A hybrid neural network‐first principles approach to process modeling

• Automated Hybrid Machine Learning System for Production

  2026 Procedia CIRP article Materials Science Machine Learning in Materials Science Open access

  2

  citations
• Accelerating Computation of Sealing Deformation—A Physics-Informed Neural Network Framework for Hyperelastic Deformation

  2026 Lecture notes in computational science and engineering conference-paper Physics and Astronomy Model Reduction and Neural Networks

  0

  citations
• Hybrid soft sensor modeling for the wire section in tissue manufacturing: integrating first-principles and machine learning models

  2025 Nordic Pulp & Paper Research Journal article Engineering Fault Detection and Control Systems Open access

  0

  citations
• Working fluid screening for ORC-based Carnot batteries by deterministic global optimization of design and nominal operation

  2025 Optimization and Engineering article Engineering Process Optimization and Integration Open access

  2

  citations
• Advancing deformation calculation: a physics-informed deep graph learning framework for hyperelastic materials

  2025 Advanced Modeling and Simulation in Engineering Sciences article Physics and Astronomy Model Reduction and Neural Networks Open access

  3

  citations
• Extrapolation of cavitation and hydrodynamic pressure in lubricated contacts: a physics-informed neural network approach

  2025 Advanced Modeling and Simulation in Engineering Sciences article Engineering Tribology and Lubrication Engineering Open access

  8

  citations
• Physics-informed neural networks for dynamic process operations with limited physical knowledge and data

  2024 Computers & Chemical Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access

  54

  citations
• Physics-Informed Neural Networks for the Reynolds Equation with Transient Cavitation Modeling

  2024 Lubricants article Engineering Tribology and Lubrication Engineering Open access

  16

  citations
• Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions

  2024 BMC Bioinformatics software-paper Computer Science Machine Learning and Data Classification Open access

  5

  citations
• Extrapolation of Hydrodynamic Pressure in Lubricated Contacts: A Novel Multi-Case Physics-Informed Neural Network Framework

  2024 Lubricants article Physics and Astronomy Model Reduction and Neural Networks Open access

  19

  citations
• Shape‐optimization of extrusion‐dies via parameterized physics‐informed neural networks

  2023 PAMM article Physics and Astronomy Model Reduction and Neural Networks Open access

  7

  citations
• Physical pooling functions in graph neural networks for molecular property prediction

  2023 Computers & Chemical Engineering article Computer Science Computational Drug Discovery Methods Open access

  59

  citations
• A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method

  2022 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access

  12

  citations
• A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method

  2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access

  216

  citations
• HybridML: Open source platform for hybrid modeling

  2022 Computers & Chemical Engineering article Computer Science Modeling and Simulation Systems Open access

  30

  citations
• Machine Learning in Chemical Engineering: A Perspective

  2021 Chemie Ingenieur Technik article Materials Science Machine Learning in Materials Science Open access

  290

  citations
• Reconstructing Neutrino Energy using CNNs for GeV Scale IceCube Events

  2021 International Cosmic Ray Conference conference-paper Physics and Astronomy Neutrino Physics Research Open access

  5

  citations
• The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns

  2020 Chemie Ingenieur Technik article Physics and Astronomy Model Reduction and Neural Networks Open access

  24

  citations

18 results