Suyog Ghungrad

University of Illinois Chicago — United States

Engineering · Physical Sciences

6h-index96citations12works6.62yr avg
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Research Topics

Additive Manufacturing and 3D Printing Technologies(9), Additive Manufacturing Materials and Processes(7), Manufacturing Process and Optimization(5), Innovations in Concrete and Construction Materials(4), Machine Learning in Materials Science(3)

Publications12 total

A physics-informed neural network framework for decomposition and path planning in multi-laser additive manufacturing
Manufacturing Letters·2025· 1 citedOpen Access
Kinematics-Guided Multi-Task Learning for Transferable Models in Robotic Manufacturing
SSRN Electronic Journal·2025Open Access
A review on physics-informed machine learning for process-structure-property modeling in additive manufacturing
Journal of Manufacturing Processes·2024· 34 citedOpen Access
Stress Analysis in Multi-head Large Scale Additive Manufacturing
2024
Kinematics-guided data-driven energy surrogate model for robotic additive manufacturing
Manufacturing Letters·2024· 2 citedOpen Access
Three-dimensional spatial energy-quality map construction for optimal robot placement in multi-robot additive manufacturing
Robotics and Computer-Integrated Manufacturing·2024· 9 citedOpen Access
Synchronous Multi-Layer Cooperative 3d Printing for Enhanced Structural Integrity
SSRN Electronic Journal·2024Open Access
Energy-efficient and quality-aware part placement in robotic additive manufacturing
Journal of Manufacturing Systems·2023· 15 citedOpen Access
Architecture-Driven Physics-Informed Deep Learning for Temperature Prediction in Laser Powder Bed Fusion Additive Manufacturing With Limited Data
Journal of Manufacturing Science and Engineering·2023· 20 cited
Three-Dimensional Spatial Energy-Quality Map Construction for Optimal Robot Placement in Multi-Robot Additive Manufacturing
SSRN Electronic Journal·2023· 1 citedOpen Access
Physics-Informed Artificial Intelligence for Temperature Prediction in Metal Additive Manufacturing: A Comparative Study
Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing·2022· 7 cited
Model-based deep learning for additive manufacturing: New frontiers and applications
Manufacturing Letters·2021· 7 cited

Frequent Co-authors

Azadeh Haghighi(12), Meysam Faegh(3), Benjamin Gould(3), Sarah J. Wolff(3), Reihane Arabpoor Hajy Abady(2), João Pedro Oliveira(1), Prahalada Rao(1), Abdullah Mohammed(1), Mojtaba Soltanalian(1), Sean Rescsanski(1), Farhad Imani(1)