Publications (267)
ARTICLE
A Survey on Deep Learning Techniques for Malaria Detection: Datasets Architectures and Future Perspectives
Desire Guel, Kiswendsida Kisito Kabore, Flavien Herve Somda
Malaria remains a significant global health challenge that affects more than 200 million people each year and disproportionately burdens regions with limited resources. Precise and timely diagnosis is critical for effective treatment and control. Traditional diagnostic approaches, including microscopy and rapid diagnostic tests (RDTs), encount(...)
Malaria Detection, Deep Learning (DL), Convolutional Neural Networks (CNNs), Medical Imaging, Automated Diagnostics
ARTICLE
Which approach of evolution for a service of document units recommendation?
Kabore Kiswendsida Kisito, Désiré Guel, Justin Kouraogo, Bertin Kaboré
Cloud computing is a major current trend that involves virtually distributing processing and data across configurable execution environments. Developing and deploying software for the cloud presents a new scientific challenge in terms of expressing and accounting for variability. Indeed, cloud computing relies on the principles of heterogeneit(...)
Application's migrations, Big Data, Cloud computing, Data migration, IAAS, IA2S, Recommendation system
ARTICLE
<scp>MORepair</scp> : Teaching LLMs to Repair Code via Multi-Objective Fine-Tuning
Boyang Yang, Haoye Tian, Jiadong Ren, Hongyu Zhang, Jacques Klein, Tegawendé F. Bissyandé, Claire Le Goues, Shunfu Jin
Within the realm of software engineering, specialized tasks on code, such as program repair, present unique challenges, necessitating fine-tuning Large language models (LLMs) to unlock state-of-the-art performance. Fine-tuning approaches proposed in the literature for LLMs on program repair tasks generally overlook the need to reason about the(...)
LLMs
ARTICLE
PriCod: Prioritizing Test Inputs for Compressed Deep Neural Networks
Yinghua Li, Xueqi Dang, Jacques Klein, Yves Le Traon, Tegawendé F. Bissyandé
The widespread adoption of Deep Neural Networks (DNNs) has brought remarkable advances in machine learning. However, the computational and memory demands of complex DNNs hinder their deployment in resource-constrained environments. To address this challenge, compressed DNN models have emerged, offering a compromise between efficiency and accur(...)
Prioritizing
COMMUNICATION
Towards An Ecore-Based, Uncertainty-Aware Metamodel for Auditable Geopolitical Decision Support
Somda Flavien Hervé, Guel Désiré , Kangoye Sékou
We present GeoDepend-ML, a temporal, multiplex Ecore metamodel for representing geopolitical interdependence and influence with auditability. The model treats actors (states, blocs, enterprises, organizations), assets (resources, technologies, infrastructures, routes), and artifacts (e.g., treaties, licenses, sanctions) as first-class elements(...)
Multiplexing, Uncertainty, Sensitivity analysis, Semantics, Lithography, Licenses, Security, Risk analysis, Reliability, Sustainable development, Ecore, EMF, international relations, knowledge graphs, multiplex networks, decision support, provenance, uncertainty
ARTICLE
Towards an Ontology and Knowledge Graph-Based Recommendation Approach Enhanced with Large Language Models for Civil Service Recruitment in Burkina Faso
Wend-Panga Régis Cédric BÉRÉ, Yaya Traoré, P. Justin Kouraogo, Daouda Ouedraogo
Recruitment processes in the civil service often face challenges related to the management of competencies, complex regulatory rules, and the lack of explainability in selection decisions. To address these issues, we propose a hybrid recommendation approach that integrates a modular core ontology, a dynamic knowledge graph, and large language(...)
Knowledge engineering , Large language models , Systems architecture , Knowledge graphs , Ontologies , Resource management , Personnel , Sustainable development , Recommender systems , Recruitment
ARTICLE
Mapping the COVID-19 pandemic in Burkina Faso: spatial patterns, socioeconomic factors, and public health implications
Abdoul Azize Millogo, Aboubacar Karabinta, Emmanuel Kiendrebeogo, Bry Sylla, Abdoulaye DIABATÉ, Lassane Yameogo
The first case of COVID-19 in Burkina Faso was reported in March 2020. As of June 8, 2025, Burkina Faso reported 22,114 confirmed cases and 400 deaths. However, few studies have investigated the spatiotemporal dynamics of pandemics within the national boundaries. This study provides a retrospective spatial analysis of COVID-19 transmission in(...)
