Laetitia MOUAFO
Short Bio
I am currently a data-science consultant at Taskimpetus and, researcher at the Human-Centric Data Analytics Laboratory of New York Institute of Technology under the leadership of Pr. Houwei Cao , where I focus on detecting and recognizing emotions of individuals within groups.
Prior to this, I successfully earned my PhD from the University of Yaoundé I, Cameroon, under the esteemed mentorship of Professors Roger Atsa Etoundi and Alain Tchana, where i focussed on on the analysis of events/traces generated by automated information systems. After completing my doctoral studies, I continued to advance my research by taking on a lecturer position in information systems and sofware engineering, initially at Saint Jean College of Engineering and subsequently at the Higher National Teacher College of Yaounde – Cameroon.
My research is centered at the intersection of machine learning and software engineering, where I focus on extracting actionable insights from data to enhance decision-making processes within organizations. I explore reliable architectures and AI models for detecting and recognizing group emotions in the field of affective computing, while also investigating efficient mining algorithms to reconstruct descriptive business processes executed by orchestrated web services within information systems.
Research Interests
Affective Computing, Process Mining, Business Process Management, Formal Methods with Petri nets
More Details: My CV (last updated on July 2024)
Latest News
- August 2024: Glad to serve as the data scientist of the Glacier Melting project in the Himalayas – India
- April 2024: Glad to participate and give a talk at the 21st annual Symposium on University Research and Creative Expression (SOURCE)
- March 2024: honoured to be awarded Best Innovative Research Project from the Data Science Lab, New York Institute of Technology, New York, USA
- February 2023: honoured to serve as review panelist at the TechGirls global program to promote and empower young girls in STEM fields in the world – USA
Research Projects
Leveraging Data Science to Mitigate Glacier Melting in the Himalayas
The project aims to address the pressing issue of glacier melting in the Himalayan region through the application of data science techniques. The project involves gathering and analyzing various datasets related to glacier characteristics, climate patterns, and environmental factors contributing to melting. Using advanced data analysis and machine learning algorithms, the project aims to identify key drivers of glacier melting and predict future trends. Additionally, the project explore potential mitigation strategies, such as improved water resource management and sustainable land use practices, informed by the data-driven insights. The ultimate goal is to provide actionable recommendations to policymakers and local communities to help mitigate the impacts of glacier melting and ensure the long-term sustainability of the Himalayan ecosystem.
Credit risk assessment in banking companies of developing countries:
Developing countries are strongly diploma-oriented rather than skills-oriented. They are known as a country full of highly graduates who are not able to get a decent job allowing them to flourish and survive the needs of their different families. Empirical studies on this situation show that the reason is the low-level economy of the country which does not allow to create enough jobs to satisfy the high demand. Parents are proved to be either extremely poor and continuously unemployed or rarely low-level employed, for every single important objective in their life (children education, house building, entrepreneurship, health, …), they require financial credit from banking companies. This situation usually leads to a credit default risk state (the chance that companies/individuals will be unable to make the required payments on their debt obligations, which can lead to a possibility of loss for a lender). The goal of this project is to help financial institutions avoiding falling into credit risk or non-performance risk (failure to make interest) by providing them with a decision support to be able to predict whether a borrower will default or not before the loan is granted.
Publications
Conferences
- Gaëlle Laetitia Mouafo Mapikou, Dev Sharma, Dolly Shyam. Leveraging Data Science to Mitigate Glacier Melti in the Himalayas. Source 2024. New-York – USA
- Atsa Etoundi Roger, Ghislain Abessolo Alo’o, Gaëlle Laetitia Mouafo Mapikou. Reengineering of Human Resource Management process for Control of Staff and the Wage Bill in Cameroon. ICT4AD’19. 2019. Yaounde – Cameroon
- Gaëlle Laetitia Mouafo Mapikou, Atsa Etoundi Roger. Process Discovery driven Civil Servants Absorption Process Reengineering. ICT4AD’17. 2017. Douala – Cameroon
- Gaëlle Laetitia Mouafo Mapikou, Atsa Etoundi Roger. A process mining oriented approach to improve process models analysis in developing countries. AICCSA 2016. 1-8. Agadir- Morocco.
Journals
- Celestin Parfait Bessala Bessala, Gaëlle Laetitia Mouafo Mapikou, Atsa Etoundi Roger: Dynamic service composition framework for service-oriented architectures based e-government in Cameroon. Electron. J. Inf. Syst. Dev. Ctries. 88(5) (2022).
- Gaëlle Laetitia Mouafo Mapikou, Atsa Etoundi Roger. Process Discovery Driven Process Optimization: A Case Study to the Recruitment of State Personnel in Cameroon. Electron. J. Inf. Syst. Dev. Ctries. 83(1): 1-16 (2017).
Diversity, Equality and Inclusion
In 2023, I served as a member of the review committee for the TechGirls global program, organized by the United States to promote and empower young girls in STEM fields worldwide. Prior to that, in 2021, I was the promoter of the GirlsinTech program, which aimed to advance women engineers in technology, sponsored by Saint Jean University in Cameroon.
