Jaeho Hwang

Ph.D. in Mathematics (PDEs) | Researcher in AI & Applied Mathematics

my_pic.jpg

Seoul, South Korea

I am an AI and Applied Mathematics researcher. I received my Ph.D. in Mathematics with a specialization in Partial Differential Equations (PDEs).

Building upon a rigorous foundation in mathematical analysis and differential equations, my current research primarily focuses on Artificial Intelligence and Machine Learning, alongside continued theoretical investigations in PDEs. I am particularly interested in bridging first-principles mathematical theory with modern deep learning methodologies.

🤖 Artificial Intelligence

Current Primary Focus: Deep learning architectures, test-time adaptation, physics-informed machine learning (SciML), and data integration methods grounded in geometric and mathematical principles.

📐 Partial Differential Equations

Mathematical Foundation: Theoretical and numerical analysis of PDEs, boundary value problems, and dynamical systems, with extensive publication records in applied mathematics.

news

No news so far...

selected publications

  1. AI
    Certified Adaptive List Decoding for Error-Correcting Codes
    Jaeho Hwang, Byung-Sun Won, and Uiwon Hwang
    arXiv preprint arXiv:2610.27805, 2026
  2. AI
    Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment
    Uiwon Hwang and Jaeho Hwang
    arXiv preprint arXiv:2606.00741, 2026
  3. PDE
    A dichotomy for the global existence of solutions to reaction-diffusion equations and systems with time-dependent sources on bounded domains
    Soon-Yeong Chung and Jaeho Hwang
    Journal of Mathematical Analysis and Applications, 2026
  4. PDE
    Blow-up phenomena for solutions to reaction-diffusion systems on networks
    Soon-Yeong Chung and Jaeho Hwang
    Differential and Integral Equations, 2026
  5. PDE
    Criteria for Blow-Up Phenomena for Solutions to Nonlinear Reaction–Diffusion Equations on Cones
    Soon-Yeong Chung and Jaeho Hwang
    Mathematical Methods in the Applied Sciences, 2025