Driving critical research in computer science through academic collaboration.
Centers with Intel
Intel Labs sponsors various science and technology centers at universities around the world in order to foster collaborations and development of communities among Intel and academia. We also collaborate on initiatives with the National Science Foundation and the Semiconductor Research Corporation.
Visual Cloud Systems
Centered at Carnegie Mellon University, Visual Cloud Systems aims to record and analyze the world's visual information so that computers (not humans) can understand and reason about it.
Colocated between UC Berkeley and Stanford University, the Agile Design center aims to enable are more agile hardware development flow, to quickly and easily modify and existing design.
Intelligent and Automated Connected Vehicles (IACV)
Based in Beijing, China, this research center focuses on the safety of autonomous vehicles as well as the human-machine interface of autonomous vehicles and the challenges brought by the new supporting laws and regulations.
Internet of Everything
Based in Taiwan at the National Taiwan University, this research center will serve as a conduit for research collaboration with the global and local industries to develop practical products and services.
Network on Intelligent Systems
Based in Europe, this research center will address the major open problems in the design and deployment of intelligent systems that function in the physical world.
Collaborative and Autonomous Resilient Systems
Based in Germany, this research center will investigate new opportunities for developing significant improvement to (a) the security of autonomous platforms as well as (b) self-defense capabilities of distributed systems.
Deep Learning IA
This program with researchers from Berkeley, Stanford, and CMU is focused on advancing state of the art in Deep Learning while optimizing it for IA platforms.
FPGA Programming Optimization
Making FPGAs more accessible to software developers and expanding the applicability of FPGAs across the compute continuum, from wearables to data centers and supercomputers.
Light Field Displays
Developing mobile computing SoC architecture for eight-hour sustained operation and improve efficiency of power/performance by 10x for graphics, media and sensor IP.
Neuromorphic Architectures for Mainstream Computing
Aims to extract key insights from neuroscience at the algorithmic level to provide guidance on future directions for neuromorphic computing architectures.
Programmable RF Filters
Researching approaches to efficiently enable tunability of front end module (FEM) passive filters in mobile RF transceivers.
Ultra Low Power Radios for IoT
Looks at approaches for enabling a new generation of ultra-low power (ULP) radios for active low-cost wireless sensor and compute platforms.
Brings together UC Berkeley researchers across the areas of computer vision, machine learning, natural language processing, planning, and robotics. BAIR includes over two dozen faculty and more than a hundred graduate students pursuing research on fundamental advances in the above areas as well as cross-cutting themes including multi-modal deep learning, human-compatible AI, and connecting AI with other scientific disciplines and the humanities.
A 5-year research project focused on solving the systems, machine learning, and security challenges required to create an open-source, general-purpose, secure stack that can make intelligent decisions on live data in real-time.
The Stanford Data Science Initiative (SDSI) is a university-wide organization focused on core data technologies with strong ties to application areas across campus. SDSI comprises methods research, infrastructure, and education.
Seeks unique data network architectures featuring an information plane using an Information-Centric Networking (ICN) approach and addressing discovery, movement, delivery, management, and protection of information within a network, along with the abstraction of an underlying communication plane creating opportunities for new efficiencies and optimizations across communications technologies that could also address latency and scale requirements.
Addresses the problem of effective software development for diverse hardware architectures through groundbreaking university research that will lead to a significant, measurable leap in software development productivity by partially or fully automating software development tasks that are currently performed by humans.
Supporting long-term research focused on high performance, energy efficient microelectronics for end-to-end sensing and actuation, signal and information processing, communication, computing, and storage solutions that are cost-effective and secure.
ASCENT focuses on demonstration of foundational material synthesis routes and device technologies, novel heterogeneous integration (package and monolithic) schemes to support the next era of “functional hyper-scaling”.
The ADA Center will reignite system design innovation by drawing on opportunities in application driven architecture and system-driven technology advances, with support from agile system design frameworks that encompass programming languages to implementation technologies.
ComSenTer will develop the technologies for a future cellular infrastructure using hubs with massive spatial multiplexing, providing 1-100Gb/s to the end user, and, with 100-1000 simultaneous independently-modulated beams, aggregate hubs capacities in the 10's of Tb/s.
The CRISP grand challenge is to significantly lower the effort barrier for every day programmers to achieve highly portable, “bare-metal,” and understandable performance across a wide range of heterogeneous, IMS architectures.
The nanoelectronic COmputing REsearch (nCORE) program funds collaborative university research in the U.S. to develop key technologies to enable novel computing and storage paradigms with long-term impact on the semiconductor, electronics, computing, and defense industries. The nCORE program supports the National Strategic Computing Initiative (NSCI) through government-industry-academia collaborations. It will be driven by fundamental research on emerging materials and devices with the potential to achieve significantly improved efficiency, enhanced performance, and new functionalities, beyond the capability of conventional CMOS technologies. The new program is built upon the learning from the Nanoelectronics Research Initiative (NRI).
Centered at CMU. Smart Headlights and AndyVision--a planogram generating robot--were both featured at Research at Intel Day in 2012 and were just a few of the many success stories highlighted during the life of the center. 2011 - 2014.
Intel-NTU Connected Context Computing Center
This center aimed to create demonstrable machine-to-machine (M2M) technologies that can showcase the potential of these technologies to transform our everyday activities and environment. Located in Taiwan - NTU. 2010 - 2016.
Centered at Stanford University. The center sought to bring modern trends in computing (the cloud, crowd sourcing, hand-held computing) to bear on hybrids of computer graphics, animation, image understanding, and large-scale gaming. 2011-2015.
Centered at the University of Washington, the Pervasive Computing research center brought together research leaders in wireless communication and sensing, AI and ML, computer vision, HCI, and security. 2011-2016.
Centered at MIT, the Big Data research center is exploring data analytics to support data-intensive discovery including database management, analytics, and visualization support. 2012-2017.
Software Defined Networks (SDN)
Seeks to make networks more amenable to innovation by extending the benefits of SDN to carrier networks. Research vectors include SDN for carriers, processing traffic in software, services architecture, and deployment scenarios. 2014-2017.
Low Latency Architectures
Develop innovative techniques to reducing memory latency, create low latency storage systems, and accelerate progress in general-purpose microarchitectures, and accelerator architectures. 2014-2017.
Develop techniques for effectively summarizing the video egocentric cameras collect and develop solutions for extracting the useful information embedded in the raw data (first-person video, images, audio, and location) egocentric cameras collect and presenting this information to the user on demand. 2014-2017.
Developing novel algorithms, architectures, accelerators, circuits and power management techniques that optimally exploit randomized compressive measurements and compressed domain data processing for 2D/3D still/video/MRI images. 2014-2017.
Hubbed in Germany at Saarland University, the Institute focused on Visual Computing research, meaning the acquisition, modeling, processing, transmission, rendering, and display of visual and associated data. 2010-2016.
Based in England at University College London, Imperial College London, and Future Cities Catapult this center researches the compute fabric needed to support an urban Internet of Things at city scale. 2012-2017.
Based in Germany at TU Darmstadt, this center explores lightweight, cost-effective security and trust anchor primitives for IoT edge devices with integrated outputs into flexible and agile silicon prototypes. 2013-2017.
Based in Israel at Technion and Hebrew University, this center focuses on hardware/software innovations for accelerating Machine Learning and Cognitive Applications. 2013-2017.
Mobile Networking and Computing
Based in China at Tsinghua University, the research center for Mobile Networking and Computing is exploring advanced mobile network technologies to support typical applications in the next generation (5G) networks. 2015-2018.