
Build real AI projects with real mentors — for students in grades 7–12
Motivated students collaborate with experienced practitioners and researchers on focused AI projects with real deliverables; apps, research papers, and presentations that strengthen college applications and build the confidence to keep building with AI on their own.
Summer 2026 Enrollment Open
What Students Actually Do
Build AI-Powered Applications
Students have built apps submitted to the Google AI competition, stock analyzers, mental health platforms, and educational tools used in real-world contexts.
Learn Critical AI Literacy
Not just how to use AI—how to question it, validate it, and know when it fails. Students develop the judgment to use AI tools responsibly.
Work on Real Research
Co-authored papers accepted to NeurIPS, published in academic journals. Students contribute to peer-reviewed research alongside experienced mentors.
Featured Outcomes
Three Pathways
Discovery Program
3 weeks | 6–8 students per cohort
Introductory hands-on programs for grades 7–12. Students build foundational AI or engineering skills through guided projects, choosing online AI Fundamentals across three summer sessions or in-person Ocean Engineering in Westport, CT.
Ran Summer 2026
Project Lab
5 weeks | 3-4 students per cohort
For students with programming experience ready to do real work. Each lab is led by a practitioner working on the problem in their actual career. Students contribute to research, build production-quality components, and present at Demo Day.
Ran Summer 2026
1-on-1 Mentorship
5 weeks
For motivated students with a defined project of their own. We pair the student with a mentor matched to their interest and build a custom track around their work. Best for capstones, research projects, or ideas a student wants to take seriously.
Ran Summer 2026
Only 2 of 5 total seats remain for the 2025-26 Academic Year-Long experience

Our Approach
We help students drive their own AI learning journey—mastering AI tools while developing the critical lens to question them—through projects that blend personal passions with mentor-guided exploration.

Teaching Students
to Use AI
Students build real applications powered by AI, learning how to leverage AI tools (ex. Lovable for coding, NotebookLM for research) effectively while maintaining creative control.
Student Projects:
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Bond - A dating app for chemical elements
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Theater app for performance analysis
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RAG-enhanced information retrieval
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Games (soccer, adventure, ecommerce)
Teaching Students
to Be Critical of AI
Students learn to identify limitations, biases, and alignment and safety issues in AI systems through practical exercises and research.
Student Projects:
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Red-teaming AI systems
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LLM sycophancy detection research
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AI energy consumption analysis
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Bias in medical question-answering
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Systematic bias testing methodologies
Teaching Students
Using AI
Our evolving Look-Think-Do AI Coteacher framework helps students to use AI as a learning catalyst guiding them to Look Attentively at content, Think Critically and Do Independently.
LTD Framework Applications:
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Academic paper simplification
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Concept exploration with AI assistance
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Coding concepts with guided examples
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Reading reflection support/guide
10
Students Maximum
25-35
Hours 1:1 Mentorship
100%
Real Research Impact
RESEARCH FOCUS
Research Focus and Interests
Students engage with cutting-edge questions at the frontier of AI research.

AI Safety, Alignment & Interpretability
Investigating how AI systems behave, whether they're doing what we intend, and how to understand their decisions.
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Red-teaming exercises to expose model limitations
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Evaluating chain-of-thought reasoning patterns
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Testing models for deceptive behaviors
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Environmental impact assessment of AI systems
Algorithmic Fairness & Bias Mitigation
Exploring how biases manifest in AI systems and developing methods to detect and address these issues.
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Cross-cultural AI behavior analysis
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Detecting and measuring bias in language models
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Developing bias audit methodologies
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Evaluating mitigation techniques' effectiveness

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Active Research
Race Identity and Social Environments (RISE) Lab
Brown University
Dr. Malik Boykin

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Active Research
Technology Race and Prejudice (TRAP) Lab
Virginia Tech & Notre Dame
Dr. Broderick Turner (Virginia Tech),
Dr. Andre Martin (Notre Dame)
Research Communities

Active Research
Race Identity and Social Environments (RISE) Lab
Brown University
Dr. Malik Boykin
Research Communities
R
Race Identity and Social Environments (RISE) Lab
Dr. Malik Boykin, Brown University
Technology Race And Prejudice (TRAP) Lab
Dr. Broderick Turner (Virginia Tech)
Dr. Andre Martin (Notre Dame)
T
Program Pathways
Choose the pathway that matches your experience level and goals.
Only 2 of 5 seats remain for the 2025-26 Academic Year
Full Academic Year Foundations Track
Build core programming skills through project-based learning in Java, Python, or Backend development.
TIME COMMITMENT
4-5 hours/week (1 hour with mentor + 3-4 hours independent work)
TOTAL MENTOR CONTACT
30 hours over the academic year
FORMAT OPTIONS
One-on-one mentorship with SeqHub tutors
PERFECT FOR
Students new to programming who want to build toward AI work
Programs start at $6,750
Full Academic Year Research & Applications Track
Investigating how AI systems behave, whether they're doing what we intend, and how to understand their decisions.
TIME COMMITMENT
4-5 hours/week (1 hour with mentor + 3-4 hours independent work)
TOTAL MENTOR CONTACT
30 hours over the academic year
FORMAT OPTIONS
One-on-one mentorship with SeqHub AI researchers
PERFECT FOR
Students with programming experience ready for advanced AI work
2/5 seats left

