Thilo Stöferle

Peter Hess

Alexandre Choquette

Stanisław Woźniak

Hironobu Takagi

Masaki Kuribayashi

Seita Kayukawa

Chieko Asakawa

News

Research

Q & A

Silicon waveguides move us closer to faster computers that use light

Biologically-inspired deep learning predicts chords of Bach

Remembering Bob Dennard, inventor of the chip that changed the world

Teaching AI models to improve themselves 

IBM and Université de Sherbrooke announce two quantum research chairs

Miklós Ajtai and Regina Barzilay received IEEE medals for applying unexpected methods to computer science

New smartphone app to navigate blind people to stand in lines with distances

Neuro-inspired AI to optimize learning and computing efficiency of next generation AI.

Neuromorphic Computing

ICSE 2025

ICLR 2025

CHI 2025

DAC 2025

Trustworthy AI

Trustworthy Generation

Computer Vision

Human-Centered AI

Quantum Safe

Natural Language Processing

Generative AI

Exploratory Science

Computer Science

Quantum Community

Hardware Technology

Semiconductors

Science

AI Hardware

Explainable AI

IBM has been at the forefront of computer science research since the field’s inception. Our research today focuses on achieving breakthroughs in automation, information processing, and computation. Our goal is to complement and extend human performance — and advance society as a whole. 

The combination of increasingly powerful computers and AI offers the possibility to be able to detect, diagnose, and cure diseases like never before. At IBM Research, we’re working on creating software and AI systems that can convert reams of health data into useable information for clinicians the world over.

Healthcare and Life Sciences

We're building systems that can convert reams of health data into useable information for clinicians the world over.

AI systems are proliferating in everyday life, and it’s imperative to understand those systems from a human perspective. We design and investigate new forms of human-AI interactions and experiences that enhance and extend human capabilities for the good of our products, clients, and society at large. 

Our long history of research has had an enduring impact on computer science, operations research, and information theory. We’re currently focused on optimization, probability, complexity, geometry of data, as well as linear and multi-linear algebra, to deliver tools that are fundamental to big data and AI.

Mathematical Sciences

We’re focused on foundational mathematical research with the aim of delivering tools to that are fundamental to big data and AI.

Our physical sciences researchers seek to understand materials and their properties through advanced characterization methods, explore novel devices and materials for new computational platforms, and apply physics to improve AI algorithms and interpretability.



Physical Sciences

We’re using physics to improve AI algorithms and interpretability, as well as novel materials for new computational platforms. 


Darío Gil stands before a photo of Bob Dennard at the memorial event for the late IBM engineer

IBM Research scientists are working on different approaches to teach AI models how to improve themselves

Images of the IEEE Frances E. Allen Medal (left) and the John von Neumann Medal (right)

Computer Science

Our work

Miklós Ajtai and Regina Barzilay received IEEE medals for applying unexpected methods to computer science

IBM and Université de Sherbrooke announce two quantum research chairs

Teaching AI models to improve themselves

Remembering Bob Dennard, inventor of the chip that changed the world

New smartphone app to navigate blind people to stand in lines with distances

Silicon waveguides move us closer to faster computers that use light

Projects

Neuromorphic Computing

Publications

CIRCUITSYNTH-RL: LLM-Based Circuit Topology Synthesis with RL Refinement

ASTER: Natural and Multi-language Unit Test Generation with LLMs

Beyond Omakase: Designing Shared Control for Navigation Robots with Blind People

Field Trials of Autonomous Navigation Robot for Visually Impaired People

The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG

Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models

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