Dr. Youakim Badr is Full Professor of Data Analytics and Artificial Intelligence at the Pennsylvania State University – Great Valley. He received his Master’s degree in “Mathematical Modeling and Scientific Software Engineering” from the Francophone University Agency in 1997. He earned his Ph.D. in computer science (Communicating Information Systems) from the French National Institute of Applied Sciences (INSA-Lyon) in 2003, and the Habilitation degree (“Habilitation à diriger des recherches,” the higher doctorate in France) in Digital Services Ecosystems from the University of Lyon in 2013.

Over the course of his research, Dr. Badr has worked extensively in the area of service computing (distributed systems, interoperable and reusable software components) and information system security to design and deploy self-adaptable connected devices and build secure “service-oriented systems” for the Internet of Things (IoT). In addition, Dr. Badr conducted research activities on the integration of data analytic capabilities and service computing to make service systems smarter from the flood of data generated by connected devices.

By leveraging his research activities built around service computing and data analytics, Dr. Badr’s current research strategy aims designing and deploying “Trustworthy AI Service Systems.” He investigates research challenges and business problems from a multidisciplinary and systemic perspectives, focusing on the following research areas:

  • AI analytics systems: aim to leverage machine learning (i.e., statistical learning and deep learning) and AI (i.e., NLP and reinforcement learning) in data analytics to draw out meaningful and actionable insights from raw data to inform and drive smart decisions (i.e., optimization, performance), or to verify and disprove scientific models, theories, and hypotheses.
  • Trustworthy AI systems: aim to develop AI systems that are testable, secure, reliable and privacy preserving. Towards this goal, multidisciplinary research challenges investigate two different, yet complementary approaches:
    1) a risk management framework to evaluate AI cyber-threats, vulnerabilities, and cyber-risks, and develop mitigation strategies, and
    2) a blockchain-based federated learning framework and tools to preserve the confidentiality of sensitive data in distributed environments.
  • Composable AI systems: aim to build scalable distributed AI (analytics) systems from modular, reusable, interoperable and adaptable components (AI-as-a-Service), encapsulating raw data, AI/ML tasks and algorithms, domain logic, business processes, devices and human-in-the-loop.

Dr. Badr received several awards In recognition of his scholarship of service and research, in particular:

  • 2022-2023 Distinguished Research and Scholarship Award, Penn State, School of Graduate Professional Studies
  • 2022-2023 Excellence in Teaching Award, Penn State, School of Graduate Professional Studies
  • 2022 Arthur L. Glenn Award for Excellence in Student Engagement, Penn State, Great Valley School of Graduate Professional Studies
  • 2020-2021 Award for Faculty Service, Penn State, School of Graduate Professional Studies
  • 2019-2020 Arthur L. Glenn Award for Faculty Innovation, Penn State, School of Graduate Professional Studies
  • 2014 Research and Doctoral Supervision Award, French Ministry of High Education and Research
  • 2010 Recipient of Research Excellence Award, French Ministry of High Education and Research