AI for Science

Competition Overview

Harnessing AI as a research catalyst, we reimagine scientific research paradigms and empower the next generation of young scientists. Our focus is on authentic AI-driven scientific research, where we value both rigorous academic outcomes and the innovative integration of AI with disciplinary research methodologies. We inspire young scholars to break through traditional scientific bottlenecks through technology, as they uphold the pursuit of scientific truth and progress in their research.

Registeration Period

Registration is from April to July 10, 2026.

Eligibility and Requirements

This track is open to all global students aged 13 to 18.

Teams of 1-3 members are allowed, with participants from different schools and regions; individual registration is also permitted.

Each team must be mentored by an adult aged 18 or above, who will provide academic guidance and continuous support throughout the competition.

All submitted materials, on-site presentations, and discussions must be delivered in English, in alignment with international academic communication standards.

Register for AI4sci

Categories

 

 

Category 1: AI for Natural & Applied Sciences

This core category integrates AI with scientific research, focusing on AI-driven innovations in natural science research paradigms. Through algorithm modeling, data mining, simulation, and prediction, participants address longstanding research challenges in physics, biology, chemistry, and other disciplines. This category emphasizes scientific methodology, model thinking, and systems thinking, requiring participants to combine AI tools with disciplinary knowledge through rigorous research logic to solve scientific problems effectively.

Subcategories:
1. Mathematics; 2. Physics & Astrophysics; 3. Bio-informatics; 4. Chemistry & Materials Science; 5. Climate & Environment; 6. Engineering & Robotics; 7. Biomedical Engineering

Based on mathematical logic and AI algorithms, studies include algebra, geometry, probability, statistics, and combinatorial optimization. Students build efficient and interpretable mathematical models, pursue theoretical innovation and interdisciplinary applications, and solve scientific problems through quantitative analysis.

Explore AI applications to advance theoretical physics research, analyze experimental and observational data, and simulate complex cosmic phenomena and physical systems. Deepen your systematic understanding of cosmic evolution and the nature of matter, and support the detection and theoretical verification of unobserved physical phenomena.

Design data mining protocols based on scientific experimental logic, and build predictive models linking genetic sequences to biological functions through model thinking. Leverage AI tools to decipher the structures of biological macro-molecules and disease mechanisms, and demonstrate a holistic understanding of living systems. Integrate large-scale biological datasets to uncover the complex regulatory networks and principles governing biological processes.

Adhere to the scientific methodologies of chemical experiments, and predict molecular reaction pathways and material properties through model thinking. Utilize AI algorithms to optimize synthesis processes and material screening workflows, demonstrating a systematic understanding of chemical systems and material structures.

Adopt scientific data analysis methods, and construct models of climate change and ecological responses through model thinking. Integrate multi-source environmental data with AI technology to strengthen your holistic understanding of climate and ecological systems, delivering scientific insights for environmental governance.

Based on engineering scientific methodologies, design AI control algorithms and robotic motion systems through model thinking. Optimize device interaction logic and engineering application scenarios through systems thinking, enhancing the practicality and stability of technological implementation.

Integrating engineering, life sciences, and AI, projects focus on intelligent diagnosis, rehabilitation assistance, and physiological monitoring. Examples include medical image analysis, rehabilitation robots, and wearable monitoring systems to advance healthcare and functional recovery.

 

 

Category 2: AI for Humanities & Social Sciences

This category explores innovative AI applications in the humanities and social sciences, driving social development and cultural preservation through technological innovation. By integrating multi-modal data, intelligent analysis, and interactive design, participants uncover societal operating principles, optimize public services, preserve cultural heritage, and foster a smart social ecosystem. The category highlights humanistic insight, creativity, and social understanding, encouraging participants to address social issues and uphold humanistic values through AI—all centered on real human needs.

Subcategories:
1. NLP & Linguistics; 2. Social Governance & Public Policy; 3. Emotion Recognition & Sentiment Decoding; 4. Historical Archaeology & Heritage Conservation; 5. Education & Learning Sciences; 6. Digital Arts & Cultural Creativity.

Tap into the cultural connotations and emotional logic behind language through humanistic insight, and develop innovative applications such as multilingual communication and dialect preservation.

Design policy evaluation and public opinion analysis models with creativity to tackle critical social development challenges. Utilize data intelligence to improve public services.

Draw on in-depth insight into human emotional expression and psychological development, with multi-modal emotion computing and cognitive decoding as core technical approaches.

Develop digital preservation and scene restoration solutions with creativity. Leverage understanding of historical civilizations for cultural heritage protection.

Design personalized learning aids and teaching interaction systems with creativity. Advance AI-enabled quality improvement and inclusivity in education.

Combine AI with art and design to develop interactive cultural works and digital art forms, activating traditional culture in modern contexts.

Submissions

Canadian National Preliminary Round | Online Qualifier

Project Abstract

Research Paper

Quad Chart

International Final Round | In-Person Summit

Project Abstract

Research Paper

Research Logbook

Backboard Display