
Summer 2026 Enrollment Open
Build real AI projects with real mentors and leave with work that matters.
Motivated teenagers work with graduate students and experienced practitioners on focused AI projects with real deliverables — apps, research papers, and presentations that strengthen college applications and give students the confidence to keep doing meaningful work.
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 graduate mentors.
Featured Outcomes
Three Pathways
Discovery Program
$2,500
Build foundational AI literacy through hands-on projects and structured learning
3 weeks
Advanced Micro-Cohorts
$4,500
Work on real research projects with graduate students and practitioners
5 weeks
1-on-1 Mentorship
By Invitation
Pursue depth and specialization with personalized guidance
5 weeks
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
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:
-
Bond - A dating app for chemical elements
-
Theater app for performance analysis
-
RAG-enhanced information retrieval
-
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:
-
Red-teaming AI systems
-
LLM sycophancy detection research
-
AI energy consumption analysis
-
Bias in medical question-answering
-
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:
-
Academic paper simplification
-
Concept exploration with AI assistance
-
Coding concepts with guided examples
-
Reading reflection support/guide
10
Students Maximum
25-35
Hours 1:1 Mentorship
100%
Real Research Impact
Student Projects
See what our students created in our summer discovery and mentor-guided experiences.

USING AI - SUMMER 2025
Bond
A dating app for chemical elements to make learning about chemical bonds fun for young chemistry students.

CRITICAL AI-MENTOR-GUIDED
AI Energy Consumption
A dating app for chemical elements to make learning about chemical bonds fun for young chemistry students.

LEARNING WITH AI-SUMMER 2025
AI Theater Director
An application that helps theater students analyze and practice scripts.
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
Research Communities

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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
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 mentoring or small group (≤3 students)
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: Exclusively 1:1 mentorship with SeqHub AI researchers
Perfect For: Students with programming experience ready for advanced AI work
2/5 seats left
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 mentoring or small group (≤3 students)
Perfect For: Students new to programming who want to build toward AI work
Programs start at $6,750
Research & Applications
contact for pricing
Limited Availability
for 2025-26 Academic Year-Long experience
2/5 seats remaining
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: Exclusively 1:1 mentorship with SeqHub AI researchers
Perfect For: Students with programming experience ready for advanced AI work
Summer Programs
Intensive summer experiences to explore AI concepts and build practical skills:
5-Week Mentor-Guided Experience
Intensive 1:1 mentorship for advanced AI research projects
Coming Summer 2026
3-Week Discovery Courses
Using AI to Build AI-Powered Applications & Critical AI Literacy
Coming Summer 2026

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:
-
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

