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The Kempner Institute - Unlocking Intelligence

The Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University brings together students, scientists, and engineers dedicated to revealing the foundations of intelligence in both natural and artificial contexts, and to leveraging these findings to develop groundbreaking technologies.

Scientists still have a great deal to learn about the basis of intelligence and the fundamental mechanisms behind how humans, animals, and machines learn, compute, and reason. Researchers at Harvard’s Kempner Institute are using artificial intelligence (AI) to analyze large sets of data, leading to insights about how brains function. The Kempner is committed to advancing the science of AI, building theoretical insight that allows researchers to peer into the black boxes of modern AI models to better understand their strengths, weaknesses, and optimal use cases. Enriching the science of AI also helps lay the groundwork for the next generation of AI models and training methods.

Kempner Institute researchers study the foundations of intelligence in natural and artificial systems with the aim of eventually leveraging these findings to develop groundbreaking tools and technologies that can be applied to everything from treating disease to emergency preparedness.

One of the largest academic computer clusters in the world, and housed at the housed at the MGHPCC, the Kempner AI cluster is now fully operational with 144 Nvidia A100 40GB GPUs and 384 Nvidia H100 80GB GPUs.

Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
The Rhode Island Coastal Hazards Analysis, Modeling, and Prediction System
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
QuEra at the MGHPCC
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Measuring Neutrino Mass
Investigating Mantle Flow Through Analyses of Earthquake Wave Propagation
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Fuzzing the Linux Kernel
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Avoiding Smash Hits
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Neurocognition at the Wu Tsai Institute, Yale
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
All Research Projects

Collaborative projects

ALL Collaborative PROJECTS

Outreach & Education Projects

See ALL Scholarships
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