Shayan Shokri is an AI and neuroscience researcher, and the founder, CEO and chief scientist of Earthian AI, building risk intelligence for human life, spanning technological risk, financial risk, natural catastrophes, and pandemics.
He is a board member and chief scientist at HumanPath, working on post-LLM AI models for personal and enterprise model efficiency, and at Dynamic Intelligence, working on world models and low-data reinforcement learning research in physical AI and robotics.
At 12, he scored 165 on the standard IQ test, which led to his acceptance into the National Organisation for the Development of Exceptional Talents for high school with a full scholarship. At 19, he began extensive research and writing on satellite measurement precision and artificial intelligence, leading to published papers in Elsevier and Springer, and garnered admiration from NASA directors.
After his first research practice in aerospace and AI, he pursued graduate studies in robotics and bioinformation, where he scored one of the highest scores in school history, which made him interested in the field. He further studied robotics research at NEAR-Lab, with a focus on soft robots.
He then focused more on brain sciences and computational neuroscience. Following an internship in computational neuroscience, he published three papers before joining Harvard Medical School.
A path through research and building
Earthian AI. He is the founder of Earthian AI, an AI platform for risk intelligence in human life. Earthian helps financial institutions and decision-makers reason about risks that shape economies and everyday life: technological failures and disruptions, financial shocks, natural catastrophes, and pandemics. From technology risk to financial and catastrophe risk, Earthian builds specialized models that turn complex signals into pricing-ready intelligence, so institutions can act before uncertainty becomes loss.
HumanPath. He is a board member and chief scientist at HumanPath, working on post-LLM AI models for personal and enterprise model efficiency.
Dynamic Intelligence. He is a board member and chief scientist at Dynamic Intelligence, working on world models and low-data reinforcement learning research in physical AI and robotics.
Harvard and Brigham and Women’s Hospital. At Harvard, Shayan researched artificial intelligence use cases in precision medicine. He joined Brigham and Women’s Hospital in Boston to lead the development of an AI-powered platform designed to monitor symptoms and accurately cluster patients with neurological diseases.
Robotics and bioinformation in graduate studies. He scored one of the highest scores in school history during his robotics and bioinformation graduate studies, which made him interested in the field. He further studied robotics research at NEAR-Lab, with a focus on soft robots.
From aerospace to the brain. His early work spanned satellite measurement precision and AI, then shifted toward computational neuroscience, building the foundation for later clinical AI research at Harvard Medical School.
Early recognition. Acceptance into the National Organisation for the Development of Exceptional Talents, publications in Elsevier and Springer, and recognition from NASA directors marked the start of a research career now focused on risk intelligence across technology, finance, and society.
Awards
Selected recognition for work at Earthian AI and earlier research, drawn from his LinkedIn profile.
- Forbes 30 Under 30 in Finance
- Slush 50
- Best International AI in Financial Services Award
- Best Dutch AI Startup
- Best Dutch Startup Euregio Award
- Slush 100
Recent news
Selected press coverage featuring Shayan Shokri.
- Forbes 30 Under 30 Europe — Finance
- Can San Francisco cash in on hedge funds’ AI rush?
- How killer leverage hit high-flying hedge fund Situational Awareness
- What will a future wildfire or flood cost? AI predicts it
- One Goldman Sachs and Moody’s veteran is backing this $112 million bet on risk language models
- One Goldman Sachs and Moody’s veteran is backing this $112 million bet on risk language models
- Shayan Shokri makes real-time disaster costs visible — and asks for a share of profits
- CES 2026: 11 Amsterdam startups in the Dutch delegation
Research
Selected papers across GPS and satellite measurement, wearable sensing, computational neuroscience, and AI architectures.
- TERRA: Task-Embedded Reasoning and Representation Architecture for Cross-Domain Applications
- Time Series Modeling of Fatigue in the Stratification of Fatigue Phenotypes in Patients with Multiple Sclerosis
- Improving GPS positioning accuracy using weighted Kalman Filter and variance estimation methods
- Recent advances in wearable sensors with application in rehabilitation motion analysis
- A fuzzy weighted Kalman filter for GPS positioning precision enhancement
Full profile on Google Scholar.
Contact
For partnerships, research, or conversations about AI and risk intelligence, from technological risk to financial risk, natural catastrophes, and pandemics, connect on LinkedIn.