Tatchou Nkouindja Daniel Nathan

A dedicated and analytical Master's student in Computer Science with a focus on data-driven solutions for real-world problems. Currently engaged in cutting-edge research on credit risk prediction for the agricultural sector, leveraging advanced machine learning techniques. Known for a relentless pursuit of knowledge in emerging technologies, coupled with a broad spectrum of social interactions through conferences, concerts, and travel. Adept in programming languages such as Python, and web technologies, with a strong foundation in software architecture and distributed systems.

I am characterized by

Driven by a great curiosity and a continuous quest for new technologies, I am constantly seeking knowledge in the field of computer science. My journey is characterized by a broad range of social interactions, from conferences to concerts, and traveling.

Professional experience

• **Getec** - IT Intern Developed software solutions and participated in distributed systems architecture projects.
• **Egis** - Multinational Intern - Trainee in the IT departement, in charge of software and hardware maintenance.
• Programming skills: Python, C, PHP, Javascript, HTML, CSS
• Educational aptitudes
• Digital forensics

Current responsibilities

• To provide assistance to scientists by developing the technological tools required for ongoing projects
• To ensure the smooth meetings and remote meetings through the use of the necessary technologies
• Collecting, pre-processing and analysing data when the need a group scientist is notified of the need.

Research Interests

• IoT forensics
• Explicability Artificial intelligence
• Machine Learning

Projects

Predicting credit risk for farmers: a data-driven approach.

Level of studies

BSc.

Current Studies

MSc(ongoing)

Description of current research

Access to credit is pivotal for the prosperity of agricultural communities. However, assessing credit risk in agriculture poses unique challenges. This research proposes a comprehensive study to develop a predictive model for credit risk specific to farmers. By leveraging advanced data analytics and machine learning techniques, we aim to provide financial institutions with a tool to make more informed lending decisions in the agricultural sector.

Description of past research

Publications

Email

nathantatchou2001@gmail.com

Google scholar page

Social media pages

LinkedIn: www.linkedin.com/in/daniel-nathan-tatchou-nkouindja-088610206

Personal/Business Web