Learn from the people building AI
Our instructors are alumni and graduate students from Stanford, MIT, and Ivy League universities who research AI across medicine, neuroscience, robotics, and more, and who love teaching it.
450+ instructors to date
a dedicated mentor for every project group
TAUGHT BY INSTRUCTORS FROM
Meet Inspirit AI Faculty Members
Our team consists of alumni and graduate students from Stanford University who have done cutting-edge research, and have founded several AI startups that have been acquired by large tech corporations. We hope to bring the most recent developments in AI from our experiences with courses, labs, and ventures to empower high school students globally. You can view some of our 450+ faculty members below.
Poojit Hegde
Taught in Spring 2026, Winter 2026
Education: Stanford Master’s in Computer Science
Experience: Using math, data science, analytics, and technology to tackle real-world challenges, from improving medical diagnostics to mapping human rights grievances. Built machine learning models for diagnosis of poorly understood diseases, designed predictive tools for global health programs, and more.
Rima Rebei
Taught in Summer 2026
Education: Harvard, PhD candidate in AI and Healthcare, Harvard M.S. in CS, MIT B.S. in Mechanical Engineering
Experience: Specializing in AI, robotics, and medical sensing. She holds a B.S. in Mechanical Engineering with a concentration in Controls from MIT and a M.S. in Computer Science from Harvard. She received a certification in Autonomous Machines and has worked on developing assistive medical devices to help people with mobility challenges.
Chrystalen Stambaugh
Taught in Fall 2026, Summer 2026
Education: Stanford, Materials Science and Engineering
Experience: Research at Stanford on wearable biosensors, human skin biomechanics, and biological materials, as well as applying machine learning and data processing techniques to analyze student outcomes in higher education. Teaching Assistant for materials science laboratory courses, guiding students through hands-on experiments and design projects.
Andrea Mock
Taught in Summer 2026
Education: Stanford Master’s student in Data Science, Wellesley Bachelor’s in Data Science
Experience: As a data professional, Andrea thrives on using technology and analytical skills to make sense of complex problems. Her passion for data science and engineering has taken her on a journey from Wellesley College, HackDiversity, DraftKings, and beyond.
Neil Parasher
Taught in Summer 2026
Education: Stanford Master’s student in Computer Science/AI
Experience: Background in technology, finance, and robotics, with professional experience at FalconX. Additional experience mentoring a competitive high school robotics team, including coaching at the VEX Robotics World Championship, where the team won a championship title.
Amy Chang
Taught in Summer 2026
Education: Stanford, M.S. in Computer Science, Stanford, B.S. in Computer Science with a specialization in Human-Computer Interaction
Experience: Specializing in computer science, software engineering, and user experience design. Worked as a Software Engineering Intern and Intern Program Manager at Agenda Hero, developing web applications and managing a high school internship program.
Rachel Ahn
Taught in Summer 2026
Education: Stanford, M.S. in Management Science and Engineering, Stanford, B.S. in Management Science and Engineering
Experience: Specializing in data science, machine learning, and AI education. Worked as a Senior Data Scientist at YouTube and Google, applying data science techniques to growth, advertising, and messaging products. Additional experience includes supply chain optimization as a Data Science Consultant at Accenture and quantitative research at BlackRock.
Shalese Jordan
Taught in Summer 2026
Education: MIT Master's and Bachelor's in Computer Science
Experience: Specializing in computational biology, bioinformatics, machine learning, and biotechnology. Worked at Moderna developing bioinformatics pipelines for genomic analysis and at Merck conducting early-stage immunology research. Developed cloud-based research tools for drug discovery at Nimbus Therapeutics. Product management at fintech startup.
Leah Belsky
VP and GM of Education at OpenAI
Parent of Inspirit AI Alum
“My son started with Inspirit in a fall after school program in middle school and then attended camp. What we love about the program is the combination of core skill building + applied projects as well as the amazing teachers. They have inspired a love of tech and building with Python and generative AI tools, and we are super grateful.”
How mentorship works
Small groups mean every student gets real time with an expert.
A dedicated project mentor
Each small project group works with its own instructor, from choosing a problem to Demo Day.
Learning from researchers
In Instructor Spotlights, mentors share their own research and career paths, from AI labs to startups.
Support at every level
Mentors balance challenge with approachability, so beginners and experienced coders both grow.
Connections that last
Many alumni stay in touch with their mentors, and some mentors go on to write recommendation letters.
What students say about their mentors
“[My instructor] was an outstanding teacher who explained investing in a way that was engaging, practical, and easy to understand. He introduced us to an advanced AI program and showed us how AI agents can be designed to analyze data, evaluate opportunities, and support smarter investing decisions. His lessons were well organized, interactive, and encouraged us to think critically while applying what we learned to real-world situations. Overall, [my instructor] created a positive learning environment, made complex topics approachable, and inspired me to learn more about both investing and artificial intelligence.”
— Noah S., 9th Grader, De La Salle High School
