Published in 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), 2021
Recommended citation: M. Xavier, S. Patil, V. Vyatkin. "Cyber-physical automation systems modelling with IEC 61499 for their formal verification." 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), 2021.
Published in 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2021
Recommended citation: M. Xavier, J. Håkansson, S. Patil, V. Vyatkin. "Plant model generator from digital twin for purpose of formal verification." 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2021.
Published in 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), 2022
Recommended citation: M. Xavier, V. Dubinin, S. Patil, V. Vyatkin. "Process mining in industrial control systems." 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), 2022.
Published in arXiv preprint arXiv:2211.03681, 2022
Recommended citation: M. Xavier, V. Dubinin, S. Patil, V. Vyatkin. "Plant model generation from event log using ProM for formal verification of CPS." arXiv preprint arXiv:2211.03681, 2022.
Published in 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), 2022
Recommended citation: M. Xavier, V. Dubinin, S. Patil, V. Vyatkin. "An interactive learning approach on digital twin for deriving the controller logic in IEC 61499 standard." 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), 2022.
Published in International Journal of Sustainable Energy, 2023
Recommended citation: P. Sobha, A. Muthusamypillai, M. Xavier. "Green transport and renewable power: an integrated analysis for India's future." International Journal of Sustainable Energy, 2023.
Published in 2023 IEEE International Conference on Prognostics and Health Management (ICPHM), Montreal, QC, Canada, 2023
Recommended citation: P. Sobha, M. Xavier, P. Chandran. "A Comprehensive Approach for Gearbox Fault Detection and Diagnosis Using Sequential Neural Networks." 2023 IEEE International Conference on Prognostics and Health Management (ICPHM), Montreal, QC, Canada, 2023.
Published in 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), Helsinki, Finland, 2023
Recommended citation: P. Ovsiannikova, E. Le Priol, V. Perret, P. Jhunjhunwala, M. Xavier, V. Vyatkin. "Formal verification of observers supervising a cyber-physical system implemented using IEC 61499." 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), Helsinki, Finland, 2023.
Published in 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), Helsinki, Finland, 2023
Recommended citation: M. Xavier, T. Liakh, S. Patil, V. Vyatkin. "Developing a Test Suite for Evaluating IEC 61499 Application Portability." 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), Helsinki, Finland, 2023.
Published in 44th International Conference on Application and Theory of Petri Nets and Concurrency (PETRI NETS 2023), Lisbon, Portugal, 2023
Recommended citation: M. Xavier, S. Patil, V. Dubinin, V. Vyatkin. "Formal modelling, analysis, and synthesis of modular industrial systems inspired by Net Condition/Event Systems." 44th International Conference on Application and Theory of Petri Nets and Concurrency (PETRI NETS 2023), Lisbon, Portugal, 2023.
Published in 2023 IEEE 21st International Conference on Industrial Informatics (INDIN), Lemgo, Germany, 2023
Recommended citation: M. Xavier, P. Sobha, S. Patil, V. Vyatkin. "DeLMS: A Decentralized Learning Management System using Ethereum Smart Contracts and IPFS." 2023 IEEE 21st International Conference on Industrial Informatics (INDIN), Lemgo, Germany, 2023.
Published in 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA), Sinaia, Romania, 2023
Recommended citation: B. Wiesmayr, M. Xavier, S. Patil, A. Zoitl, V. Vyatkin. "Generating Portable Test Cases for IEC 61499 FBs from Interface Behaviour Specifications." 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA), Sinaia, Romania, 2023.
Published in IEEE Open Journal of the Industrial Electronics Society, 2023
Recommended citation: G. Lilli, M. Xavier, E. Le Priol, V. Perret, T. Liakh, R. Oboe, V. Vyatkin. "Formal Verification of the Control Software of a Radioactive Material Remote Handling System, Based on IEC 61499." IEEE Open Journal of the Industrial Electronics Society, 2023.
Published in 2024 IEEE International Conference on Industrial Technology (ICIT), 2024
Recommended citation: I. Faqrizal, T. Liakh, M. Xavier, G. Salán, V. Vyatkin. "Probabilistic Model Checking for IEC 61499: A Manufacturing Application." 2024 IEEE International Conference on Industrial Technology (ICIT), 2024.
Published in IEEE Open Journal of the Industrial Electronics Society, 2024
Recommended citation: M. Xavier, V. Dubinin, S. Patil, V. Vyatkin. "A framework for the generation of monitor and plant model from event logs using process mining for formal verification of event-driven systems." IEEE Open Journal of the Industrial Electronics Society, 2024.
