corcho is a Full Professor at Universidad Politécnica de Madrid (UPM) and co-leads the Ontology Engineering Group (OEG). He holds a BSc, MSc, and PhD in Computer Science from UPM. His research focuses on Semantic Web technologies, Linked Data, and Ontological Engineering, with applied work in e-Science and Open Science. He has coordinated major EU projects like STARS4ALL, MobileAge, and CLARITY, and led national initiatives such as Ciudad2020 and myBigData. Corcho’s academic background includes over 100 publications, including the textbook Ontological Engineering , and an h-index of 40+. He has supervised 16 PhD theses and serves on editorial boards of journals like Semantic Web and Journal of Web Semantics . His awards include the 2016 Juan López de Peñalver Award and the Semantic Web Challenge 2015. Research leadership roles include co-directing OEG and coordinating Marie Curie actions (SemData, KOPAR). His projects span innovation in public transport (TransformingTransport), elderly digital inclusion (MobileAge), and open government data (LocaliData). He actively promotes citizen science through projects like STARS4ALL to combat light pollution. Education: BSc in Computer Science (UPM, 2000) MSc in Software Engineering (UPM, 2001) PhD in Computer Science and AI (UPM, 2004) Awards: Highlighted awards including Royal Academy of Engineering recognition and EU innovation prizes Labs/Teams: Ontology Engineering Group (OEG), STARS4ALL consortium, SlideWiki collaborative learning platform

• Semantic Web
• Open Data
• Knowledge Graph
• +8 more

Joonas Kesäniemi is a Researcher at the School of Science , Aalto University , where he focuses on Semantic Web technologies and Linked Open Data . He holds a Master's degree in Engineering and Technology from the University of Jyväskylä (2020) and is currently pursuing a doctoral degree. Research Interests : Kesäniemi’s work bridges Knowledge Graphs , Cultural Heritage , and Political Data Modeling . His research applies Semantic Web standards like CIDOC CRM to domains such as European biographical data and Finnish legislative systems . Scientific Contributions : He has published in conferences like ADBIS 2022 and workshops at DHN 2022, with a focus on data modeling, open access, and interdisciplinary applications of Wikibase and Parliamentary Sampo tools. Projects : Active in EU-funded InTaVia (2020–2023) and national initiatives like SuALT (2017–2021), his collaborations span institutions in Finland and Europe, particularly with teams at Aalto University and the Parlamenttisampo project.

• Digital Humanities
• Linked Data Publishing
• Ontology Services
• +7 more

Jouni Tuominen is a University Researcher at the University of Helsinki, affiliated with the Helsinki Institute for Social Sciences and Humanities (HSSH), and a visiting researcher at Aalto University's Department of Computer Science. He holds a D.Sc. (Tech.) from Aalto University (2017), where his dissertation focused on ontology services for knowledge organization systems. His roles include collaboration with the Helsinki Centre for Digital Humanities (HELDIG) and the Semantic Computing Research Group (SeCo). Education: D.Sc. (Tech.) in Computer Science, Aalto University, 2017 (Dissertation: "Ontology Services for Knowledge Organization Systems") Research Interests: Jouni specializes in ontology repositories, linked data publishing tools (e.g., ONKI and LDF.fi ), semantic modeling of legacy datasets, and computational methods for digital humanities. His work emphasizes interdisciplinary projects such as WarSampo , LawSampo , and Mapping Manuscript Migrations , aiming to integrate fragmented data into unified semantic infrastructures. He collaborates with institutions to digitize and publish cultural heritage, legal, and archaeological data for public and academic use. Articles Trends: His recent publications (2023–2025) focus on semantic portals for historical and parliamentary data, ontology-driven harmonization of heterogeneous datasets, and methodologies for enhancing Linked Open Data quality and trust. Key themes include event-based modeling for war history, epistolary networks, and cross-cultural data aggregation. Scientific Awards: While Jouni has received multiple national and international honors, specific award names are not detailed in the provided text. Advising and Grants: He leads or contributes to large-scale projects like FIN-CLARIAH, ECHOES, and ARCH-ON, funded by national and international grants. His work involves open science initiatives, such as creating the ParliamentSampo data service and co-developing the SuALT citizen science platform for archaeological data. Projects emphasize collaboration with libraries, museums, and archives to advance digital humanities infrastructure. Labs and Teams: Jouni is affiliated with the Helsinki Institute for Social Sciences and Humanities (HSSH) and the Helsinki Centre for Digital Humanities (HELDIG). He collaborates internationally through initiatives like the Mapping Manuscript Migrations project and the COST Action network for Web-centred linguistic data science. Key tools developed include FindSampo (archaeological finds), BiographySampo (biographical data), and LawSampo (legal data).

