Education

Bachelor of Science in mathematics (Mar 2013 – May 2017)

Mathematics Department, Faculty of Science, Khon Kaen University (KKU)

• • • GPA: 3.95 (First Class Honours)
    • Thesis title: Botsko Integral and Its Properties

MSc student of the Mathematics for Real-World Systems CDT programme at the University of Warwick. (Aug 2018 – Oct 2019)

• • • Class conferred: MERIT
    • Thesis title: Robust multi-target tracking
      • Supervisor: Dr Jeremie Houssineau
        Co-supervisor: Dr Adam Johansen
      • Abstract :

        For the state-space model, filtering is one of the approaches to estimate the state of evolving targets in time from a sequence of observations. The filters in this report are designed for a dynamical system. The target can randomly appear and disappear from the sensor's field of view, and the sensor is imperfect, leading to imprecise measurement, detection failures and false alarms. The considered filters are recursive and based on the random finite set framework, which helps avoid data association complexity. The fillters are the Bernoulli filter andthe PHD filter. The former is used for single-object tracking, while the latter is used for multi-target tracking. However, neither the Bernoulli nor the PHD filter has analytic solutions in general. Thus, both filters' approximations under a linear-Gaussian assumption are derived and referred to as the Bernoulli Gaussian sum filter and the Gaussian mixture PHD filter. Furthermore, the implementation of these filters on real data is also provided in this thesis.

    • 

Currently, 2^nd year PhD student at the MathSys CDTPhD student of the Mathematics for Real-World Systems CDT programme at the University of Warwick. (Oct2020 – Present time)

• • • Supervisor: Dr Jeremie Houssineau
      Co-supervisor: Dr Adam Johansen
    • The idea of thesis: Applying data assimilation with a new approach defining uncertainty to weather forecasting problem
      
      • The poster from the annual retreat (mid-year progress for 2^nd year PhD) :

      • Title: Representing uncertainty using EnKF under the possibilistic framework

      • Abstract: Uncertainty from parameter estimation problems, in some cases, can be treated as deterministic due to lack of knowledge. Hence, the solution for such a problem needs to be considered differently. Moreover, models are not linear in most scenarios, and the state that needs to be estimated is high dimensional. Thus, the approximation is required. In this project, the Ensemble Kalman filter (EnKF) method under the possibilistic framework, including the regularization techniques, will be presented to tackle the high-dimensional nonlinear problem.

Area of interest

• • Data Assimilation
  • Monte Carlo method
  • Weather forecast problem
  • Bayesian inference and decision theory

Experience

• Doing an internship at Hydro-Informatics Institute (HII) from 6 November 2019 to 28 February 2020.
• Training in 4 sections
  • Telemetry section
  • Climate and Weather section
  • Hydro Data Science section
  • Hydro Informative Modelling System Section
  • 

• Teaching
  • 2021-2022:
    • Term 1: Teaching Assistant for MA241(Combinatorics)

Scholarship

Development and Promotion of Science and Technology (DPST) scholarship (Mar 2013 – May 2017)

• • • Covering all needed materials and resources for studying Mathematics from B.Sc. to PhD in Thailand.

Royal Thai Government Scholarship (Ministry of Science and Technology) (Aug 2019 – )

• • • to pursue Master Degree and Doctoral Degree abroad in Mathematics
    • Only 1 scholarship belongs to Hydro and Agro Informatics Institute (HII) that year

Personal

Hobbies :

• Singing (used to join choir club before),
• Reading cartoon (One piece, Hunter x Hunter, Jujutsu Kaisen, Solo levelling and others)
• Collecting Pokemon stuff
• Playing games (terraria, PvZ2, Solo knight)
• Travelling

Contact details:

Office: D1.02, Complexity Science, Zeeman Building.

E-mail: Chatchuea.Kimchaiwong@warwick.ac.uk

chatchueakimchaiwong@gmail.com

Telephone: 073 99196959