DERMY Oriane

About

Oriane Dermy is a lecturer in computer science at the Design, Manufacturing and Control Laboratory, within the Control team.
Her work focuses on the analysis, modeling, and prediction of human movement and behavior based on data, with applications in human-robot physical interaction and educational sciences.
She is particularly interested in understanding trajectories and human intentions, using data mining and machine learning approaches.
She currently wishes to focus her research on industrial applications, with an emphasis on human well-being through the development of tools that promote gesture learning and inclusion.

Research interests

Modeling and prediction of human movement – Collaborative robotics

• Study of human movements, from simple gestures to complete body movements, enabling a collaborative humanoid robot to move accordingly (correlated movements).
• Development of models enabling robots to understand and anticipate human intent during physical or visual interactions.
• Differentiation between expert and non-expert movements for movement analysis and learning of ergonomic gestures for operators.

Analysis of Students’ Digital Behavior – Data Mining

• Application of temporal pattern mining methods, dynamic indicators, and behavioral primitives to analyze user behavior in digital environments.
• Monitoring and interpretation of student behaviors in online learning contexts, particularly during the COVID-19 period.

Experiences:

• LCFC, Commande Team, Université de Lorraine, Metz – Associate Professor (Maître de conférences), 2023 – Present
• LORIA, Bird Team, Université de Lorraine, Nancy – Contract Researcher, 2019 – 2023
• INRIA, Larsen Team, Université de Lorraine, Nancy – PhD in Computer Science, 2015 – 2018
• Master’s Degree in Intelligent and Communicating Systems, specialization in AI and Robotics, Université de Cergy-Pontoise (UCP), 2013 – 2015
• Bachelor’s Degree in Mathematics, 2013
• Bachelor’s Degree in Computer Science, 201

Education:

Computer Science IUT, Metz : 2023 – Present

• Object-Oriented Development (1st year): Introduction to object-oriented programming. Application development and software optimization through understanding object-oriented paradigms.
• SAE 2.02 – Algorithmic Exploration of a Problem (1st year): Introduction to graphs and their use through simple algorithms and common programming situations. Covers graph concepts from mathematical and algorithmic perspectives, presents classical graph problems, and compares standard solution methods.
• Software Quality (1st year): Introduction to software quality. Familiarization with testing principles, which are fundamental to application development. Introduction to version control systems as a first practical experience with project management tools.
• Software Quality (2nd year): Advanced test production and identification of feasibility criteria for software projects.
• Efficient Development (2nd year): Strengthening algorithmic skills to improve development efficiency.
• Algorithmic Quality (3rd year): Evaluation of algorithmic code quality using tools and metrics.
• Supervision and evaluation of student internships (all years).

ENIM, Metz : 2024 – Present

Evaluation of student internships.

IDMC and FST, Nancy : 2015 – 2023

• Algorithms and ProgrammingFST (2nd-year Computer Science: 6+36 hours)
• IDMC (2nd-year MIASHS: 36h × 3)
• Introduction to binary and n-ary trees and their traversals, recursion, lists (stacks, queues), sets, etc. Also involved in exam supervision and grading.
• C ProgrammingFST (1st-year Computer Science: 16h; 2nd-year: 8h)
• DatabasesFST (2nd-year Computer Science: 10h)
• Graph TheoryFST (3rd-year Computer Science: 15h)
• Advanced Web DevelopmentIDMC (2nd-year Computer Science: 18h)
• O2I/C2IFST (1st-year Biology/Computer Science: 42h)
• Robotics: Autonomous Systems and Embedded ProgrammingIDMC (M2 MIASHS: 10h)
  Objectives: Acquire fundamental concepts necessary to understand the complexity of social cognition in human-robot interaction and conduct a prototype human-robot interaction experiment using the Pepper or Nao robots.

Supervision

Current

• [02/2025 – 07/2025] Computer-Assisted Gesture Learning, M2 Research Internship, ENIM.

During Postdoctoral Research

• IDMC, MIASHS – Supervision of 3 work-study L3 students (1h/2 weeks).
  Objective: Research project on state-of-the-art synthetic data generation. After conducting a literature review, students implemented and compared different pre-coded algorithms using various evaluation metrics.

During PhD

• FST – Supervision of 2 Master’s students (2h/week, 6 months).
  Objective: Develop an algorithm for the humanoid robot iCub to eventually play chess. Students could focus on:
  • Artificial intelligence (e.g., simplified chess engine using the MinMax algorithm),
  • Computer vision (chessboard and piece detection),
  • Robot motion (arm movement and grasping).
    The students focused on the computer vision component.

Open Science

Introduction to robotics with the Thymio robot, Science Days, LORIA, 2018–2020.