• Dataset Retrieval
• Linked Data
• Decentralised Technologies
• +4 more

Dr. Luis-Daniel Ibáñez is a Lecturer in Computer Science at the University of Southampton, where he leads research in dataset retrieval, linked data, and decentralized technologies. He is affiliated with the Web and Internet Science team and the Centre for Machine Intelligence. Prior to his academic role, he worked as a Research Fellow (2015–2020) and holds a PhD from the University of Nantes, France, focusing on distributed data management. His teaching includes courses on Data Science, Data Visualization, and Data Analysis. Education: PhD in Computer Science, University of Nantes, France (Distributed Data Management Team) Computer Engineering Diploma, Universidad Simón Bolívar, Venezuela Research Interests: Focuses on scalable data systems, including decentralized knowledge graphs, data marketplaces, and provenance management. His work integrates AI techniques like LLMs for automated provenance inference and explores privacy-preserving mechanisms in data sharing. Current projects include UPCAST (Universal Platform Components for Safe Data Exchange). Advising & Grants: Supervises 5 PhD students and contributes to projects funded by research councils. His team collaborates on modular data marketplace architectures and game-theoretic approaches to data monetization. Labs/Teams: Active in the Web and Internet Science group and the Centre for Machine Intelligence at the University of Southampton.

• Pathology Informatics
• Clinical Systems Engineering
• Artificial Intelligence in Diagnostics
• +4 more

Peter Gershkovich is an Associate Professor of Pathology and Director of the Section of Pathology Informatics and Cancer Data Science at Yale School of Medicine. His roles include leading software development to integrate clinical technologies and improve patient care through systems engineering. He holds an MD from Altai State Medical University (1987) and an MHA from Suffolk University (1996). His research focuses on clinical informatics, AI in diagnostics, genomic data analysis, and precision medicine platforms. Notable projects include the TQuest web platform linking tumor genetics to therapies, systems for Lynch syndrome diagnosis, and AI-driven prostate cancer detection validation. During the pandemic, his team rapidly deployed SARS-CoV-2 testing software. Recent work explores organizational readiness for AI in pathology (2023), senescent cell mapping (SenNet Consortium, 2022), and systems engineering for clinical workflows. His software solutions emphasize pragmatic, impactful integration into daily clinical operations. No scientific awards are explicitly listed in the provided materials. His academic contributions include over 15 peer-reviewed publications since 2001, with a focus on pathology informatics, laboratory systems, and oncology diagnostics.

Andrea Berez-KroekerView profile

Professor

• Documentary Linguistics
• Endangered Language Preservation
• Language Technology
• +4 more

Andrea Berez-Kroeker is a Professor in the Department of Linguistics at the University of Hawaiʻi at Mānoa, specializing in documentary linguistics with a focus on endangered language preservation, language technology, and reproducible research practices. She holds a PhD from the University of California, Santa Barbara. Her work bridges linguistics, archiving, and community activism, emphasizing sustainable data practices and technological infrastructure for endangered languages. Research Interests: Her research examines discourse-functional frameworks in language description, integrating field-collected data and archived materials. She advocates for reproducible research methodologies in linguistics and leads initiatives such as the Kaipuleohana Digital Language Archive. Her projects in Alaska and Hawaiʻi prioritize community-driven language preservation and education. Labs/Teams: Director of the Kaipuleohana University of Hawaiʻi Digital Language Archive, collaborating on projects like C’ek’aedi Hwnax, an Ahtna digital archive. She also participates in international conferences and workshops on language documentation and conservation. Advising & Grants: Advises graduate students in documentary linguistics and related fields. Her work includes grants focused on digital archiving, data citation standards, and curriculum development for reproducible research practices in linguistics.

