Cross-cutting Areas and Systems
View the complete list of Cross-cutting Areas and Systems cluster founding faculty.
CyberInfrastructure (Cloud, Computation, Networks)
CI, human and machine, is where ideas and fundamentals of data science get implemented in practical systems used by scientific communities to derive knowledge from data.This is an integration heavy area that could benefit/relate to many others.
CyberInfrastructure (Cloud, Computation, Networks) Members
John Ahlquist Global Policy & Strategy
Rommie Amaro Chemistry & Biochemistry
Chaitan Baru San Diego Supercomputer Center
Eric Bennett Biological Sciences
Jelena Bradic Mathematics
Benjamin Bratton Visual Arts
Todd Coleman Bioengineering
Tom DeFanti Qualcomm Institute
Fernando
Hadi Esmaeilzadeh Computer Science & Engineering
Ron Graham Computer Science & Engineering and Mathematics
Amarnath Gupta San Diego Supercomputer Center
Michael Holst Mathematics and Physics
Trey Ideker Health Sciences and Bioengineering
Lilly
Michael Norman Physics and San Diego Supercomputer Center
Ramesh Rao Electrical & Computer Engineering
Tajana Rosing Computer Science & Engineering
Brett Stalbaum Visual Arts
George Sugihara Biological Oceanography and Natural Science
Alexander Vardy Electrical & Computer Engineering and Computer Science & Engineering
Frank Wuerthwein Physics and San Diego Supercomputer Center
Sonia Martinez Diaz Mechanical and Aerospace Engineering
Telecommunication Networks and Wireless Systems
Traditional approaches to traffic engineering and network deployments rely on generic modelling assumptions and rule of thumb over provisioning. Future generation systems, such as 5G systems, aspire to
Telecommunication Networks and Wireless Systems Members
Dinesh Bharadia Electrical & Computer Engineering
Bhaskar Rao Electrical & Computer Engineering
Ramesh Rao Electrical & Computer Engineering
Nambi Seshadri Electrical & Computer Engineering
Alexander Vardy Electrical & Computer Engineering and Computer Science & Engineering
Xinyu Zhang Electrical & Computer Engineering
Data-Driven System Design
We focus on the use of data science to reduce the difficulty and cost of complex system design processes that today require thousands of engineers and years of schedule. Goals include (1)
Data-Driven System Design Members
Amy Alexander Visual Arts
Benjamin Bratton Visual Arts
Todd Coleman Bioengineering
Steven Dow Cognitive Science
William Griswold Computer Science & Engineering and Design Lab
Amarnath Gupta San Diego Supercomputer Center
Jim Hollan Cognitive Science
Andrew Kahng Computer Science & Engineering and Electrical & Computer Engineering
Scott Klemmer Cognitive Science and Computer Science & Engineering
Alex Orailoglu Computer Science & Engineering
Alan Simmons Psychiatry
Brett Stalbaum Visual Arts
George Sugihara Biological Oceanography and Natural Science
Xin Tu Biostatistics and Family Medicine & Public Health
Kamala Visweswaran Ethnic Studies
Frank Wuerthwein Physics and San Diego Supercomputer Center
Kesong Yang NanoEngineering
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Data Visualization, Sonification, Interactive Spaces (AR/VR)
Data Visualization, Sonification, Interactive Spaces (AR/VR). Activity Centered Visualization Members
Amy Alexander Visual Arts
Nuno Bandeira Computer Science & Engineering and Skaggs School of Pharmacy & Pharmaceutical Sciences
Eric Bennett Biological Sciences
Sheldon Brown Visual Arts
Manmohan Chandraker Computer Science & Engineering
Steven Dow Cognitive Science
Shlomo Dubnov Music
James Fowler Medicine and Political Science
Joshua GraffZivin Global Policy & Strategy and Economics
John Graham Qualcomm Institute
John Hildebrand Scripps Institution of Oceanography
Jim Hollan Cognitive Science
Trey Ideker Health Sciences and Bioengineering
Dusan Keres Physics
Scott Klemmer Cognitive Science and Computer Science & Engineering
Kim Prather Chemistry & Biochemistry
Yannis Papakonstantinou Computer Science & Engineering
Debashish Sahoo Pediatrics and Computer Science & Engineering
Brett Stalbaum Visual Arts
Pinar Yoldas Visual Arts
Scientific Workflows and Process Management
Instruments (and possibly simulations as well) across all scientific disciplines are a source of
Scientific Workflows and Process Management Members
John Ahlquist Global Policy & Strategy
Ilkay Altintas San Diego Supercomputer Center
Rommie Amaro Chemistry & Biochemistry
Nuno Bandeira Computer Science & Engineering and Skaggs School of Pharmacy & Pharmaceutical Sciences
Chaitan Baru San Diego Supercomputer Center
Jennifer Burney Global Policy & Strategy
Bruce Cornuelle Scripps Institution of Oceanography
John Hildebrand Scripps Institution of Oceanography
Andrew Kahng Computer Science & Engineering and Electrical & Computer Engineering
Thomas Liu Center for fMRI and Radiology Psychiatry and Bioengineering
George Sugihara Biological Oceanography and Natural Science
Frank Wuerthwein Physics and San Diego Supercomputer Center
Peter Rose San Diego Supercomputer Center
Data Science in Art
Understanding how meaning is made with new methods of representation is the ongoing undertaking of contemporary art. With new ways of characterizing the self and the world through data science, insight will come from
Data Science in Art Members
Jordan Crandall Visual Arts
Neuromorphic Engineering
Neuromorphic Silicon Learning Machines Learning and adaptation are key to natural and artificial intelligence in complex and variable environments. Neural computation and communication in the brain are partitioned into the grey matter of dense local synaptic connectivity in tightly knit neuronal networks, and the white matter of sparse long-range connectivity over axonal
Neuromorphic Engineering Members
Gert Cauwenberghs Bioengineering
Hadi Esmaeilzadeh Computer Science & Engineering
Tajana Rosing Computer Science & Engineering
Pinar Y
Data, Public Policy and Law - Shaping Public Opinion
Data, Public Policy and Law. Shaping Public Opinion Members
John Ahlquist Global Policy & Strategy
Chaitan Baru San Diego Supercomputer Center
Cinnamon Bloss Family Medicine & Public Health
Benjamin Bratton Visual Arts
Richard Carson Economics
Scott Desposato Political Science
Kamala Visweswaran Ethnic Studies
Pinar Y
Angela Yu Cognitive Science
Kirk Christian Bansak Political Science
Robust machine learning on artificial neural networks utilizing advanced non-volatile memory technologies
Neuro-inspired hardware-software co-design approaches for energy-efficient neural networks utilizing non-volatile memory-based synaptic devices. Characterization,
Robust machine learning on artificial neural networks utilizing advanced non-volatile memory technologies Members
Duygu Kuzum Electrical & Computer Engineering
Paul Siegel Electrical & Computer Engineering