Carnegie Mellon University Planning Grant: I/UCRC for Big Learning

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This project will study the feasibility of establishing the Center for Big Learning (CBL), as an NSF IUCRC. The mission of CBL is to develop novel large-scale deep learning algorithms, systems, and applications through unified and coordinated efforts in the CBL consortium. The vision of CBL is to develop intelligence algorithms towards intelligence-driven society. With the explosion of big data generated from natural systems, scientific experiments, engineered systems, and human activities, we need to develop intelligent algorithms and systems to facilitate our decision making with distilled insights automatically at scale. The proposed CBL center is a timely initiative as we move towards intelligence-enabled world of opportunities. The CBL consortium is expected to become the magnet of deep learning research and applications and attract leading researchers, entrepreneurs, IT and industry giants working together on accomplishing our mission and vision. This planning grant will lead to a successful Phase I proposal for the establishment of the Center for Big Learning at CMU with a solid consortium across multiple campuses and a large number of industry partners.CBL has the following broader impacts. (1) Making significant contributions and impacts to the deep learning community on pioneering research and applications to address a broad spectrum of real-world challenges. (2) Making significant contributions and impacts to promote products and services of industry in general and our members in particular. (3) Making significant contributions and impacts to the urgently-needed education of our next-generation talents with real-world settings and world-class mentors from both academia and industry. (4) Our meetings, forums, conferences, and planned training sessions will greatly promote and broaden the research and materialization of Deep Learning.Recent dramatic breakthroughs in deep learning (DL) and multi-model learning (e.g., image, video, speech, and text), hold great promise for making a big impact on many research areas, including computational biology, neuroscience, medical diagnosis, computer vision, data mining, and robotics. The key mission of CBL at CMU is to pioneer in large-scale deep learning (DL) algorithms, systems, and applications through unified and coordinated efforts in the CBL consortium via fusion of broad expertise from our large number of faculty members, students, and industry partners. The vision of CBL at CMU is to develop intelligent algorithm towards intelligence-driven society. CBL possesses the pioneering intellectual merit in the following key research themes:(1) Novel algorithms. This theme focuses on novel DL algorithms and architectures, such as deep neural networks, complex recurrent neural networks, brain-inspired components, optimization, deep reinforcement learning, and unsupervised learning.(2) Novel systems. We propose to develop novel architectures, resource management, and software frameworks for enabling large-scale DL platforms and applications on desktops, mobiles, clusters, and clouds.(3) Novel applications in health, mobile/IoT, and surveillance. During the planning phase, we will establish a solid center strategic plan, marketing plan, and the CBL consortium that consists of four academic sites and a large number of industrial members.