Dr. Ashlin Iser

Data Infrastructure, Systems Engineering & Efficient Symbolic Reasoning

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Deep expertise in low-level systems engineering, database modeling, and symbolic reasoning, grounded in a strong academic and research background with over 20 years of hands-on software engineering spanning bare-metal performance optimization to full-stack system design. I develop algorithms and heuristics that push the practical boundaries of complex combinatorial problems, and architect systems where learning and reasoning synergize to enhance one another.

🔬 Research Interests

I specialize in Efficient Symbolic Reasoning (SAT/SMT, combinatorial optimization, constraint solving, planning, and scheduling) and its two-way relationship with machine learning: AI for reasoning – data-driven algorithm selection, configuration, and tuning to push solvers to peak performance – and reasoning for AI – trustworthy, explainable AI that makes learned models verifiable and interpretable, with an emerging interest in neuro-symbolic architectures that ground them in sound solvers via solver-in-the-loop pipelines. My work spans high-performance solver engineering for combinatorial problems and their real-world applications, such as planning, scheduling, software verification, and formal explainability.

📈 Engagement

Professional Activities: Organizer of the International SAT Competitions (2015; annually since 2020), directing distributed evaluation pipelines across high-performance compute clusters; active program committee member (e.g., SAT, ECAI) and reviewer for leading journals (e.g., AIJ, NCOMMS).

Teaching & Mentorship: Focused on graduate-level courses (including Practical SAT Solving, consistently evaluated in the top percentile, and the Recent Advances in SAT Solving seminar) along with mentoring research and software engineering projects. Experienced in organizing large-scale undergraduate lab courses (Algorithms, Programming) with up to 700 participants.

Supervision: Over 30 completed theses (Bachelor, Master, Diploma), split between academic research groups and industry-partnered software engineering teams (CAS Software AG, PLANTA Projekt-Management Systeme GmbH).

Publications: 24 peer-reviewed papers (journals, conferences & workshops), listed on my Google Scholar profile.

Open Source: Author and maintainer of open-source tools on my GitHub profile, most notably the Global Benchmark Database (GBD), a modular data ecosystem utilizing decentralized, content-based hashing for automated metadata indexing.

🛠 Technical Expertise

Systems & Performance Engineering: Bare-metal C++ optimization, memory footprint tuning, high-performance solver engineering for combinatorial problems, and parallel algorithm design.

Data Infrastructure & Architecture: End-to-end system design spanning database modeling, indexing strategies, automated extraction pipelines, zero-bloat CLI tools, and web interfaces.

Technologies & Paradigms: High Performance Computing (HPC), Distributed Pipelines, Constraint & Logic Solving, Database Systems and Modeling, Machine Learning, Software Testing, Static Code Analysis, Git, CI/CD.

Languages & Tools: C++, Python, SQL, C, Java, diverse Scripting Languages and Web Technologies, and deep experience across Linux systems environments.

📚 Selected Publications

Sustainable Benchmarking Tool (SAT@FLOC, Lisbon 2026) Ashlin Iser, Marie Anastacio, Théo Matricon, Laurent Simon, Holger H. Hoos

Active Learning for SAT Solver Benchmarking (JAR 2025) Tobias Fuchs, Jakob Bach, Ashlin Iser

Global Benchmark Database (SAT, Pune 2024) Ashlin Iser, Christoph Jabs

Oracle-Based Local Search for Pseudo-Boolean Optimization (ECAI, Krakow 2023) Ashlin Iser, Jeremias Berg, Matti Järvisalo

A Comprehensive Study of k-Portfolios of Recent SAT Solvers (SAT@FLOC, Haifa 2022) Jakob Bach, Ashlin Iser, Klemens Böhm

Unit Propagation with Stable Watches (CP 2021) Ashlin Iser, Tomáš Balyo

SAT Competition 2020 (AIJ 2021) Nils Froleyks, Marijn Heule, Ashlin Iser, Matti Järvisalo, Martin Suda