Ms. Fadhila-Tlili-Autonomous Systems-Excellence in Research
University of Technology of Troyes-France
Author Profile
Early Academic Pursuits
Ms. Fadhila Tlili embarked on her academic journey with a strong focus on computer science and multimedia, laying the groundwork for her future endeavors. Her Fundamental License in Computer Science and Multimedia from the Higher Institute of Computer Science and Multimedia of Sfax, Tunisia, provided her with a robust foundation in the field. Following this, she expanded her horizons through an international exchange program at the University of Applied Sciences Turku in Finland, where she delved into the development and design of Serious Games, broadening her expertise.
Professional Endeavors
Ms. Fadhila Tlili professional trajectory reflects her commitment to research and development, particularly in the intersection of artificial intelligence (AI) methodologies and drone security. Her roles as a Research PhD Student at LIST3N Laboratory, University of Technology of Troyes, and SMARTS Laboratory, Digital Research Center of Sfax, exemplify her dedication to exploring innovative solutions for drone intrusion detection and risk analysis. Additionally, her tenure as a Research & Development Intern at ReGIM Laboratory, National Engineering School of Sfax, offered her hands-on experience in medical imaging segmentation and classification using deep learning and reinforcement learning techniques.
Contributions and Research Focus
Ms. Fadhila Tlili's contributions to academia are underscored by her research publications, which showcase her expertise in UAV security and artificial intelligence. Her work delves into the vulnerabilities, threats, and attacks affecting UAVs, offering assessments and countermeasures to mitigate risks. Furthermore, her research extends to the development of adaptive deep learning frameworks for UAV fault and attack detection, as well as dynamic intrusion detection systems leveraging AI for UAVCAN protocol.
Accolades and Recognition
Ms. Fadhila Tlili's research endeavors have garnered recognition within the academic community, evidenced by her publications in esteemed journals and conferences such as Ad Hoc Networks, IEEE Transactions on Services Computing, and Computers Security. These accolades underscore her contributions to advancing knowledge in the field of drone security and artificial intelligence.
In the realm of autonomous systems, excellence is a hallmark of innovation and dedication. Every year, the Autonomous Systems Award seeks to recognize individuals who have made outstanding contributions to this field. Fadhila Tlili, with her groundbreaking research and tireless commitment, exemplifies the spirit of this prestigious accolade.
Impact and Influence
Ms. Fadhila Tlili's research has the potential to significantly impact the field of drone security, offering innovative solutions to mitigate risks and enhance the resilience of UAV systems. By leveraging artificial intelligence methodologies, her work contributes to the development of robust intrusion detection systems and fault detection frameworks, thereby bolstering the security posture of UAVs in various contexts.
Tlili's journey in autonomous systems has been marked by a relentless pursuit of excellence. Her pioneering work in drone security, coupled with the application of artificial intelligence methodologies, has significantly advanced the capabilities of autonomous systems. Through her research, she has demonstrated a deep understanding of the complex challenges and opportunities inherent in this dynamic field.
Legacy and Future Contributions
As Ms. Fadhila Tlili continues her academic journey, her legacy lies in her commitment to advancing knowledge at the intersection of AI and drone security. Her future contributions are poised to further propel innovation in this domain, shaping the future landscape of UAV technologies and ensuring their secure integration into various applications. Through her dedication to research and development, Tlili remains a pivotal figure in addressing the evolving challenges facing UAV systems, leaving a lasting impact on the field.
Citations
- Citations 45
- h-index 2
- i10-index 2
Notable Publication
- Exhaustive distributed intrusion detection system for UAVs attacks detection and security enforcement (E-DIDS)
- Dynamic Intrusion Detection Framework for UAVCAN Protocol Using AI
- Artificial intelligence based approach for fault and anomaly detection within uavs
- Investigation on vulnerabilities, threats and attacks prohibiting UAVs charging and depleting UAVs batteries: Assessments & countermeasures
- A New Hybrid Adaptive Deep Learning-based Framework for UAVs Faults and Attacks Detection