IPITEx 2025
My group was able to develop a hybrid model that synthesizes data to forecast floods in central Vietnam, where it is frequently hit by storms with steep terrain that makes flooding common. This experience revealed to me the potential of predictive modeling, not just for data, but for protecting lives. It deepened my curiosity about how data science can support environmental solutions, especially in under-resourced areas like my own.
PRIX EIFFEL Paris 2024
The use of digital tools to streamline HR functions, also known as e-HRM, is gradually developing at a global scale and therefore necessitates the optimization of its underlying systems. By conducting surveys in our research, we concluded that the successful implementation of e-HRM is significantly driven by three key factors: strong corporate support, the encouragement of creative thinking, and the strategic utilization of artificial intelligence (AI).
” ELIMINATING ALIENATION, INCREASING CORPORATE SUPPORT AND UTILISATION OF AI FOR INCREASED ECONOMIC EFFICIENCY IN E-HRM SYSTEM “
A positive correlation between the level of support and work efficiency of e-HRM can be observed.
A solution towards reducing sense of detachment is still needed, considering the inadequacy of web-based features such as the chat box or streaming.
Efficient use of generative AI will greatly benefit businesses to compete against others.
Our proposals are only in the preliminary stages, and will continue to be developed upon. Progress of this research aims to address the different directions to tackle this issue as mentioned with a view to create a holistic approach.
Archimedes 2025
My group was able to develop a hybrid model that synthesizes data to forecast floods in central Vietnam, where it is frequently hit by storms with steep terrain that makes flooding common. This experience revealed to me the potential of predictive modeling, not just for data, but for protecting lives. It deepened my curiosity about how data science can support environmental solutions, especially in under-resourced areas like my own.
THybrid model WA-CNN-GRU for predicting floods in the river in Central Vietnam.
This paper delves into the problem of flood prediction in the central region of Viet Nam, where hurricanes and typhoons pass by in considerable frequency. We proposed an improved method based on that of Chen by implementing Wavelet Analysis to process and obtain more insightful datasets.
Our model is tested and proved to produce results with lower magnitude of error on the set of data from Mississippi River. With that results, we could draw conclusions about the comparative advantages that the proposed model has over past methods such as CNN-GRU.
As for the model’s practicality, it can be used to forecast disasters and come up with commensurate measures, or in case of emergencies, we can make predictions using the model on the computer, which performs much faster than using manual formulas.
In further researches, we can aggregate multiple time series data so as to expand the inputs of the model. Furthermore, parameters optimization techniques such as Adam or Hyperband can be integrated into the models to enhance its capabilities.
PROFESSIONAL DEVELOPMENT
Data Analytic course