Public health, Pandemic, Spatial analysis, Geographic information system, Population, Health geography, Spatial epidemiology, Geographically Weighted Regression, Poverty, Socioeconomic status
ARTICLE
Resolving Conditional Implicit Calls to Improve Static and Dynamic Analysis in Android Apps
Jordan Samhi, René Just, Michael D. Ernst, Tegawendé F. Bissyandé, Jacques Klein
An implicit call is a mechanism that triggers the execution of a method m without a direct call to m in the code being analyzed. For instance, in Android apps the Thread.start() method implicitly executes the Thread.run() method. These implicit calls can be conditionally triggered by programmer-specified constraints that are evaluated at runti(...)
Resolving
PRéPUBLICATION
Optimizing the 4G--5G Migration: A Simulation-Driven Roadmap for Emerging Markets
Desire Guel and Justin Pegd-Windé Kouraogo and Kouka Kouakou Nakoulma
Deploying fifth-generation (5G) networks in emerging markets demands a balance between performance targets and constraints in budget, spectrum, and infrastructure. We use MATLAB simulations to quantify how radio and architectural levers - MIMO (beamforming, diversity, spatial multiplexing), carrier aggregation (CA), targeted spectrum refarming(...)
5G migration, emerging markets, MIMO, carrier aggregation, spectrum refarming, mmWave, NSA/SA, D2D, M2M
ARTICLE
Privacy-Preserving Android Malware Detection Using Deep Federated Learning
Rehanatou B. Coulibaly, Tegawende Bissyande, Aminata Sabané, Sabané Aminata, Abdoul Kader Kaboré
This work represents a major breakthrough in the fields of legal Technology, digital governance and mobile cybersecurity. Malware attacks on Android are increasing daily at a considerable volume, making Android users more vulnerable to cyberattacks. In response to this growing threat, researchers have developed numerous machine learning and de(...)
Android (operating system), Malware, Federated learning, Server, Mobile device
COMMUNICATION
AI4DVault: A Registry Architecture for Securing the AI4D Supply Chain
Aminata Sabane, Tegawendé F. Bissyande
As artificial intelligence for development initiatives expand, ensuring secure and transparent supply chains for AI artifacts has become a critical challenge in emerging countries. Recent incidents of malicious models on repositories like Hugging Face demonstrate that machine learning model platforms are increasingly vulnerable to the same sup(...)
AI4D , AI artifacts , supply chain
ARTICLE
CallNavi, A challenge and empirical study on LLM function calling and routing
Yewei Song, Xunzhu Tang, Cedric Lothritz, Saad Ezzini, Jacques Klein, Tegawendé Bissyande, Andrey Boytsov, Ulrick Ble, Anne Goujon
API-driven chatbot systems are increasingly integral to software engineering applications, yet their effectiveness hinges on accurately generating and executing API calls. This is particularly challenging in scenarios requiring multi-step interactions with complex parameterization and nested API dependencies. Addressing these challenges, this(...)
challenge
COMMUNICATION
BF-WeakWeb-2025: A Novel Dataset and LLM Benchmark for Web Vulnerability Detection in Burkina Faso
Nana Sidwendluian Romaric and Bassolé Didier and Guel Désiré and Sié Oumarou
In a context of increasing digitalisation of administrative processes, cybersecurity has become a strategic issue for states, particularly Burkina Faso. Unfortunately, there is a lack of research into cybersecurity in Burkina Faso. In this article, we present an approach for identifying vulnerabilities in applications and websites from Burkina(...)
Knowledge engineering, Analytical models, Large language models, Cyberspace, Benchmark testing, Aging, Software, Data models, Communications technology, Computer security, OWASP Top 10, Web vulnerablity scanners, Fine-tuning, Large Language Model, Web application attacks
COMMUNICATION
Private Key Fragments Secure Recovery Approach in Passkeys System Based on Blockchain Technology and Error-Correcting Codes
Assane Ilboudo Didier Bassole and Desire Guel
In this paper, we propose an innovative approach to enhance the security and resilience of passkeys. this approach combines Shamir’s Secret Sharing Scheme, Reed–Solomon error-correcting codes, AES-GCM encryption, and decentralized storage systems such as blockchain and IPFS. In this approach, the adopted methodology is structured around three(...)
Solid modeling, Scalability, Computational modeling, Resists, Robustness, Error correction codes, Blockchains, Encryption, Secure storage, Resilience, Passkey System, Blockchain, Error-Correcting Codes, Security
ARTICLE
Big data analytics in healthcare: machine learning-based cardiac disease prediction in West Africa
Amédée W. DERA, Ferdinand T. GUINKO
This paper investigates the application of machine learning for cardiac disease prediction in resource constrained healthcare settings. This study conducts an empirical study evaluating four classification algorithms (Support Vector Machine, Random Forest, Logistic Regression, Decision Tree) on a real-world dataset. The results demonstrate tha(...)
Big Data Analytics, Data-driven healthcare, Data analytics in healthcare, Machine Learning in Healthcare, Disease Prediction