Chaitanya Krishna Vallabh

• PhD (2017) Clarkson University (Mechanical Engineering)
• MS (2014) Clarkson University (Mechanical Engineering)
• Bachelor of Technology (2012) Vignan's Institute of Technology and Aeronautical Engineering (Aeronautical Engineering)

• StevensChefs LLC Member
• Senior Design Chair
• Senior Design Member
• Mechanical Engineering Admitted Students Weekend Member
• ME AI Taskforce committee Member
• ME Industry Outreach Committee Member
• Senior Design Member
• Senior Design Chair
• Mechanical Engineering Admitted Students Weekend Member

• Engineering Applications of Artificial Intelligence Reviewer
• Additive Manufacturing Reviewer
• Measurement Reviewer
• Journal of Manufacturing Processes Reviewer

• ASEE – American Society for Engineering Education Member
• Adhesion Society Member
• ASME – American Society of Mechanical Engineers Member

Conference Proceeding

1. Fontaine, M.; Vallabh, C. (2025). Effects of Spatial Ability on the Mastery of Statics Concepts. 2025 ASEE Annual Conference \& Exposition.
2. Mahmoud, Y.; Lyu, J.; Vallabh, C.; Manoochehri, S. (2024). Melt Pool Depth Prediction in Directed Energy Deposition Single-Track Prints Using Point Cloud Analysis. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (vol. 88346, pp. V02AT02A024).
3. Akhavan, J.; Xu, K.; Vallabh, C.; Manoochehri, S. (2024). Real-Time Print Tracking in Metal Additive Manufacturing Using Acoustic Emission Sensors and Vision Transformer Algorithms. Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability (pp. V002T07A009). American Society of Mechanical Engineers.
   https://doi.org/10.1115/msec2024-125391.
4. Fontaine, M.; Vallabh, C. (2024). Correlating Common Errors in Statics Problem Solving with Spatial Ability. 2024 ASEE Annual Conference \& Exposition.
5. Caputo, A.; Neu, R. W.; Vallabh, C.; Zhao, X.; Zhang, H. (2023). Investigating the Influence of Build Parameters and Porosity on Fatigue of AM IN718. TMS Annual Meeting \& Exhibition (pp. 571--591).
6. Lyu, J.; Akhavan, J.; Mahmoud, Y.; Xu, K.; Vallabh, C.; Manoochehri, S. (2023). Real-Time Monitoring and Gaussian Process-Based Estimation of the Melt Pool Profile In Direct Energy Deposition. International Manufacturing Science and Engineering Conference. ASME.
7. Lyu, J.; Akhavan, J.; Mahmoud, Y.; Xu, K.; Vallabh, C.; Manoochehri, S.. Real-Time Monitoring and Gaussian Process-Based Estimation of the Melt Pool Profile In Direct Energy Deposition. International Manufacturing Science and Engineering Conference. ASME.

Journal Article

1. Xu, K.; Vallabh, C.; Manoochehri, S. (2025). Integrating Machine Learning with Multimodal Monitoring System Utilizing Acoustic and Vision Sensing to Evaluate Geometric Variations in Laser Directed Energy Deposition. arXiv.
   https://doi.org/10.21203/rs.3.rs-7435959/v1.
2. Xu, K.; Mahmoud, Y.; Manoochehri, S.; Vallabh, C. (2025). Using acoustic emission signal analysis and machine learning algorithms for predicting mechanical hardness in laser directed energy deposition parts. The International Journal of Advanced Manufacturing Technology (pp. 1--20). Springer London London.
3. Akhavan, J.; Vallabh, C.; Zhao, X.; Manoochehri, S. (2024). Binocular Model: A deep learning solution for online melt pool temperature analysis using dual-wavelength Imaging Pyrometry. arXiv preprint arXiv:2408.11126.
4. Zhang, H.; Caputo, A. N.; Vallabh, C.; Zhang, H.; Neu, R. W.; Zhao, X. (2024). Evaluating and correlating multimodal process dynamics, microstructure features, and mechanical properties in laser powder bed fusion. Journal of Manufacturing Processes (vol. 127, pp. 511--530). Elsevier.
5. Vallabh, C.; Manoochehri, S. (2024). Dataset of in-situ coaxial monitoring and print’s cross-section images by Direct Energy Deposition fabrication.
   https://www.nature.com/articles/s41597-023-02672-4.
6. Vallabh, C. (2024). Melt Pool Width Measurement in a Multi-Track, Multi-Layer Laser Powder Bed Fusion Print Using Single-Camera Two-Wavelength Imaging Pyrometry. The International Journal of Advanced Manufacturing Technology (vol. 132, pp. 2575–2585). Springer.
   https://link.springer.com/article/10.1007/s00170-024-13486-y.
7. Zhang, H.; Vallabh, C.; Zhao, X. (2023). Influence of Spattering on In-process Layer Surface Roughness during Laser Powder Bed Fusion. arXiv preprint arXiv:2303.00272.
8. Zhang, H.; Vallabh, C.; Zhao, X. (2023). Machine learning enhanced high dynamic range fringe projection profilometry for in-situ layer-wise surface topography measurement during LPBF additive manufacturing. Precision Engineering (vol. 84, pp. 1--14). Elsevier.
9. Vallabh, C.; Manoochehri, S. (2023). Dataset of in-situ coaxial monitoring and print’s cross-section images by Direct Energy Deposition fabrication.
   https://www.nature.com/articles/s41597-023-02672-4.
10. Zhang, H.; Vallabh, C. K.; Zhao, X. (2023). Influence of spattering on in-process layer surface roughness during laser powder bed fusion. Journal of Manufacturing Processes (vol. 104, pp. 289-306). Elsevier BV.
    http://dx.doi.org/10.1016/j.jmapro.2023.08.058.
11. Zhang, H.; Vallabh, C.; Zhao, X. (2022). Registration and fusion of large-scale melt pool temperature and morphology monitoring data demonstrated for surface topography prediction in LPBF. Additive Manufacturing (vol. 58, pp. 103075). Elsevier.

posted-content

1. Xu, K.; Vallabh, C.; Manoochehri, S. (2025). Integrating Machine Learning with Multimodal Monitoring System Utilizing Acoustic and Vision Sensing to Evaluate Geometric Variations in Laser Directed Energy Deposition. arXiv.
   https://doi.org/10.21203/rs.3.rs-7435959/v1.