Published in IECON 2024 – 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, USA, 2024
Recommended citation: M. Xavier, T. Liakh, S. Patil, V. Vyatkin. "LLM-Powered Multi-Actor System for Intelligent Analysis and Visualization of IEC 61499 Control Systems." IECON 2024 – 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, USA, 2024.
Published in PhD Dissertation, Luleå University of Technology, 2025
Recommended citation: M. Xavier. "Enabling dependable flexibility in industrial automation with formal methods integrated to development toolchains." PhD Dissertation, Luleå University of Technology, 2025.
Published in IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society, 2025
Recommended citation: M. Xavier, S. Patil, C.-W. Yang, V. Vyatkin. "ReACT-Gen AI Agents for Reasoning, Planning, and Testing in IEC 61499-Based Control Systems." IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society, 2025.
Published in arXiv preprint, 2026
Recommended citation: M. Xavier, M. Jolly, M. Xavier. "Agentproof: Static Verification of Agent Workflow Graphs." arXiv preprint, 2026.
Published in arXiv preprint, 2026
Recommended citation: M. Xavier, M. Jolly, M. Xavier. "IndustriConnect: MCP Adapters and Mock-First Evaluation for AI-Assisted Industrial Operations." arXiv preprint, 2026.
Generalization & Scaling, LTU, 2025
A key challenge in Neural Combinatorial Optimization is generalizing to instances that are larger or drawn from different distributions than those seen during training. I investigate curriculum learning, data augmentation, and inference-time search strategies to improve out-of-distribution robustness, and I benchmark learned solvers against exact and metaheuristic baselines (OR-Tools, LKH, Gurobi) on solution quality, optimality gap, and runtime.
Learned Heuristics, LTU, 2025
Beyond constructing solutions in a single pass, I research learned improvement operators that iteratively refine an existing solution. This includes neural local search, guided and large-neighborhood search, and hybrid schemes that combine learned policies with classical operations-research techniques to reach lower optimality gaps within a fixed compute budget.
Objectives & Evaluation, LTU, 2025
At inference time, neural solvers typically sample multiple candidate solutions and keep the best one. I am interested in training directly for these best-of-K settings by optimizing Pass@K and Max@K objectives, so that the training signal matches how models are actually deployed. This work explores objective design, variance reduction, and the trade-off between solution diversity and per-sample quality.
Policy Optimization, LTU, 2025
I study how modern policy-optimization algorithms can train neural solvers end-to-end without labelled optimal solutions. This includes policy-gradient and actor–critic methods, REINFORCE with greedy and rollout baselines, and recent algorithms such as GRPO, PKPO, RSPO, and PPO. My goal is to make training more stable, sample-efficient, and better aligned with the true optimization objective of the underlying combinatorial problem.
Neural Combinatorial Optimization, LTU, 2025
My core research interest is Neural Combinatorial Optimization (NCO): training deep neural networks to solve classic combinatorial optimization problems such as the Travelling Salesman Problem (TSP), Capacitated Vehicle Routing (CVRP), scheduling, and assignment. I focus on attention-based encoder–decoder architectures, Pointer Networks, and graph neural networks that learn to construct high-quality solutions directly from data, complementing or replacing hand-crafted heuristics.
Applied RL (Aerobase), Aerobase, 2025
I develop reinforcement-learning methods that minimize defects — such as porosity, cracking, residual stress, and distortion — in parts produced by Directed Energy Deposition (DED), Laser Powder Bed Fusion (LPBF), and Wire Arc Additive Manufacturing (WAAM). The RL agents learn from multiphysics simulation feedback, including thermal and mechanical finite element (FEM) analysis, microstructure analysis, and melt-pool computational fluid dynamics (CFD) simulations, closing the loop between process parameters, deposition-path planning, and predicted part quality.
Applied NCO (Aerobase), Aerobase, 2025
At Aerobase, I apply neural combinatorial optimization to robot path generation and toolpath planning across metal additive-manufacturing processes — Directed Energy Deposition (DED), Laser Powder Bed Fusion (LPBF), and Wire Arc Additive Manufacturing (WAAM). I formulate deposition- and scan-path sequencing as a combinatorial optimization problem and train attention-based neural solvers to generate paths that reduce travel, balance thermal load, and improve build quality, throughput, and material efficiency.