Eric Coatanea - Helsinki University of Technology (TKK)

基本信息

Career Trajectory

Bio

Eric works at Tampere University. He does research in modelling and simulation for Manufacturing and Engineering design. He is developing new Machine Learning methods and tools for additive manufacturing, early conceptual modelling, simulation and decision support using partial and ill-defined knowledge. His current most active project is Dimensional Analysis Conceptual Modelling Framework. He is also co-founder of two spin-off companies and act as head of the board of Dynavio cooperative.

Research Interests

Papers共 113 篇Author StatisticsCo-AuthorSimilar Experts

By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选

Machine learning-supported manufacturing: a review and directions for future research

Baris Ordek,Yuri Borgianni,Eric Coatanea

PRODUCTION AND MANUFACTURING RESEARCH-AN OPEN ACCESS JOURNALno. 1 (2024)

Cited0Views0Bibtex

Modeling and Optimization of Height-Related Geometrical Parameters for Thin Wall Structures Manufactured by Metal Additive Manufacturing

M. Rahmani Dehaghani,Yifan Tang,Suraj Panicker, Di Wu,Eric Coatanea,G. Gary Wang

The international journal of advanced manufacturing technology/International journal, advanced manufacturing technologyno. 9-10 (2023): 4663-4675

Cited0Views0Bibtex

Self-supervised Representation Learning Anomaly Detection Methodology Based on Boosting Algorithms Enhanced by Data Augmentation Using StyleGAN for Manufacturing Imbalanced Data

Yoonseok Kim,Taeheon Lee, Youngjoo Hyun,Eric Coatanea, Siren Mika,Jeonghoon Mo,Youngjun Yoo

Computers in industry (2023): 104024-104024

Cited0Views0EIBibtex

Roadmap on Artificial Intelligence and Big Data Techniques for Superconductivity

Superconductor science and technology/Superconductor science & technologyno. 4 (2023): 043501-043501

Cited6Views0Bibtex

A Dimension Selection-Based Constrained Multi-Objective Optimization Algorithm Using a Combination of Artificial Intelligence Methods

Di Wu,Dmitry Sotnikov,G. Gary Wang,Eric Coatanea,Mika Lyly,Tiina Salmi

JOURNAL OF MECHANICAL DESIGNno. 8 (2023)

Cited0Views0Bibtex

Assessing the Effect of Infill Strategies on Hardness Properties of Cuboidal Parts Printed with Wire and Arc Additive Manufacturing

Jari Kuosmanen, Aaron Azadikhah,Suraj Panicker,Hossein Mokhtarian, Di Wu, Akshay Dhalpe,Antoine Queguineur,Éric Coatanéa

Lecture notes in networks and systemspp.133-144, (2023)

Cited0Views0Bibtex

Online Thermal Field Prediction for Metal Additive Manufacturing of Thin Walls

Yifan Tang,Mostafa Rahmani Dehaghani,Pouyan Sajadi,Shahriar Bakrani Balani, Akshay Dhalpe,Suraj Panicker, Di Wu,Eric Coatanea,G. Gary Wang

JOURNAL OF MANUFACTURING PROCESSES (2023): 529-550

Cited0Views0Bibtex

A Prospective Analysis of the Engineering Design Discipline Evolution Based on Key Influencing Trends

Eric Coatanea,Hari Nagarajan,Suraj Panicker,Hossein Mokhtarian

Journal of integrated design & process science（2023）

Cited1Views0EIBibtex

Graph Models for Engineering Design: Model Encoding, and Fidelity Evaluation Based on Dataset and Other Sources of Knowledge

Eric Coatanea,Hari Nagarajan,Hossein Mokhtarian, Di Wu,Suraj Panicker,Andres Morales-Forero,Samuel Bassetto

AI EDAM/Artificial intelligence for engineering design, analysis and manufacturing (2023)

Cited0Views0Bibtex

Integrated modeling of heat transfer, shear rate, and viscosity for simulation-based characterization of polymer coalescence during material extrusion

Shahriar Bakrani Balani,Hossein Mokhtarian,Eric Coatanea,France Chabert,Valerie Nassiet,Arthur Cantarel

JOURNAL OF MANUFACTURING PROCESSES (2023): 443-459

Cited2Views0Bibtex

Author Statistics

Co-Author

Co-Institution

D-Core

合作者
学生
导师

No result temporarily, you can search similar Scholar with the same research interest

Data Disclaimer

The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn