Multimodal Big Data

Multimodal Big Data Health Care

Multimodal Big Data Science and Healthcare

The Center for Multimodal Big Data Science and Healthcare's primary mission is to address the grand challenge of developing novel computational methods leveraging image analysis, natural language processing, machine learning, system identification and database technologies to discover significant knowledge to provide a transformative impact on a broad spectrum of applications. A central component in this research effort is the BisQue image management and analysis platform that supports the management and analysis of large scale, multi-dimensional multimodal images.


BMSE

Quantitative Biology

Biomolecular Science and Engineering (BMSE) at UC Santa Barbara enables cutting-edge research and provides post-graduate education at the interface between the Biological, Physical, and Engineering Sciences. We are an integral component of UCSB's widely recognized strength in interdisciplinary research. Drawing its faculty from eight departments and two colleges, BMSE is uniquely capable of developing outstanding young scientists well-versed in quantitative aspects of modern biological science, and ready for leadership positions in multidisciplinary research.


Bio Engineering

Center for Bioengineering

Biological Engineering is a hub for research and teaching at the interface of biology, engineering and physical sciences. It builds on UC Santa Barbara’s strengths in biophysics, biomaterials, biomolecular discovery, and computational and experimental systems biology, enabling fundamental scientific discoveries to be transitioned to applications in medicine and biotechnology.


Bioimage Informatics

Bioimage Informatics

The Center for Bio-image Informatics is an interdisciplinary research effort between Biology, Computer Science, Statistics, Multimedia and Engineering. The overarching goal of the center is the advancement of human knowledge of the complex biological processes which occur at both cellular and sub-cellular levels. To achieve this core objective, the center employs and develops cutting edge techniques in the fields of imaging, pattern recognition and data mining.


Brain Initiative

Brain Initiative

The UCSB Brain Initiative is a campus-wide initiative to foster collaboration and recruit top neuroscientists to Santa Barbara. The UCSB Brain Initiative spans departmental boundaries and seeks to build on the campus’s strengths in engineering, physics, and computer science to elucidate the function of the brain.


Earth Research

The mission of the Earth Research Institute (ERI) is to support research and education in the sciences of our solid, fluid, and living Earth. While the scope of ERI research spans the breadth of Earth and Environmental sciences, the institute is organized around four major themes of Natural Hazards, Human Impacts, Earth System Science, and Earth Evolution. Each of these themes has been transformed in the past decade by both the increasing availability of high-resolution spatio-temporal data, and the emergence of complex physically-based modeling approaches for characterizing the dynamics of Earth and Environmental systems. ERI faculty and researchers are taking advantage of this convergence of big data and large-scale modeling to catalyzed new discoveries and understanding across campus, while ERI research computing staff are developing new infrastructure and data management tools for handling these computationally intensive approaches. 


Center for Responsible Machine Learning

Responsible Machine Learning

Artificial intelligence (AI) is changing our world. The Center for Responsible Machine Learning reflects UC Santa Barbara's commitment to advancing cutting-edge research in AI, machine learning, natural language processing, and computer vision, with an emphasis on the societal impacts of these rapidly evolving technologies. We are particularly interested in addressing issues of fairness, bias, privacy, transparency, explainability, and accountability in the context of AI algorithms, and in understanding the wide range of ethical, policy, legal, and even energy-efficiency issues associated with machine-learning models. We envision the center becoming an indispensable locus of innovation, where bold leaders produce visionary software and revolutionary techniques that powerfully serve the greater good.


 

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