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Renate Schmidt

Renate Schmidt

Dr

     https://orcid.org/0000-0002-6673-3333

    • Department of Computer Science, University of Manchester

      Oxford Rd Manchester

    Accepting PhD Students

    Personal profile

    My group

    Research Group(s)

    Overview

    Renate Schmidt is University Reader in Computer Science, Head of Postgraduate Research and Leader of Formal Methods Research Group in the Department of Computer Science at the University of Manchester. She served as Chair of the PGR Degrees Panel in the Faculty of Science and Engineering and was Member of the FSE Doctoral Academy Academic Leadership Team and the Faculty Graduate Committee (2021-2024). She is Associate Editor or Editorial Board Member of Artificial Intelligence Journal, Journal of Artificial Intelligence Research, Journal of Automated Reasoning and Journal of Applied Non-Classical Logic. She was PC (Co-)Chair of KR 2025 Recently Published Paper Track, IJCAR 2024, CADE-22, TABLEAUX 2017, FroCoS 2013. She was Vice-President of the Board of Trustees of CADE Incorporated (2020-2026, 2011-15). She serves on the Steering Committee of TABLEAUX and was member of the Board of Trustees of the Britisch Logic Colloquium.
     
    Her research involves the development of both theoretical results and implemented systems for knowledge representation, automated symbolic reasoning and formal methods. She has published widely in the areas of  automated reasoning , knowledge representation , ontology engineering , automated model building , multi-agent systems , non-classical logics , and relation algebras. What unites this broad range of topics is the need for solving decision problems , i.e., problems that can be solved in finite computation time and the development of practical automated reasoning methods. Significant contributions have been made on developing resolution and tableau decision procedures, tableau system synthesis, automated prover generation, forgetting/uniform interpolation and knowledge base extraction & processing. She is a co-author of a monograph on the topic "Second-Order Quantifier Elimination".
     
    Her current research is driven by the aim to develop improved automated support for knowledge representation, ontology extraction, knowledge re-engineering, information hiding, abductive learning and query answering in the context of ontologies, modal logics, guarded fragments and first-order logic. 
     

    Opportunities

    School of Engineering funded PhD Studentship in Symbolic AI for Knowledge Representation and Reasoning

    Closing date for first round of funding: 1 November 2026

    Applications are invited from PhD candidates in the area of content
    extracting and sharing for knowledge representation and reasoning. The project will explore how contemporary techniques in logic, automated reasoning, and specifically ontology modularisation, forgetting, interpolation, subontology generation, definability and ontology alignment can be used, refined and applied for automated extraction and reuse of content from knowledge bases.

    Other opportunities:

    Students interested in doing a PhD in areas related to ontology engineering, knowledge representation and reasoning, symbolic AI, automated reasoning, logic, logic-based multi-agent systems and any topics close to my research interests are welcome to contact me to discuss possible projects.

    I am currently particularly interested in supervising projects on these topics:

    • Automated support for focussed sharing, distribution, tracking and learning of content of medical ontologies underpinning healthcare services.
    • Query answering for expressive description logics based on saturation-based automated reasoning.
    • Advancement and application of second-order quantifier elimination, in particular, exploring open questions and applications of automating the witness SOQE problem.

    Anybody with a keen interest and background in (a subset of) ontologies, classical logic, description or modal logic, automated reasoning, knowledge representation and reasoning and symbolic AI will enjoy these projects. The research may be focussed on investigation of the theoretical underpinnings, it may be focussed on enhancing existing technologies developed in my group, develop new technology, or it may be application-oriented. Most likely the research will involve a combination of these.

    Since deadlines for University/Faculty/School PhD studentships are normally in very early in November to middle of January it is advisable to apply early in the academic year. 

    Education/Academic qualification

    Doctor of Engineering, Optimised Modal Translation and Resolution, Universitat des Saarlandes

    Award Date: 3 Nov 1997

    Areas of expertise

    • QA75 Electronic computers. Computer science
    • Automated Reasoning
    • Computional Logic
    • Knowledge Representation
    • Symbolic AI
    • Knowledge Base Extraction and Processing
    • Query Answering
    • Decidability Problems

    Research Highlights, Institutes and Platforms

    • Digital Futures
    • Institute for Data Science and AI

    Keywords

    • Computational Logic
    • Automated Reasoning
    • Knowledge-Based AI
    • Knowledge Representation
    • Deduction
    • Forgetting
    • Decidability Problems

    Accepting PhD students

    • Accepting PhD students

    Expertise related to UN Sustainable Development Goals

    In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

    1. SDG 13 - Climate Action
      SDG 13 Climate Action

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