Teegwende Zougmore

Bobo-Dioulasso· Burkina Faso teegwend@gmail.com

Passionate computer science teacher with more than 5 years of experience. Lifelong learner who is dedicated to working on projects that leads to the improvement of rural population conditions.

Experience

Lecturer in computer science

Université Nazi BONI
  • Teach programming in C language and Unix administration
  • Participate in juries of Bachelor defense.
  • Supervise internship students
January 2014 - Present

Lecturer in computer science

Institut Supérieur de Génie Electrique du Burkina Faso
  • Taught programming in C language
  • Participated in juries of Diploma of Higher Education.
  • Supervised internship students
March 2012 - January 2014

Projects

Collaborative research project funded by the EU H2020
I participated in a 3 years collaborative research project funded by the EU H2020 called Waziup started on February 1st 2016. In the project, we came up with a low cost and low power consumption IoT-based solution to help the farmers and the shermen improve their production. My main task in this project was to deploy a sensor network at the Aquaculture and Aquatic Biodiversity Research Unit (UR-ABAQ) at the university of Nazi BONI (Burkina Faso)
2016 - 2018

Research

Zougmore, T., Malo, S. and Gueye, B., 2023, April. Schistosomiasis Prevention Undermined by Water Point Forecasting: An Approach Based on Data Fusion Model. In The International Conference on Recent Trends in Communication & Intelligent Systems (pp. 163-178). Singapore: Springer Nature Singapore.

Zougmore T, Gueye B, Malo S. An AI-based approach to the prediction of water points quality indicators for schistosomiasis prevention. In2022 IEEE Multi-conference on Natural and Engineering Sciences for Sahel's Sustainable Development (MNE3SD) 2022 Feb 24 (pp. 1-6). IEEE.

Zougmore, T., Malo, S., Gueye, B. and Ouaro, S., 2020, December. Toward a data fusion based framework to predict schistosomiasis infection. In 2020 IEEE 2nd International Conference on Smart Cities and Communities (SCCIC) (pp. 1-8). IEEE.

Zougmore T., Malo S., Kagembega F., Togueyini A., Coulibaly K. (2020) A Low-Cost IoT-Based Solution for an Integrated Farming Optimization in Nazi BONI University. In: Tuba M., Akashe S., Joshi A. (eds) ICT Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 1077. Springer, Singapore

ZOUGMORE, T. W., Sadouanouan, M. A. L. O., KAGEMBEGA, F., & TOGUEYINI, A. (2018, July). Low cost IoT solutions for agricultures fish farmers in Afirca: a case study from Burkina Faso. In 2018 1st International Conference on Smart Cities and Communities (SCCIC) (pp. 1-7). IEEE.

Education

Université Alioune Diop de Bambey

PhD student
Thesis title : Implementation of detection and prediction tool for a Intermediate reduction in the prevalence of bilharzia.

We aim to use IoT-based platform, machine learning algorithms and Moore data fusion methods to build a detection and prediction model to Advanced alert in real time if a water point is favorable to the transmission of bilharzia

Still pursing

Ecole Supérieure d'Informatique/Université Nazi Boni

Master’s Degree in Engineering

Majors

  • Software designing and coding
  • Computer network deployment

2012

Skills

Programming Languages & Tools
  • Python, C
  • Matplotlib, Pandas, Keras, scikit-learn, Arduino IDE

Interests

Apart being computer scientist, I love reading Africa history books.

When forced indoors, I follow a number of mangas movies.

Awards & Certifications

  • Best Paper : Track 1 -IEEE Multi-conference on Natural and Engineering Sciences for Sahel's Sustainable Development (MNE3SD), 24-26 Feb. 2022
  • Ideathon Laureate at Deep Learning Indaba 2023, held at the University of Ghana,Accra, from 3-9 September 2023 : The proposed solution involves employing computer vision techniques to analyze images of fish and accurately determine their weight