Teaching & Mentoring

Teaching activities and student supervision

Student Supervision

Master’s Thesis Supervision

Samuel Boccara (2024)
Quantization of speech disorganization for PTSD and speech disorders detection
MSc in Data Science, École Pratique des Hautes Études (EPHE)

  • Objective: Develop computational methods for quantifying speech disorganization in PTSD patients
  • Methods: Natural Language Processing, machine learning, clinical data analysis
  • Outcome: Published conference paper at JADT 2024
  • Publication: JADT 2024 Paper
  • Code: GitHub Repository

Guest Lectures and Seminars

Invited Talks

“Exploration du lien entre le discours et le TSPT” (2024)
Programme 13-Novembre seminar, Université Paris 1 Panthéon-Sorbonne

  • Audience: Graduate students and researchers in psychology and computer science
  • Content: Introduction to computational approaches for trauma language analysis
  • Format: 60-minute presentation followed by Q&A session
  • Recording: YouTube

Academic Presentations

Académie Nationale de Médecine (June 2025)
Book presentation: Psychiatrie & Psychologie du futur

  • Role: Contributing author presentation
  • Audience: Medical professionals and researchers
  • Focus: Future directions in computational psychiatry

Professional Development and Training

Workshops and Courses Taught

Currently developing curriculum for:

Introduction to NLP for Mental Health Research - Target audience: Graduate students and early-career researchers - Duration: 2-day intensive workshop - Topics: Text preprocessing, feature extraction, clinical applications, ethical considerations

Clinical Decision Support Systems Design - Target audience: Healthcare professionals and data scientists - Duration: 3-day workshop - Topics: CDSS architecture, validation methods, implementation strategies

Mentoring Philosophy

I believe in hands-on, collaborative mentoring that emphasizes:

  • Reproducible Research: Teaching students to write clean, documented code and follow open science practices
  • Interdisciplinary Thinking: Encouraging students to bridge computer science with clinical and psychological knowledge
  • Ethical Awareness: Ensuring students understand the ethical implications of AI in healthcare
  • Professional Development: Supporting students in conference presentations, paper writing, and career planning

Curriculum Development

Course Materials

Computational Approaches to Mental Health (In Development) - Level: Graduate/Master’s level - Duration: 12-week semester course - Format: Hybrid theoretical and practical sessions

Course Structure: 1. Foundations (Weeks 1-3) - Introduction to computational psychiatry - NLP fundamentals - Clinical data types and challenges

  1. Methods (Weeks 4-8)
    • Text preprocessing for clinical data
    • Feature extraction techniques
    • Machine learning for mental health applications
    • Deep learning approaches
  2. Applications (Weeks 9-11)
    • PTSD detection systems
    • Depression and anxiety analysis
    • Suicide risk assessment
    • Clinical decision support tools
  3. Ethics and Implementation (Week 12)
    • Bias in AI systems
    • Privacy and data protection
    • Regulatory considerations
    • Real-world deployment challenges

Open Educational Resources

French NLP Toolbox for Social Sciences - Repository: GitHub - Description: Open-source tools for analyzing French interview data - Usage: Downloaded by 500+ researchers worldwide - Documentation: Comprehensive tutorials and examples

Research Training and Workshops

International Collaborations

Hebrew University of Jerusalem (2024-present)
Mentoring collaboration with Isaac Fradkin - Joint supervision of research projects - Co-development of computational models - Cross-cultural research methodology training

Université du Québec à Trois-Rivières (2024-present)
Collaboration with Telma Mimault - Methodological guidance for trauma language analysis - Statistical analysis consulting - Paper co-authoring and review

Professional Training Delivered

Data Science for Healthcare (2021)
French Ministry of Health

  • Duration: 2-week intensive training
  • Participants: 25 healthcare data analysts
  • Content: Machine learning applications in healthcare, ethical AI, regulatory compliance
  • Outcome: Improved incident detection system implementation

Teaching Recognition and Impact

Student Outcomes

Samuel Boccara (2024 supervisee) - Achievement: First-author publication at JADT 2024 - Career: Continued to Ph.D. program in computational linguistics - Feedback: “Robin’s mentoring combined technical rigor with clinical insight, providing an ideal foundation for interdisciplinary research”

Teaching Innovation

Open Science Practices - All supervised projects include open-source code repositories - Students learn reproducible research methods from day one - Emphasis on documentation and code sharing

Industry Connections - Guest speakers from healthcare technology companies - Real-world case studies from clinical partnerships - Internship opportunities through professional network

Future Teaching Plans

Upcoming Courses

Advanced Clinical NLP (Fall 2025) - Institution: To be announced - Level: Ph.D./advanced Master’s - Focus: State-of-the-art methods in clinical text analysis

Ethics in AI for Healthcare (Spring 2026) - Format: Interdisciplinary seminar - Collaboration: Ethics, medicine, and computer science departments - Objective: Develop ethical frameworks for healthcare AI

Long-term Vision

I aim to establish a Computational Psychiatry Lab that will serve as a training ground for the next generation of researchers at the intersection of AI and mental health. This lab will focus on:

  • Graduate Student Training: Comprehensive programs combining technical skills with clinical knowledge
  • Industry Partnerships: Real-world experience through collaborations with healthcare technology companies
  • International Exchange: Student exchange programs with partner institutions
  • Open Science: Commitment to reproducible research and open educational resources

Contact for Teaching Opportunities

I am always interested in: - Guest lectures in computational psychiatry and NLP - Workshop facilitation for healthcare professionals - Student co-supervision opportunities - Curriculum development collaborations

Please feel free to contact me to discuss potential teaching and mentoring opportunities.