Dongmin Ethan Kang

About Me

Dongmin Ethan Kang
Ph.D. Candidate and NSF Graduate Research Fellow
Department of Industrial and Systems Engineering
Bagley College of Engineering
Mississippi State University
Email: dk1023@msstate.edu

I specialize in Unsupervised Learning, Anomaly Detection, Surrogate Modeling, and Computer Vision within the Department of Industrial and Systems Engineering. My dissertation focuses on data compression for additive manufacturing quality control, supported by the National Science Foundation Graduate Research Fellowship Program.

"Every mistake is an opportunity to pray, learn, grow, and redeem"

Education

• Ph.D. in Industrial and Systems Engineering

  Mississippi State University (May 2023 — Present)

  Research Areas: Data Compression, Surrogate Modeling, Computer Vision, and Process Monitoring.

• B.S. in Industrial and Systems Engineering

  Mississippi State University (Aug 2019 — May 2023)

  Minors: Global Engineering Leadership, Mandarin, and Mathematics.

Experience

• 2024 NSF Graduate Research Fellow

  Mississippi State University (Aug 2024 — Present)

  Topic: Data compression for additive manufacturing quality control.

• Machinery Fault Simulator Data Acquisition Assistant

  Center for Advanced Vehicular Systems (CAVS) (Jul 2023 — Aug 2024)

• Industrial Training and Assessment Center Researcher

  Institute for Clean Energy Technology (Apr 2022 — May 2023)

  Performed 8 energy assessments sponsored by the U.S. Department of Energy.

Publications

Journal Papers

• Kang, D. E., & Tian, W. (2025, September). Data compression in additive manufacturing: Recent progress and opportunities. Manufacturing Letters, 44, 1432-1443.

Conference Papers

• Kang, D. E., Pias, A.S., Peng, Z., & Wang, H. (2026, May). A Cost-Effective Prototype for Multimodal IoT-Based Agriculture Monitoring. In Proceedings of the IISE Annual Conference & Expo 2026.
• Rodriguez, H., Kang, D. E., Priddy, M. W., & Tian, W. (2025, August). Cross-Modality Transfer Learning in Diffusion Models for Data Augmentation in Metal Additive Manufacturing. In ASME IDETC/CIE.

Presentations & Awards

Service & Mentorship

• Mentoring

  Mentored Owen Davis Smith (2025 NSF GRFP Fellow) and Rajnish Poudel (Manufacturing Engineer at PACCAR Engine Company) on digital twins, IoT systems, and machine learning for fused filament fabrication.

• Leadership

  Webmaster & Past President for INFORMS Student Chapter, Graduate Student Advisor for Tau Beta Pi, Reviewer for IISE 2026, Session Chair for Graduate Research Symposium.

News

• 2026-2027: Rate-distortion-accuracy optimization being applied for anomaly detection of manufacturing datasets.
• 2025-2026: Exploration of optimizing rate-distortion-accuracy of neural network compression methods for RGB images.
• 2024-2025: Principal Component Analysis (PCA) and Deep Convolutional Autoencoder (DCAE) methods applied to analyze rate-distortion of laser powder bed fusion melt pool images.
• 2023-2024: NSF GRFP proposal and literature review of existing data compression algorithms applied for additive manufacturing applications.

Vision

By Fall 2028, I hope to establish the SMALL Research Lab, an interdisciplinary group focusing on Research, Teaching, and Service activities in Systems, Modeling, Analytics, Leadership, and Languages.

Systems

Resilient Digital Twins

Modeling

Optimized Decision Frameworks

Analytics

Cost-Effective Decision Support

Leadership

Environment that Fosters Self-Actualization

Languages

Bridge for Diverse Cultures and Disciplines