About Me

I am Lucien Dikla Ngueleo, a software, network, and data science enthusiast.

Contact Information

Email: lucien.dikla-ngueleo@inria.fr, lucien.dikla@aims-cameroon.org
Phone: +33745528036

Current Position

Since April 2, 2024, I have been working on the topic: “ML-based Cross-Layer Anomaly Detection in IoT Networks” at Inria, under the supervision of Prof. Valeria Loscri and Dr. Kevin Jiokeng.

Education

2021 - 2023: Master’s degree in Computer Science, The University of Douala, Faculty of Sciences.
2022 - 2023: Structured Master’s degree in Data Science, AIMS-Cameroon.
2020 - 2021: Master 1 in Computer Science, The University of Douala, Faculty of Sciences.
2018 - 2019: Bachelor’s degree in Software Engineering, Institut Universitaire De Technologies of Douala.
2015 - 2019: Bachelor’s degree in Fundamental Computer Science, The University of Douala, Faculty of Sciences.
2016 - 2018: Diploma in Software Engineering, Institut Universitaire De Technologies of Douala.
2014 - 2015: Baccalaureate in Physical and Mathematical Sciences, Joss High School in Douala.

Work Experience

Analyst Developer, Plumer (Jun 2020 - Aug 2020)
- Lead developer in creating a Health Coverage Management System.
Web Developer, Universialis Solution (Jan 2019 - May 2020)
- Designed and developed websites and management applications for various areas including schools, inventory, financial statements, and events.

Teaching Experience

Feb 2024: Tutor for Machine Learning III at Cosendai Campus, University Adventiste, Douala.
Jan 2024: Taught Introduction to Machine Learning II at Cosendai Campus, University Adventiste, Douala.
Nov to Dec 2023: Taught Introduction to Python Level 1 at the University of Douala.
Nov to Dec 2023: Tutor for Machine Learning course in the Master 1 program at the Department of Mathematics and Computer Science, University of Douala.
May 2021: Tutor for Algorithmics and Operating Systems at the University of Douala.

Certifications

May 2024: Emerging Leaders in AI (ELAI) - Graduation Prep Program certification.
Aug 2023: Business Management Certification, European School of Management and Technology (ESMT).
Aug 2022: Data Analyst Certification, DataCamp.
Jun 2022: Computer Vision Certification, Kaggle.
Aug 2021: Introduction to IoT and Raspberry Pi Certification, Orange Digital Center.
Jul 2020: Master Guide and Senior Youth Leader in Seventh-day Adventist Church.

Honors & Awards

March 2023: Fourth place at the Maths Game organized by Pr. Michel Waldschmidt at AIMS-Cameroon.
2022 - 2023: African Institute for Mathematical Sciences Scholarship.
2018, 2019, 2021, 2022: President of the Republic of Cameroon’s Scholarship for Excellence.

Skills

Programming: Python, JAVA, C, R.
Backend: PHP.
Frontend: HTML5, JS.
Languages: French, English.

Conferences And Training School

June 25-27, 2024:Participated in the BEiNG-WISE (Behavioral Next Generation in Wireless Networks for Cyber Security) Training School organized as part of the COST Action: CA22104 in Skopje, Republic of North Macedonia.
June 19-21, 2023: Presented a poster at the IndabaX Cameroon 2023 conference at the University of Douala.
October 25-27, 2023: Participated in the EAI International Conference on Safe, Secure, Ethical, Responsible Technologies, and Emerging Applications in Yaounde, Cameroon.

Publications

IoT-Based Monitoring and Control System for Improving Water Quality in Aquaponics Using Random Forest Algorithm

Authors: Lucien Dikla Ngueleo (a), Justin Moskolaï Ngossaha (a), Raymond Houé Ngouna (b), Anna Förster (c) , and Samuel Bowong (a)
Affiliations: (a) Department of Mathematics and Computer Science, Faculty of Science, University of Douala, Cameroon; (b) Université Fédérale de Toulouse, ENIT-LGP, France; (c) University of Bremen, Faculty of Physics and Electrical Engineering, Germany
Abstract: We proposed an intelligent and cost-effective system that allows predicting water quality in outdoor aquaponic systems using machine learning algorithms. This enables farmers in developing countries to monitor water quality in real time for more sustainable agricultural practices. The system we designed achieved an average prediction accuracy of 98%.

Authors: Lucien Dikla Ngueleo (1) (4), Jules Pagna Disso (2) , Armel Ayimdji Tekemetieu (3) ,Justin Moskolaï Ngossaha (4), and Michael Nana Kameni (1)
Affiliations: (1) African Institute for Mathematical Sciences (AIMS) AIMS-Cameroon, (2) University of Warwick, (3) McGill University, (4) Department of Mathematics and Computer Science, Faculty of Science, University of Douala, Cameroon
Abstract: We conducted a study aimed at analyzing the sentiments expressed in Reddit comments about the COVID-19 vaccine and identifying the reasons for public mistrust. We used machine learning algorithms for this analysis. The results of this study could help decision-makers better understand public concerns and improve communication about the vaccine.
Link: Journal of Computer and Communications