I am a postdoctoral researcher developing reliable and explainable AI systems through neuro-symbolic integration. My research focuses on combining machine learning with knowledge representation and automated reasoning to transform natural language into expressive symbolic representations that can be verified and reasoned over. I investigate applications in domains where correctness, transparency, and formal guarantees are critical, including automated building compliance checking, scholarly communication, and aerospace engineering.
Research Interests
- Logics
- Information theory
- Knowledge representation & reasoning
- Knowledge extraction
- Unsupervised learning
- Automated machine learning
- Neuro-symbolic AI
- eScience
- Building compliance checking
- Aerospace engineering
Research directions
Description logic-based natural language formalization
Developing methods for transforming domain knowledge expressed in natural language into machine-interpretable symbolic representations.
Publications:
- I. Baimuratov. (2026). DeLTA: A Description Logic–based Annotation Schema for Constructing Expressive OWL DL Axioms from Text. Description Logics 2026.
Repositories:
- DeLTA: Description Logic–based Text Annotation Schema
Automated building compliance checking
Representing regulatory requirements as OWL DL axioms and enabling reasoning-based compliance checking.
Publications:
- I. Baimuratov & D. Turygin. (2025). Representing Normative Regulations in OWL DL for Automated Compliance Checking Supported by Text Annotation. LDAC 2025.
- U. Saluz, I. Baimuratov & P. Geyer. (2025). Large-language-model-based building-information-model alignment for automatic-compliance-checking: towards closing the gap between model authoring and model checking for kit-of-parts architecture. EG-ICE 2025.
Computational support in peer review
Combining computational argumentation, semantic representations, and machine learning for analyzing scientific peer review.
Publications:
- I. Baimuratov, E. Lisanyuk, & D. Prokudin. (2023). Dispute Resolution with OWL DL and Reasoning. Description Logics 2023.
- I. Baimuratov, A. Karpovich, E. Lisanyuk & D. Prokudin. (2024). Argument Identification for Neuro-Symbolic Dispute Resolution in Scientific Peer Review. ACM/IEEE JCDL 2024.
- I. Baimuratov & A. Karpovich. (2025). Abstract Argumentation Frameworks Extraction for Dispute Resolution in Scientific Peer Review. SEMANTiCS-PDWT 2025.
Repositories:
- computational_argumentation_dung: Encoding of Dung’s abstract argumentation frameworks in OWL DL
- ReviewArgumentationFramework: A corpus of peer reviews with annotated abstract argumentation frameworks
Scholarly knowledge infrastructures
Building semantic infrastructures for scientific knowledge management.
Publications:
- C. Bless, I. Baimuratov & O. Karras. (2023). SciKGTeX-a LATEX package to semantically annotate contributions in scientific publications. ACM/IEEE JCDL 2023.
Repositories:
- PDF2ORKG: Importing SciKGTeX annotations into ORKG
Knowledge representation for engineering
Advancing FAIR principles in engineering domains.
Publications:
- I. Antonau, S. Warnakulasuriya, S. Baars, I. Baimuratov, T. Wittenborg, L. Kreuzeberg, A. Attravanam & R. Wüchner. (2025). Challenges in realizing 3rd generation multidisciplinary design optimization. Advances in Computational Science & Engineering (ACSE), 5.
- I. Baimuratov, T. Wittenborg, I. Antonau & S. Baars. (2025). Enabling Reuse of Knowledge from Coupled Systems in Aerospace Engineering. SEMANTiCS-PDWT 2025.
Repositories:
- coupled_modelling: Knowledge representation for multidisciplinary optimisation
Other publications
- I. Baimuratov. (2024). Diagrammatic Reasoning for ALC Visualization with Logic Graphs. ACM Web Conference (WWW) 2024.
- B. Zhou, Y. Svetashova, T. Pychynski, I. Baimuratov, A. Soylu & E. Kharlamov. (2020). SemFE: Facilitating ML pipeline development with semantics. ACM CIKM 2020.
