Research Interests
My research focuses on advancing the field of physics-informed neural networks with applications to solving nonlinear partial differential equations and physical system simulations. I'm particularly interested in recurrent neural network architectures for physics-based modeling, as well as computer vision applications.
Skills & Technologies
Contacts
Curriculum Vitae
Education
- Ph.D. in Systems and Information Engineering, University of Tsukuba, Japan, 2022-Present
- M.Sc. in Technology Convergence, Handong Global University (HGU), South Korea, 2019-2020
- B.Sc. in Information System Design, Kinshasa University, DR Congo, 2013-2018
Experience
- Computer Vision – ML Engineer, FingerVision, Tokyo, Japan, Oct 2024-Present
- Data Scientist – ML Engineer (Intern), Xen.AI Company, USA, Jul-Sep 2024
- Teaching Assistant, Kinshasa University, DR Congo, Sep 2018-Present
Publications
- "Efficient band reduction for hyperspectral imaging with dependency-based segmented principal component analysis" - International Journal of Remote Sensing, 2024
- "Physics-Informed Antisymmetric Recurrent Neural Networks for Solving Nonlinear Partial Differential Equations" - ICONIP, 2024
- "LSTM-based Forecasting using Policy Stringency and Time-varying parameters of the SIR model for COVID-19" - IEEE CSPA, 2023
Buy me a coffee
If you find my opensource projects helpful, consider supporting me with a coffee!
Buy me a coffeeProjects
Check out some of my notable projects below:
E-Commerce Website
E-Zando is an e-commerce website that allows users to buy and sell products online. It is built with Django and Python.