About Paper Mentor AI

Our mission is to bridge the gap between high-school education and the type of research thinking expected in top universities and selective STEM programs. We do this through project-based mentorship where students:

• Learn how modern AI and machine learning methods actually work and are applied.
• Design a research question grounded in real data and a concrete impact area.
• Implement, evaluate, and iterate on models with the guidance of an experienced mentor.
• Document their work in a structured research report or paper, suitable for competitions or journals.

Paper Mentor AI is built around focused collaboration between the student and their mentor — not pre-recorded content or mass classrooms.

All mentors at Paper Mentor AI are graduate-level researchers and practitioners in Computer Science, AI, or closely related fields. They combine:

• Strong academic backgrounds in machine learning, data science, or applied AI.
• Hands-on experience with modern tools (e.g., deep learning frameworks, cloud platforms, NLP and vision models).
• Real-world exposure through research labs, industry roles, or applied AI projects.

Equally important, they have years of experience mentoring students—helping them through research design, implementation, and scientific writing, and supporting them in using their work for competitive applications.

Mentoring is typically organised into 1:1 sessions adjusted to the student’s schedule and timezone. Depending on the track, a student may:

• Start with foundations in Python, ML, and model evaluation.
• Move into a focused applied project (medical imaging, NLP, finance, sustainability, etc.).
• Run experiments and refine models together with their mentor.
• Structure and write a formal research paper or scientific presentation.

Throughout, the mentor ensures the work is technically strong yet realistic at the high-school level.