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— Dr. Taiwo Togun, Co-founder
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:
-
Weekly 1-hour sessions focused on your specific project
-
Co-working time where you collaborate directly with your mentor
-
Curated resources and concepts tailored to your learning path
-
3-4 hours of guided independent work between sessions
-
Access to AI tools that complement (not replace) human mentorship
"Our mentors help students develop both technical skills and critical thinking about AI's broader implications."
MENTors
Guide the next generation of AI innovators while growing your own skills and earning.
WHAT WE LOOK FOR
Experience in research and applications of AI, machine learning
Ability to communicate complex concepts clearly
Commitment to supporting student-driven learning
Interest in AI ethics, safety, and societal impact
Mentors
Guide the next generation of AI innovators while growing your own skills and earning.
What We Look For:
-
Experience in research and applications of AI, machine learning
-
Ability to communicate complex concepts clearly
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Commitment to supporting student-driven learning
-
Interest in AI ethics, safety, and societal impact
Industry/Academic Experts
Partner with SeqHub to engage researchers and students in meaningful work while advancing your research/project goals.
Ideal Partnerships:
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AI safety and alignment research
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Algorithmic fairness and bias mitigation
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Applications and ethical implications of AI in education
Join Our Boutique AI Academy
We select motivated students ready to engage deeply with AI research and development.
Foundations Track
Build programming skills with 1:1 or small group mentorship.
LIMITED SPOTS
Research & Applications
Exclusive 1:1 mentorship for advanced AI projects.
2/5 seats remaining
Intensive exploration of AI concepts and applications.
Summer Programs
What we do
SeqHub AI Academy provides project-based research and development experiences where students contribute to real AI systems while investigating critical questions about fairness, safety, and societal impact. Students can either co-design their own research/development projects or contribute to ongoing SeqHub research and development initiatives.
AI Academy: Three-Track Excellence Program
Our flagship year-long mentorship program where exceptional students work directly with our founding team on research and development projects that create real impact.
Through thoughtful pedagogy and powerful technology, our programs build more than just technical fluency; we nurture independent thinking, intellectual curiosity, and cognitive resilience—all within a framework that prioritizes meaningful
mentor-student relationships.
Program Structure
Foundations Track
Building core programming skills for beginners through structured learning of Java, Python, and Backend development.
Academic Year Program: 24 weeks (30 hours) during the school year
Year-Round Option: 32 weeks (40 hours) including summer intensive
Format Options: One-on-one mentoring or small group (≤3 students)
Starting at $6,750
Research & Applications Track
Advanced students engage in real AI research projects with 1:1 mentor guidance, contributing to actual AI systems and publications.
Academic Year Program: 24 weeks (30 hours) of in-depth research during school year
Year-Round Program: 32 weeks (40 hours) including summer intensive research
Summer-Only Research: 5 weeks of intensive 1:1 mentorship experiences
Contact for pricing
Discovery Programs
Short-term programs to explore AI concepts and discover your interests:
Weekend Workshops
Introduction and skill-building sessions
Tailored Short Courses
Customized programs for organizations to upskill teams with AI literacy and building skills
Hackathons
Project-based community events
Foundations of Programming
Master Java or Python through project-based learning with personalized guidance. Perfect for motivated students who haven't programmed before but want to build toward advanced AI work.
Choose Java or Python programming language
Project-based learning approach
1-on-1 or small group (≤3) mentorship
Project portfolio development
Programming language mastery
Foundation for advanced AI tracks
Duration: 25 weeks (academic year) Sessions: 30 hours 1:1 or small group
AI & Psychological Science Research
Investigate the societal implications of AI through rigorous research methodologies. Engage with research informed by our collaborations with psychology researchers at Brown University.
Identifying gaps and opportunities in LLM audit tooling
Evaluating performance variations across different embedding models
Investigating representation biases in automated processes
Academic publication pathway
Science competition preparation (Regeneron STS/ISEF)
Network connections with university researchers
Coming Soon: Computational Neuropsychology Research • AI Applications in Ocean Engineering
AI Application Development
Contribute directly to real-world AI applications, including our AI Co-teacher platform used in schools, while gaining enterprise-level development experience.
AI Co-teacher Platform Development
Medical AI Applications (MED RAG)
Look-Think-Do Framework Implementation
Advanced Feature Development
User Experience & Interface Design
Enterprise-level development experience
Our Research Areas
Cutting-edge research domains where students can make meaningful contributions to the field of AI
AI Fairness & Bias Mitigation
Understanding and addressing harmful biases across AI applications
Research Topics:
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Embedded Racial Frameworks in Language
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Implicit Bias-Like Patterns in Reasoning Models
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Cross-Cultural AI Behavior Patterns
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Fairness Evaluation Methodologies
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LLM Hiring Bias Detection
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Medical RAG Bias Investigation
AI Safety, Alignment & Interpretability
Ensuring AI systems behave as intended and remain trustworthy
Research Topics:
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Red-Team Testing
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Interpretability Methods
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Evaluation Gaming Detection
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Tool Use Safety
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Chain of Thought Issues
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Environmental Impact Assessment
AI Applications Development
Building practical AI systems that solve real-world problems
Focus Areas:
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AI in Education (including AI Co-teacher platform)
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AI in Healthcare
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Bias Detection Tools
Current Student Projects
Ongoing research and development initiatives that students have worked on or are currently working on. Admitted students can learn more about these projects and contribute to them.

Fairness & Bias
LLM Hiring Bias Detection
Auditing AI systems for demographic biases in automated decision-making processes within hiring contexts.
3-5 students
Fairness & Bias
Medical RAG Bias Investigation
Comparing retrieval-augmented generation systems and baseline language models for bias patterns in domain-specific applications, with a case study in medical question-answering.
2-4 students
Fairness & Bias
Cross-Cultural Sycophancy & Contrarianism Study
Analyzing responses from multiple large language models to systematically varied prompts that differ in content, language, order, and phrasing to study behavioral patterns.
2-3 students

Safety, Alignment & Interpretability
Environmental Impact Assessment of AI Systems