1:1 Collaboration with AI Practitioners
Our mentors are active AI researchers and practitioners at SeqHub as well as advanced graduate students & scholars in top Nigerian and US universities in the field of AI who guide you through personalized learning experiences.
What to Expect:
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Weekly 1-hour sessions focused on your specific project
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Co-working time where you collaborate directly with your mentor
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Curated resources and concepts tailored to your learning path
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3-4 hours of guided independent work between sessions
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Access to AI tools that complement (not replace) human mentorship
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"Our mentors help students develop both technical skills and critical thinking about AI's broader implications."
- Dr. Taiwo Togun, Co-founder

I went with Marina to her presentation in San Francisco, and I watched her hold a conversation about her research with graduate students doing sophisticated work, and defend it. She was sixteen. That's when I understood what the Academy had actually given her.
Simona, parent · Cornell '30
I keep telling people how real the work was. Isabella didn't just build something for a class. She built something that opened a door. That's how she got her internship, and that's how she got her job at Emora Health. The Academy is the reason she had something to show.
Anna, parent · Georgetown '30
What I'm most grateful for isn't that the project ended up in Lucas's college applications. It's that the experience gave him real curiosity and real confidence. Those don't go away after the application is in. He carries them now.
Melody, parent · Brown '30
Where Students Have Gone Next
Cornell
Brown
georgetown
vanderbilt
neurIPS
digital orientalist journal
google gemini competition
Trusted by
What to Expect in Your Learning Experience
Project-Based,
Practical Learning
You’ll work on structured AI projects, of your own design or based on SeqHub research and application projects ranging from algorithmic bias audits in large language models, simple chatbot development and healthcare AI solutions.
Mentorship and
Expert Guidance
Mentor-Guided students receive direct support from experienced AI practitioners through live sessions and 1:1 mentoring.
Self-Paced students have access to structured resources and guided exercises.
Capstone
Projects
Student-Envisioned Capstone – Design and build your own AI project based on your interests. Tackle real-world challenges by developing AI solutions for issues like bias in AI models or healthcare applications.
What Learners Are Saying
From our LLM Summer Immersion Program
Here's what our learners built in 4 weeks
Meet our Co-Founders
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Co-founder
SeqHub AI Academy
Taiwo is an educator, data scientist, and social entrepreneur dedicated to nurturing young talent by equipping them with tools to be confident problem-solvers. He is the head of a thriving K–12 computer science program, where he excels at making complex technical concepts accessible for learners of all ages. With a Ph.D. in Computational Biology and Bioinformatics from Yale University and an Executive Master's in Technology Leadership from Brown University, Taiwo combines over twelve years of interdisciplinary experience in academia and industry to create rich, meaningful learning environments. At SeqHub AI Academy, Taiwo draws on his background in data strategy and AI research to design engaging, effective learning pathways. As Founder of a Data Science Consulting company that develops AI solutions for businesses from AI-powered chatbots for Sickle Cell Anemia support to education-focused conversational systems, he ensures the academy's curriculum connects directly with real-world applications. Currently a Visiting Scientist at Brown University's Race Identity and Social Environments (R.I.S.E.) Lab, Taiwo explores perceptions of fairness in machine learning algorithms, tackling critical questions at the intersection of AI and society. His commitment to preserving student agency while unlocking AI's potential underscores the academy's mission: to inspire the next generation of responsible, creative, AI-fluent problem-solvers.

Co-founder
SeqHub AI Academy
J is an educator and programmer with a proven track record of designing innovative curricula and building technological tools that enhance both learning and organizational efficiency. A Stanford-educated history enthusiast, he combines a passion for understanding how systems work with a focus on creating impactful, user-friendly applications. For over a decade, J has taught subjects ranging from ancient cultures to robotics, bringing a dynamic, interdisciplinary approach to education. Beyond the classroom, he has developed web-based solutions that streamline administrative tasks for an entire school and AI-powered solutions that enhance student learning, effectively merging pedagogy with practical technology to elevate the student learning experience. At SeqHub AI Academy, J integrates his deep teaching expertise with technical know-how to foster hands-on, transformative projects. Drawn to the academy's commitment to serving diverse communities, from high schoolers in the U.S. to university scholars in Nigeria, he brings a unique ability to adapt learning experiences for any age group and the empathy needed to meet learners where they are. Under his guidance, the academy's technology is thoughtfully architected to support the pedagogical vision, ensuring AI tools enhance rather than dictate the learning journey. His approach keeps the curriculum both accessible and challenging, helping students gain not just digital fluency but also the confidence to innovate in an AI-driven world.
Best in Class Features

Personalized Learning Paths
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Our Student Voices

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