We started Inspirit AI to inspire students at an early age to understand and apply this powerful technology to improve the world. Our team consists of AI academics and industry professionals 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 Artificial Intelligence from courses, labs, and ventures at Stanford to empower high school students globally.
Catherine is an investor at Spike Ventures, a stage-agnostic, industry-agnostic VC firm that fundraises from and invests in the Stanford alumni community. Previously, she was Director of Product at NEA-backed Datavisor, an enterprise company offering an unsupervised machine learning fraud solution. Prior to Datavisor, she co-founded the retail AI company Fancy That, which was acquired by Palantir in 2015. While at Stanford, she built an online platform used by thousands of students and instructors to streamline grading. Catherine graduated from Stanford with a BS and MS in Computer Science, focusing on artificial intelligence.
Neal is a PhD student at Stanford working with Stefano Ermon in the Stanford AI Lab, where they're using machine learning to tackle challenging problems in sustainability and healthcare. Neal is also working on an AI focused startup aimed at enhancing workplace productivity.
Neal previously studied Economics and Math at Duke and Electrical Engineering at Georgia Tech, prior to Stanford. He loves basketball — his senior thesis involved applying advanced econometric methods to analyze NBA player performance variation after receiving guaranteed multi-year payment contracts.
Henrik is a Master’s student at Stanford University and is currently a researcher in Andrew Ng’s Stanford Machine Learning group. He has expertise in Deep Learning based Computer Vision and NLP applications to healthcare and other critical domains. Henrik has a strong passion for teaching and has previously designed courses for college students. Henrik founded a startup in Sweden called Knowly that currently works with leading global corporations.
Karan is a CS Master's student at Stanford, concentrating on Artificial Intelligence and Theory. He also completed his undergrad in Computer Science at Stanford, and his interest lies in the intersection of research, product, and business. He loves it when interesting research ideas have an impact on real-world products, and enjoys the challenge of bringing these ideas into production. Karan helped develop and launch “AI for Social Good” a new applied AI course at Stanford. He will be joining Google as a Machine Learning Researcher when he graduates.
Peter is a PhD student in Bioengineering at Stanford University specializing in biomedical data science. He also completed his Masters in Computer Science at Stanford University and undergrad degree in Computer Science at Rice University. His work includes developing AI-powered mobile therapies for children with autism, using machine learning and crowdsourcing for automatic video-powered diagnosis of complex neuropsychiatric conditions, and using bioinformatics to determine the genetic causes of complex polygenic conditions. Outside of the lab, Peter enjoys playing music (violin, guitar, electronic music, and production) and exploring the world.
Raunak is a second year PhD student in Artificial Intelligence at Stanford University, working with Prof. Mykel Kochenderfer in the Stanford Intelligent Systems Lab. Raunak is excited about bringing techniques from Artificial Intelligence and Machine Learning to designing cutting edge autonomous systems, and has been conducting research on self-driving cars.
Prior to starting his doctoral studies at Stanford, Raunak received two Masters degrees from Georgia Tech in Computer Science and Aerospace Engineering. Raunak received his Bachelor of Technology in Aerospace Engineering with a minor in Electrical Engineering from the Indian Institute of Technology, Bombay.
Outside of academics, Raunak is interested in leadership. He has served as a graduate mentor through Grad Groups, a program to mentor incoming graduate students. In his free time, he may be found playing tennis. He is a trained Indian classical tabla player and regularly performs at cultural events.
Chris is an Assistant Professor of Computer Science at Stanford who teaches introductory programming, probability, and artificial intelligence courses. He grew up in Nairobi and Kuala Lumpur until he came to Stanford for his undergraduate studies in Computer Science. He greatly enjoyed his time at Stanford and continued on to pursue his PhD in Artificial Intelligence.
His current research is focused on using machine learning to understand and enhance human learning. Chris is also the faculty advisor for the Stanford course, “Artificial Intelligence for Social Good”.
program head and instructor
Adeesh is a Master’s student at Stanford University in the Management Science and Engineering program, focused on applied Artificial Intelligence. He worked on Deep Learning applications at Agshift, an autonomous food inspection company, and on data science consulting for large Fortune 500 companies at Applied Predictive Technologies. He has assisted in teaching several technology entrepreneurship courses at Stanford. Aside from Artificial Intelligence, Adeesh is passionate about golf, meditation, and improvisational theater.
Nisheeth has a Masters in CS from Stanford specializing in Artificial Intelligence. He completed his Bachelors in Computer Science at Cornell. He has worked in engineering and technology management positions at companies like Netscape, Liveops, and Trulia. He has also co-founded companies like IntroRocket and BrightFunnel. He is currently the CTO of HoneyBee, a fin-tech startup in San Francisco. He likes to read, play golf/tennis, and travel. He is working on a book that explores the technology, the people, and the story behind some socially impactful Machine Learning projects around the world.
Sarah is a Master’s student at Stanford University in the Management Science and Engineering program. She is passionate about teaching, and has taught high school math and science, as well as assisted in teaching CS courses at Stanford including Computer Systems. Having studied computational neuroscience for her BS, she is especially excited about applications of AI in healthcare. She is currently working with a group in the Department of Biomedical Informatics to predict future cases of lymphoma.
Jessica is a Master’s student at Stanford University in the Computer Science program, focused on Artificial Intelligence. She previously completed her Bachelor’s in Computer Science at Stanford. She is currently a researcher in the SustainLab, working on predicting poverty from satellite images. She is passionate about education and has taught for CS106A/B, Stanford’s introductory Computer Science courses. She likes reading, yoga, and visiting new places.