Haipeng CaiView profile

Associate Professor

• Software Security
• Software Engineering
• Program Analysis
• +4 more

Haipeng Cai is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. Previously, he served as an Assistant Professor (2016–2022) and tenured Associate Professor (2022–2024) at Washington State University. His research focuses on software engineering and security, particularly program analysis, machine learning for security applications, and multilingual software systems. He holds a PhD in Computer Science and Engineering from the University of Notre Dame (2015). Education: PhD in Computer Science & Engineering (University of Notre Dame, 2015). Research interests include: Software security and reliability of distributed systems Machine learning-driven vulnerability detection and patching Analysis of multilingual software and cross-language bugs Tools like VGX (vulnerability data generation), PyRTFuzz (Python runtime fuzzing), and PolyFuzz (multi-language system fuzzing) Notable awards include the 2025 TOSEM Outstanding Paper Award for malware detection sustainability, multiple Distinguished Reviewer Awards, and the 2022 Junior Faculty Research Award. His work has led to over 50 publications, with a focus on practical security solutions. Advising: Mentor to students like Wen (PhD 2024, now at Utah State), Xiaoqin (first PhD graduate from his lab), and current advisees Haoran, Jiawei, and Yu. Projects include grants from NSF, ONR, and the Open Technology Fund. Key contributions include tools like VulGen (vulnerability dataset generation) and FlowDist (distributed system analysis), and labs focused on AI-driven security and multilingual software engineering.

• Responsible AI
• Software Engineering
• Machine Learning
• +3 more

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.

• Programming Language Theory
• Functional Programming
• Logic Programming
• +3 more

Tom Schrijvers is a Professor at the Department of Computer Science, Faculty of Engineering Science, KU Leuven. His research focuses on programming language theory, functional programming, logic programming, and computational effects. Advancing multi-stage programming with computational effects (2024–2028) Generating Educational Feedback with Program Analysis (2024–2028) Programino: An Educational Programming Platform (2023–2027) eTeacher: Interactive web-based programming education platform (2023–2025) AmPERSand: Programming Education Runtime System (2023–2026) His recent publications emphasize bidirectional transformations, effect handlers, and programming education tools. He collaborates extensively with British institutions like Imperial College London and works on the book Language Engineering in Haskell with Dr. Nicolas Wu.

Diana BannisterView profile

Researcher

• Effective use of Learning Technologies
• School Development and School Improvement
• Innovation and Creativity in the Curriculum
• +7 more

Diana Bannister MBE (PFHEA) is the Director of the Institute of Education and Associate Dean at the University of Wolverhampton , Faculty of Education, Health & Wellbeing. Since 2001, she has led research and development in learning technologies, school improvement, and future educational scenarios. Principal Fellow of the Higher Education Academy (PFHEA) Expert in 1:1 learning, interactive technologies, and educational change Collaborates with Ministries of Education, commercial providers, and international agencies Education: Postgraduate Certificate in Higher Education Leadership and Management (2018) MA in Education Management and Leadership (2005) B.Ed. (Honours) (1996) Research Interests: Specializes in the effective use of learning technologies , school development , mobile learning , and innovative learning spaces . Her work bridges technology integration with pedagogical improvement across global contexts. Scientific Awards: Member of the Order of the British Empire (MBE) for Services to Education (2000) Lloyds TSB Teaching Award for Creative ICT use in Primary Education (1999) Project Leadership: Directed major international projects including Living Schools Lab (2013–present) and Creative Classrooms Lab (2012–2014), observing practices in over 30 countries. Currently supports Digital Campus Transformation as a member of the Digital Academic Reference Group.

• Knowledge Representation
• Mathematical Knowledge Management
• Natural Language Processing
• +5 more

Prof. Dr. Michael Kohlhase is a Professor in the Computer Science department at FAU Erlangen-Nürnberg and an Adjunct Associate Professor at Carnegie Mellon University . His work spans Computer Science and Formal Methods , focusing on Mathematical Knowledge Management (MKM), Knowledge Representation , and Natural Language Processing (NLP) in STEM domains. He leads the KWARC (Knowledge Adaptation and Reasoning for Content) research group, driving projects like OMDoc , sTeX , and MathHub . His research emphasizes modular logical foundations for mathematical knowledge and large-scale document corpora analysis, with applications in computer-supported education and semantic document systems . Collaborations include extended visits to institutions such as SRI International , University of Amsterdam , and University of Edinburgh . Key projects include developing scalable module systems for formal mathematics, theory graph models for knowledge integration, and mathematical search engines like MathWebSearch . His work bridges formal logic with practical software systems , ensuring interoperability across proof assistants , computer algebra systems , and educational tools .

