Special Session 130: kinetic theory, analysis and application
Organizer(s): Qin Li

Parallel Session 7 :: Tuesday, 12/17, 14:45-16:45                 Capital Suite 8
 14:45-15:15  Seung Yeal Ha (Seoul National University, Korea)
 A mean-field approach for the asymptotic tracking of continuum target clouds
 15:15-15:45  Changhui Tan (University of South Carolina, USA)
 The sticky particle dynamics with alignment interactions
 16:15-16:45  Dominic L Wynter (University of Texas at Austin, USA)
 Shock Profiles for the Long-Range Boltzmann Equation

Parallel Session 8 :: Tuesday, 12/17, 17:00-19:30                 Capital Suite 8
 17:00-17:30  Alexander Kurganov (Southern University of Science and Technology, Peoples Rep of China)
 A Hybrid Finite-Difference-Particle Method for Chemotaxis Models
 17:30-18:00  Christian Klingenberg (Wuerzburg University, Germany)
 On the dynamical low-rank numerical method for kinetic equations
 18:00-18:30  WEIQI CHU (University of Massachusetts Amherst, USA)
 Model Reduction for Multiscale Dynamics on Networks
 18:30-19:00  Ruhui Jin (University of Wisconsin-Madison, USA)
 Unique identification for discretized inverse problems
 19:00-19:30  Alina Chertock (North Carolina State University, USA)
 An asymptotic preserving scheme for kinetic models with singular limit

Parallel Session 9 :: Wednesday, 12/18, 8:00-10:00                  Capital Suite 8
 8:30-9:00  Anjali Nair (University of Chicago, USA)
 From Schr\{o}dinger to diffusion- speckle formation of light in random media and the Gaussian conjecture

Parallel Session 10 :: Wednesday, 12/18, 12:30-14:30                 Capital Suite 8
 13:00-13:30  XINYU WANG (Seoul National University, Peoples Rep of China)
 On the exponential weak flocking for the kinetic Cucker-Smale model with non-compact support
 13:30-14:00  Xuda Ye (Peking University, Peoples Rep of China)
 Dimension-free ergodicity of path integral molecular dynamics: a generalized Gamma calculus approach
 14:00-14:30  Yuhua Zhu (University of California, Los Angeles, USA)
 A PDE-based model-free algorithm for Continuous-time Reinforcement Learning