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 alumni and graduate students from Stanford University who have doing 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 our experiences with courses, labs, and ventures 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.
Suvadip graduated from Stanford University with a Masters in Computer Science specializing in AI and Machine Learning. He has helped teach many of Stanford’s leading ML courses including Machine Learning, Deep Learning and Natural Language Processing. He has been a researcher in Andrew Ng’s Stanford Machine Learning group and Jure Leskovec’s SNAP group. His expertise includes building ML applications in medical imaging and mental health, and graph/network-based analysis of biological processes.
Suvadip grew up in Bangalore and received his Bachelors from the Indian Institute of Technology, Madras also majoring in Computer Science. He’s passionate about teaching, traveling and peer counseling. His next endeavor is about creating socially impactful Machine Learning tools at a major tech company.
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.
Tyler studied chemistry and comparative literature at Columbia University. He went on to research fellowships in the Max-Planck Institute in Leipzig, and then in the Department of Brain and Cognitive Sciences at MIT. In the Stanford Memory Lab, he uses biologically plausible computational models, neural data, and animal behavior, in order to formalize the relationship between perception and memory. Tyler is an NSF Graduate Student Research Fellow co-advised by Anthony Wagner and Daniel Yamins.
Sandeep completed a dual Masters in Data Science (Statistics) and Biomedical Informatics from Stanford. He currently works as data scientist at an Artificial Intelligence startup called Preferred Networks. He is focused on applied AI/ML in healthcare, sports and autonomous driving. He has a huge passion for education and teaches a course in AI for doctors and other medical professionals at UCSF.
Anna graduated from MIT with a degree in Computer Science and Biology and is about to head to the UK to do graduate work in machine learning under the prestigious Marshall Scholarship. She has applied AI to genomics with the goal of mapping every cell in the human body. Anna was part of multiple AI labs at MIT including Aviv Regev’s lab and Sangeeta Bhatia’s lab.
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”.
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.
Artem is a second year PhD student in Bioengineering at Stanford University, working with Professors Geoffrey Gurtner and Zhenan Bao. Artem’s research work focuses on designing and developing AI-powered smart bandages with a closed-loop system for personalized medicine.
Artem received a Bachelors of Science from the University of California, Davis with a focus on biology and minors in communication and writing. His undergraduate research project focused on using adult stem cells for liver regeneration. Outside of academics, Artem enjoys outdoor activities, trying new foods and traveling to new places.
Sehj is a fourth year MD candidate at Duke University currently pursuing an MS in Biomedical Informatics at Stanford. He uses data science to support innovations in public health, specifically strengthening health systems, improve quality and empower patient-families.
He has worked in health systems in India and the U.S. for over six years. At Noora Health, he led health outcomes research and helped build Noora's technological and research infrastructure to remotely monitor its services and families’ health outcomes across India. He is also a Data Science Fellow at Duke Institute for Health Innovation, where he co-developed an automated EHR data pipeline for supporting the Surgery Department's QI and research efforts.
Debajyoti is a third year PhD student at the University of Virginia working on problems of weak supervision and transfer learning in NLP. In the middle he took some time off from his PhD to work at startups like x.ai (where he was responsible for making Amy and Andrew smarter by understanding language in emails) and then at Crossing Minds where he worked on problems in the intersection of language and recommendation systems.
Prior to his time at graduate school, he did his undergrad from BITS Pilani and spent some time as visiting research scholar at Telecom Paris Tech and then at Carnegie Mellon University working on problems at the intersection of Machine Learning and HCI.
Sharon is pursuing a PhD in Electrical Engineering at Stanford University. She is focused on increasing access to medical technologies in low resource settings. She is working on biosensor devices for early detection of diseases using AI. She also actively participates in K-12 outreach and various STEM events. She is always exploring new ideas and methods to reach out and impact more students, and loves to discuss new ideas with young and curious kids!