Michael HicksView profile

Professor

• Programming Languages
• Computer Security
• Quantum Computing
• +7 more

Michael Hicks is a Professor in the Department of Computer and Information Science at the University of Pennsylvania and an Amazon Scholar. Previously, he was a Professor at the University of Maryland (2002-2021) and Senior Principal Scientist at Amazon Web Services (2022-2025). He co-founded the Programming Languages research lab (PLUM) at Maryland and was its director, as well as Director of the Maryland Cybersecurity Center (MC2). He is a Fellow of the Association of Computing Machinery (ACM), former Chair of ACM SIGPLAN, and Editor-in-Chief of Proceedings of the ACM on Programming Languages (PACMPL). His research focuses on programming languages and their application to software security , quantum programming , and formal verification . He has pioneered dynamic software updating techniques, developed tools like Checked C for memory safety, and co-designed the Cedar authorization policy language at AWS. In quantum computing, he works on verified compilers like VOQC and Qunity to ensure reliability and correctness. His recent work trends include quantum programming languages , secure multi-party computation (e.g., Wysteria , Symphony ), and fuzz testing methodologies . He has contributed to formal verification for quantum programs and language-based security frameworks. Scientific Awards include: ACM Fellow He has advised numerous PhD and Master’s students , including James Parker, Andrew Ruef, Kesha Hietala, and Aseem Rastogi, who now hold academic and industry positions. His lab, PLUM , has been instrumental in advancing programming languages research.

Shriram KrishnamurthiView profile

Professor

• Programming Languages
• Type Systems
• Formal Methods
• +3 more

Shriram Krishnamurthi is a Professor in the Department of Computer Science at Brown University, specializing in programming languages, formal methods, and software education. His research focuses on language design, type systems, and pedagogical approaches to programming concepts. Recent publications highlight his work in areas such as Rust trait error debugging formal methods teaching tools automated type error telemetry document calculus design logic misconceptions in education His contributions also include program committee roles at major conferences like SPLASH, ICFP, and SIGCSE.

Ben GreenmanView profile

Assistant Professor

• Language Design
• Type Systems
• Formal Methods
• +1 more

Ben Greenman is an Assistant Professor at the University of Utah's Department of Computer Science. He has affiliations with institutions including Cornell University (BS, M.Eng), Northeastern University (PhD), and Brown University (CIFellows 2020). His work spans programming language design, type systems, formal methods, and human factors in software development. His research focuses on Gradual typing and type soundness Language design with emphasis on usability Formal methods education tools Empirical studies of type system usage Recent work analyzes temporal logic misconceptions, privacy-respecting telemetry for type errors, and macro systems without traditional syntax barriers. His publications reveal trends in Gradual type migration Runtime monitoring and profiling Visual formal methods Developer-centric language design He has received the CIFellows 2020 award and serves on program committees for SPLASH, Scheme, and other conferences. His work addresses both theoretical and practical aspects of programming language design.

KC SivaramakrishnanView profile

Assistant Professor

• Functional Programming
• Language Runtimes
• Concurrency
• +4 more

KC Sivaramakrishnan is an Assistant Professor at Indian Institute of Technology Madras and concurrently serves as CTO of Tarides. He works at the intersection of programming languages and systems, focusing on concurrency, distributed systems, and OCaml runtime development. Primary Affiliation: Indian Institute of Technology Madras Co-founder: Tarides His research explores: Concurrency and parallelism in OCaml Effect handlers for modular programming Mergeable Replicated Data Types for distributed systems Weak memory models and consistency guarantees Lock-free algorithms and safe multicore programming Recent publications focus on OCaml 5.0's concurrency features, effect handler integration, and verified CRDT implementations. He contributes to compiler design, runtime optimization, and testing frameworks for multicore systems. Service roles include committee memberships in SPLASH, ICFP, OCaml, and PROPL conferences. He actively bridges functional programming with systems research through practical implementations.