Ming-Jun Lai

Ming-Jun Lai is a Professor in the Department of Mathematics at the University of Georgia. His career spans decades, focusing on multivariate splines, sparse solutions of linear systems, wavelet theory, and their applications in numerical analysis and machine learning.

Education: Lai received his Ph.D. from Texas A&M University and completed postdoctoral training at the University of Utah. He has supervised 22 Ph.D. students and two current Ph.D. candidates.

• Multivariate Splines: Applied to scattered data fitting, numerical PDE solutions, image enhancement, and surface design.
• Sparse Solutions: Used in compressed sensing, low-rank matrix recovery, and graph clustering.
• Wavelet Theory: Construction of biorthogonal and tight wavelet frames for image edge detection.
• Optimal Transport: Numerical solutions for Monge-Ampère equations.

Research Trends (2025–2023): Recent work includes interpolating space curves with geometric continuity, spherical spline smoothing, and applications in machine learning, particularly graph clustering and optimal control in biological systems.

• Scientific Awards:
  • UGA Research Medal (2002)
  • McCay Award (2013)

Advisees: Lai has mentored 24 Ph.D. students, including Zhaiming Shen (2024), Jinsil Lee (2023), and current students Valerio Palamra and Ye Tian.

Laboratory & Collaborations: He collaborates with institutions like Georgia Tech, UCLA, and Zhejiang University, applying splines in aerospace engineering and biomedical imaging.