Computational Science Vision for the Future of

Science: Excellence through Interdisciplinary Research and

Education

Susan Keun-Hang Yang, PhDProfessor, Computational Science

Director, International Science Programs Chapman University

Agenda Chapman’s Schmid College of Science

Computational Science at Chapman University

Classical Science Computational Science

Data Science

Chapman’s Schmid College of Science: Rationale for Interdisciplinary Science Programs Science is today critical to most of societies’

problems Understanding science at a level that will allow

general appreciation and assist someone to be a better citizen, and more productive in her work, will be crucial as society’s issues become more complex

Chapman is known for its individualized, competent training in several fields: Interdisciplinary science focused in computational science will be developed as part of what Chapman is known for nationally and internationally

We have a real opportunity to work with other schools such as Business and Law in providing their students understanding in the sciences and give them an edge over their competitors

Build Computational Science Infrastructure at Chapman University

RS Lab (12 nodes) S/W: ENVI, GIS, etc. (H. El-Askary, C. Kim, A. Prasad, M. Kafatos

CU; X. Liu, IGC) Modeling capabilities (C. Tremback, A. Prasad, TBD Computer

Engineer) CU Modeling Lab (10 node PC-cluster, 2 servers)

RAMS (with G. Kallos, Univ. Athens, CU; C. Tremback, ATMET, CU)

ICLAMS (with G. Kallos, Univ. Athens, CU; C. Tremblack, ATMET, CU)

WRF (Community model) Hydrology Modeling (S.K. Park, Ewha Womans Univ.)

CU Climate Scenarios IPCC Global Model Scenarios for future

Chapman Science Intends to be Internationally Known in Key Science Areas

Only SUNY Brockport offers undergraduate degrees in computational science

Only Chicago, Michigan (and 3 more) have programs in computational finance

Chapman will create strong ties with local industries and universities for applied research projects

We will establish national leadership in several key areas such as: Undergraduate degrees in computational science Computational biology and biotechnology Applications of quantum theory Computational mathematics (wavelets, statistics, etc.) Applied research in hazards (earthquakes, forest fires, floods, droughts, pollution, etc.) Top notch undergraduate research M.S. and Ph.D. in computational science Explore feasibility of interdisciplinary programs such as computational finance, film and

computers, etc.

Chapman just recruited a top team of scientists to its faculty, including:

Yakir Aharonov: Internationally known Physicist, nominated for Nobel Prize; received Wolf Prize, etc.

Foundations of quantum theory, weak measurements, Aharonov-Bohm effect (quantum non-locality); discovered more than 30 effects named after him; member of the National Academy of Sciences, received numerous prizes

Jeff Tollaksen: Aharonov’s collaborator and Chair Department of Physics, Computational Science and Engineering

Susan Keun-Hang Yang: Director, International Science Programs, renown expert in computational biology and neuroscience, Computational biology, computational neuroscience, biochemistry, bioinformatics, electrophysiology

Menas Kafatos

Earth system science Aerosols Hazards and climate change Computational science Quasar redshifts and cosmological models Active galactic nuclei Black holes and general relativity Fluid motions in curved spacetime Quantum theory and Cosmology Consciousness and quantum theory

Wealth of research experience and international reputation, administrator (dean, director and principal investigator of large, muti-member projects); founder of many innovative educational programs, including computational science, global and environmental change, etc. Author of 12 books and 290 articles. Participates in international programs in Korea, Greece, Egypt, World Meteorological Organization, member of Romanian Academy of Sciences, member of National Academy, National Science Foundation and NASA panels.

Earth system scienceAerosolsPollutionRemote sensing

Hesham el-Askary

Earthquakes FiresPredicted within days of its occurrence the devastating earthquake that rocked southern China in May 2008

Dimitar Ouzounov

Eyal Amitai

Hydrology , Precipitation, Floods in Orange CountyPrincipal collaborator on The Global Precipitation Measurement,joint U.S.-Japanese mission

Ramesh SinghRemote Sensing, Aerosols, Pollution

Proposed Structure of New Graduate Science Degree

ProgramsM.S. Hazards and Global Environmental Change– Core, 13 Credits

– Electives, 18 Credits; or

– Electives, 15 Credits; Thesis, 3 Credits

M.S. Computational Science– Computational Biology/Biotechnology Track

– Computational Mathematics Track

– Modeling and Data in Earth System Science

Ph.D. Computational Science– Core: Scientific Computing; Scientific Databases; Visualization; Numerical Techniques