See full list at Google Scholar
Education
- 2009-2014 Specialist Student (equiv. to MA). Faculty of Philosophy, SPBU, St. Petersburg, Russia. Specialization: Logic
- 2016-2020 Ph.D. student. Faculty of Software Engineering and Computer Systems, ITMO University, St. Petersburg, Russia. Thesis: The method of data models complex evaluation for automated unsupervised machine learning
Career
- 2019-2022 ITMO University, Faculty of Software Engineering and Computer Systems, associate professor, software developer.
- 2022-…. Leibniz University Hannover, L3S/TIB joint lab, postdoc.
Projects
- 2019-2021 “Digital University”: intelligent services for students and university staff
- 2020-2022 NSR Specification: digital platform with automated technologies for building compliance checking
- 2021-2022 Picvario: intelligent module for a media asset management platform
- 2022-…. ORKG: service for machine-reusable descriptions of research findings
- 2023-2025 Formal philosophy of argumentation: OWL-based dispute resolution
- 2023-…. SE2A ICA-B4.2: knowledge representation in multidisciplinary analysis for aerospace engineering
- 2026-…. DIPONI: digital transformation and AI-supported process optimization in rubber and polymer processing
Student supervision
In progress:
- MA Thesis: Semantic Representation of Scientific Claims for Automated Evidence-based Verification
- MA Thesis: Generation of NLU Benchmarks from Formal Representations for Contamination-Proof LLM Evaluation
Suggested topics:
- Reinforcement Learning from Symbolic Reasoning Feedback: A Use Case from Building Compliance Checking
- Facilitating OWL DL Representation of Scientific Claims Using DeLTA for Consistency Checking
- Automating Translation of Natural Language Requirements into OWL DL Language Using DeLTA Annotation Schema: A Use Case from Building Compliance Checking
- GraphReview: Structured Representation for Formal-Argumentation-Based Computational Support in Scientific Peer Review
- Meta-learning for Data-Driven Retrieval of Relevant Scientific Literature
- Aligning Automatically Generated and Crowdsourced Scholarly Knowledge Graphs: A Case Study of CS-KG and ORKG
See more details here
Lecturing
- Non-classical logics (ITMO University, MA students)
- Machine learning methods (ITMO University, MA students)
- Contemporary AI methods (ITMO University, PhD students)
Other achievements
- Creator of scientific workshop of Faculty of Software Engineering and Computer Systems, ITMO University
- Member of the Council of Young Scientists of ITMO University
- Program chair: MICSECS 2020-2021
- Program chair: DAMDID 2022-…
- Vannevar Bush best paper award at JCDL 2023 for “SciKGTeX - A LaTeX Package to Semantically Annotate Contributions in Scientific Publications”
- L3S Best Paper Recognition 2024 for “Diagrammatic Reasoning for ALC Visualizations with Logic Graphs”
- SymGenAI4Sci 2025 best paper award for “Abstract Argumentation Frameworks Extraction for Dispute Resolution in Scientific Peer Review”
Technical skills
- Operating Systems: Windows, Linux
- Database Management System: SQLite, MySQL, MongoDB, GraphDB
- Programming/Query languages: Python, SQL, SPARQL, Datalog
- Data libs: NumPy, pandas
- NLP libs: NLTK, CoreNLP, spaCy
- ML libs: SciPy, sklearn, mlxtend, statsmodels, Keras, transformers
- Visualization: matplotlib, plotly, graphviz
- Semantic technologies: RDF, OWL, Protégé, owlready2
- App libs: click , Flask, FastAPI, Dash
- Tools: LaTeX, Jupyter Notebook, Google colab, WebAnno/Inception, Git
Languages
- Russian: native
- English: full professional proficiency
- German: limited working proficiency
Contacts & Links
- Berlin, Germany
- baimuratov.i@gmail.com
- ResearchGate
- ORCID