David J. Hoelzle
Engineering · The Ohio State University
Publications
102
Citations
1,618
Est. group size
~7
Recurring co-author estimate
Active years
19
Publishing since 2008
David J. Hoelzle works on control systems and process monitoring for advanced manufacturing, particularly additive manufacturing (3D printing) methods like laser powder bed fusion and metal deposition. His research develops feedback control, machine learning, and digital-twin (simulation-based monitoring) techniques to make manufacturing processes more precise and autonomous, with applications ranging from industrial 3D printing to point-of-care medical device fabrication such as surgical fixation hardware and robotic tissue printing.
Publication output has gradually declined over the last decade, from about 12 papers/year in 2017 to roughly 4 per year in recent years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Experimental validation of the Ensemble Kalman Filter as a Laser Powder Bed Fusion digital twin
Additive manufacturing · 2026
- Closed-loop control of a robotic point-of-care manufacturing system for incremental forming of craniomaxillofacial skeletal fixation hardware
SSRN Electronic Journal · 2026
- Experimental Validation of the Ensemble Kalman Filter as a Laser Powder Bed Fusion Digital Twin
SSRN Electronic Journal · 2025
- Gaussian Process-Enhanced Multiple-Input Multiple-Output Model Predictive Control of Incremental Deformation of Craniomaxillofacial Fixation Plates
IFAC-PapersOnLine · 2025
- Virtual Surgical Planning for Point-of-Care Manufacturing
Procedia CIRP · 2024
- Kinematic analysis of engagement and bending capabilities of a point-of-care, incremental skeletal fixation plate bending system
Manufacturing Letters · 2024
- Machine Learning-Enhanced Model Predictive Control for Incremental Bending of Skeletal Fixation Plates
2024
- Robust Higher-Order Spatial Iterative Learning Control for Additive Manufacturing Systems
IEEE Transactions on Control Systems Technology · 2023
- An Additive Manufacturing Testbed to Evaluate Machine Learning-Based Autonomous Manufacturing
Journal of Manufacturing Science and Engineering · 2023
- Laser Powder Bed Fusion Process and Structure Data Set for Process Model Validations
Integrating materials and manufacturing innovation · 2023
- Statics and dynamics of an underwater electrostatic curved electrode actuator with rough surfaces
Journal of Micromechanics and Microengineering · 2023
- An advantage based policy transfer algorithm for reinforcement learning with measures of transferability
arXiv (Cornell University) · 2023
- Reinforcement Learning Enabled Autonomous Manufacturing Using Transfer Learning and Probabilistic Reward Modeling
IEEE Control Systems Letters · 2022
- A Surgical Robot for Intracorporeal Additive Manufacturing of Tissue Engineering Constructs
IEEE Robotics and Automation Letters · 2022
- On the Controllability and Observability of Temperature States in Metal Powder Bed Fusion
Journal of Dynamic Systems Measurement and Control · 2022
- Additive manufacturing×3
- Mechatronics×3
- IEEE Transactions on Control Systems Technology×3
- IFAC-PapersOnLine×3
- HAL (Le Centre pour la Communication Scientifique Directe)×3
- Yujie Shan
Engineering · Purdue University West Lafayette
- Huachao Mao
Engineering · Purdue University West Lafayette
- Lei Li
Engineering · The Ohio State University
- Eduardo Barocio
Engineering · Purdue University West Lafayette
- Akshay J. Thomas
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
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