– Science Tracks; and Tracks with other Colleges

– Doctoral Thesis

School of Computational Sciences

School of Environmental Sciences/Global ChangeSchool of Health Sciences

Public Health

Chronicle of Higher Education: “5 College Majors on the Rise”

Chronicle of Higher Education (September 4, 2009)

Computational Science

SustainabilityHealth Informatics

Service Science

Theoretical, Laboratory andComputational Science

Theory

Experiment

Computing

Two Classical Phases of Science Theoretical Science (e.g. the

formulation of the general theory of relativity; brain dynamics)

Experimental/Laboratory Science (e.g. the development of experiments to confirm or deny general relativity theory: deflection of light during a total solar eclipse; fMRI)

The Third Phase of Science:Computational Science

When a fully formed theory does not exist (e.g. we do not fully understand what causes cancer)

When a theory exists but cannot be applied because of its complexity (e.g. we fully understand the theory of hurricanes, but the physics of turbulence is too complex)

When experiments are impossible or too cumbersome (e.g. experiments with blood flow in humans, etc.)

Computational Science Computational science is a fairly new

discipline which is defined as: “Computational science (or scientific computing) is the field of study concerned with constructing mathematical models and numerical solution techniques and using computers to analyze and solve scientific, social scientific and engineering problems. In practical use, it is typically the application of computer simulation and other forms of computation to problems in various scientific disciplines.”

Computational Science : Frontier Approaches for Applied Science & Engineering

Distinct from computer science (the mathematical study of computation, computers and information processing). Scientific computing is to gain understanding through the analysis of mathematical models implemented on computers.

Scientists and engineers develop computer programs, application software, that model systems being studied and run these programs with various sets of input parameters. Typically, models require massive calculations (usually floating-point) and are executed on supercomputers or distributed computing platforms.

Numerical analysis is an important underpinning for computational science.

Programming languages commonly used for the more mathematical aspects of scientific computing applications include Fortran, MATLAB, SciLab, GNU Octave, COMSOL Multiphysics, and PDL. The more computationally-intensive aspects of scientific computing often utilize some variation of C or Fortran.

Computational Science

Computational science application programs often model real-world changing conditions, such as weather, air flow around a plane, automobile body distortions in a crash, the motion of stars in a galaxy, an explosive device, etc. Such programs might create a 'logical mesh' in computer memory where each item corresponds to an area in space and contains information about that space relevant to the model. For example in weather models, each item might be a square kilometer; with land elevation, current wind direction, humidity, temperature, pressure, etc. The program would calculate the likely next state based on the current state, in simulated time steps, solving equations that describe how the system operates; and then repeat the process to calculate the next state”.

Computational Science

Therefore, computational science involves both the computing methodology and the scientific applications. Applied mathematics, numerical analysis as well as computational methods are all part of scientific computing or computational science. Established areas of computational science include applications in computational fluid dynamics, atmospheric science, seismology, chemistry, global ocean/climate modeling, environmental studies, physics, with emerging applications in bioinformatics, neuroscience, economics, etc. The list continues to grow.

Computational Science

Many experiments and investigations that have traditionally been performed in a laboratory, a wind tunnel, or the field can now be performed using computers. While some studies, such as global climate change, involve time scales that preclude the use of realistic physical experiments.

Computational Science

Data Science: Data Mining and Massive Data

Sets Massive data sets are expanding

exponentially across several fields “On demand” access is expected by

diverse user communities K-12, undergraduate and graduate students, policy makers, the general public

Data access and analysis are essential Data mining looks promising to reduce

the volume and complexity of available data

Data Science: The Challenge of Exploding

Information

Data Volume

Number of Scientists & Engineers

Data Transfer Rate

Understanding Cancer

Relevance of New Team to California

Floods Wildfires Droughts Earthquakes Biotechnology Bioinformatics General computational tools Mathematical tools Data mining, computing Engineering

Theoretical Science Experimental/Laboratory Computational science

ulti sensor Earthquake

Observations

Aerosols

Modeling the Blood

Flow

Classical Phases of Science