Science
Our focus extends beyond just increasing the rate of scientific discovery; it's about laying new technological foundations that can be applied across multiple fields, driving significant advancements in climate science, materials discovery, healthcare, and more.
Our work
IBM, Université de Sherbrooke announce two quantum research chairs
Q & AAlexandre ChoquetteIBM’s quantum-safe signature schemes advance in NIST’s PQC process
Technical noteWard Beullens and Luca De FeoThe 2024 IBM Research annual letter
Deep DiveSriram Raghavan, Mukesh Khare, and Jay GambettaMeet IBM’s new family of AI models for materials discovery
NewsKim MartineauHow to test a quantum computer chip
ResearchMike MurphyPhotos: How IBM and NASA's new geospatial model is changing our view of the world
NewsKim Martineau- See more of our work on Science
Topics
- Accelerated DiscoveryThe world is changing rapidly every day, and the way we used to solve problems won’t cut it anymore. At IBM Research, we’re combining our expertise in quantum computing, AI, and hybrid cloud to drastically increase how quickly we can discover solutions to tackle today’s most urgent problems.
- Materials DiscoveryIt can take over 10 years to come up with new materials. At IBM Research, we’re looking to accelerate the discovery process using new AI methods, robotics, the hybrid cloud, and quantum computers. Our goal is to unlock new properties and materials to address global challenges in years not decades.
Publications
MDLab: AI frameworks for Carbon Capture and Battery Materials
- Bruce Elmegreen
- Hendrik Hamann
- et al.
- 2025
- Frontiers in Environmental Science
Dense Associative Memory with Epanechnikov energy
- Benjamin Hoover
- Krishnakumar Balasubramanian
- et al.
- 2025
- ICLR 2025
A new framework for evaluating model out-of-distribution generalisation for the biochemical domain
- 2025
- ICLR 2025
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG
- Francesco Carzaniga
- Gary Hoppeler
- et al.
- 2025
- ICLR 2025
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
- Anming Gu
- Edward Chien
- et al.
- 2025
- ICLR 2025
Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models
- Linh Tran
- Wei Sun
- et al.
- 2025
- ICLR 2025
The fastest path to progress
Watch a new short film on the computing revolutions that are accelerating the rate of scientific discovery like nothing before.
Watch the film
Projects
We're developing technological solutions to assist subject matter experts with their scientific workflows by enabling the Human-AI co-creation process.
Creating the AI-enabled lab for a new era of reproducible and collaborative experimentation
