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Andreas Schlapbach's Publications

Welcome to the repository of my research publications. This collection encompasses a wide range of topics in software engineering, machine learning, and artificial intelligence, reflecting the evolution of research interests over the years.

The early work explores two foundational ideas in software engineering: the π-calculus as a formal basis for component composition languages, and the Meta-Object Facility (MOF) as a meta-meta-model for language-independent meta-model interchange via XMI.

Later work applies machine learning (Gaussian Mixture Models, Hidden Markov Models, Support Vector Machines) to handwriting recognition and writer identification, contributing to the fields of document analysis and pattern recognition.

Recent research focuses on the design and formal verification of LLM Agentic systems, proposing new paradigms for agent interoperability and tool protocol semantics.

This repository serves as a comprehensive archive of these contributions, spanning from foundational software composition theories to cutting-edge AI agent research.

If you're interested in connecting professionally, you can find me on LinkedIn.

Publications

Preprints

Books

Journal Articles

Book Chapters

Conference Papers

Theses & Technical Reports

Presentations

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mindmap
  root((Research Focus))
    Software Composition & Reengineering
      π-Calculus-Based Composition Language
      Agents · Forms · Channels
      XMI & XML Metadata Interchange
      MOF Meta-Meta-Model
      MOOSE Reengineering Environment
      Component-Oriented Programming
      White-Box vs Black-Box Reuse
    Handwriting & Documents
      Machine Learning - GMM · HMM · SVM
      Handwriting Recognition & Analysis
      Writer Identification - Offline & Online
      Document Analysis & Pattern Recognition
    LLM Agentic Systems
      Agent Tool Protocols - SGD & MCP
      Formal Verification & Process Calculus
      AI Governance & Schema-Driven Interoperability
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Document Organization

All papers are organized chronologically by publication year and venue:

  • 2026 — arXiv preprints on LLM Agentic systems
  • 2011 — Pattern Analysis and Applications gender detection journal paper
  • 2008 — PhD thesis book (IOS Press/DISKI); DAS whiteboard recognition; EUSIPCO, ICPR readability estimation; IJPRAI gender detection
  • 2007 — Book draft on machine learning in document analysis; book chapter on GMM-based writer identification; gender/handedness detection
  • 2006 — DAS, ICPR, IWFHR follow-up work
  • 2005 — ICDAR, IGS publications
  • 2004 — ICPR, IWFHR initial conferences
  • 2002 — Master thesis on white-box reuse in JPiccola (Universität Bern)
  • 2001 — Bachelor thesis on XMI/MOOSE, a reengineering environment (Universität Bern)

How to Use This Repository

  1. Browse papers — All PDFs are in the root directory
  2. Review by topic — Check the conference/journal name for specific focus areas
  3. Access full texts — Each PDF contains the complete paper and results
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timeline

    2001        : Schl01a
                : XMI/MOOSE Technical Report
    2002        : Schl03a
                : Diplomarbeit JPiccola
    2004 - 2006 : ICPR · IWFHR · DAS · ICDAR · IGS
                : Handwriting Recognition
                : Writer Identification
                : Document Analysis
    2007        : Book Chapter
                : Gender & Handedness Detection
    2008        : PhD thesis (IOS Press) · DAS
                : EUSIPCO · ICPR · IJPRAI
                : Readability Estimation
                : Gender Detection
    2011        : PAA
                : Gender Detection
    2026        : arXiv Preprints
                : LLM Agent Systems
                : Formal Verification
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About

This archive preserves research publications spanning:

  • Software composition grounded in the π-calculus (agents, forms, channels) and component-oriented programming
  • Meta-modeling via XMI/XML metadata interchange and the MOF meta-meta-model
  • Reuse strategies including white-box and black-box approaches in reengineering environments
  • Machine learning applied to document analysis using Gaussian Mixture Models, Hidden Markov Models, and Support Vector Machines
  • Handwriting recognition, analysis, and writer identification (offline and online)
  • Document image analysis and pattern recognition
  • LLM agentic systems, including tool protocols (SGD, MCP) and formal verification
  • AI governance and schema-driven interoperability

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