FCI Programs

Computational Biology

Genomic databases, protein databanks, MRI images of the human brain, and remote sensing data on landscapes contain unprecedented detailed information about biological systems that are transforming the way that we do almost all of biology. Problems investigated by computational biologists span a wide spectrum including topics as diverse as the genetics of disease susceptibility, comparing whole DNA genomes to uncover the secrets of evolution, predicting protein structures and understanding their motions and interactions, designing new therapeutic drugs, mathematically modeling the complex signaling mechanisms within cells, predicting how ecosystems will respond to climate change, and designing recovery plans for endangered species. The computational biologist must have skills in mathematics, statistics, and the physical sciences as well as in biology. A key goal in training is to develop the ability to relate biological processes to mathematical models that can be solved computationally.

Cornell faculty work primarily in four subareas of computational biology: biomolecular structure, bioinformatics and data mining, ecology and evolutionary biology, and statistical and computational methods for modeling biological systems. These include the computational study of topics such as DNA databases, protein structure and function, computational neuroscience, biomechanics, population genetics, and management of natural and agricultural systems. Beyond the basic core skills in mathematics, physical sciences and biology, the computational biology program of study requires additional coursework in mathematics, computer programming, a "bridging" course aimed at connecting biology to computation, and an advanced course where the theoretical/computational component of one aspect of biology will be studied.

The FCI-created undergraduate program of study in computational biology encourages students to gain fundamental skills and understanding that will allow them to focus on specific subareas and problems later in their careers. Computational biology is a new emerging area that has applications as broad as biology itself. The problems of interest, as well as the tools available to study them, will undoubtedly change during the four years of an undergraduate program. The program is an excellent preparation for students who wish to specialize in one of these computational areas in graduate school. There is great, and increasing, demand for research scientists and technical personnel who can bring mathematical and computational skills to the study of biological problems.

Computational Molecular Biology (CMB) is an interdisciplinary field that brings together numerous diverse research areas. A separate and isolated program in CMB will have difficulties in maintaining excellence in all fields, in teaching the diverse tools, and in providing the breadth of research topics that form the core of CMB. We therefore propose a different model of a multi-field program in Computational Molecular Biology. Computational Molecular Biology is a program that crosses several fields. For example, to meet the program conditions, a Ph.D. candidate in computer science can have supplementing studies in molecular biology. Alternatively, a Ph.D. student in the biophysics field can have supplementing studies in computer science and meet the CMB requirements. Hence, the students of this program may come from diverse fields such as molecular biology and genetics or computer science, creating the diverse community of researchers that we seek in CMB.

Digital Arts and Graphics

Graphics is approaching a crossroads. University departments around campus depend on computer technology; architecture can't be produced without the computer; art graduates don't have to use computers, but many are discovering new creative outlets using them. Computational graphics, which has been dominated by the entertainment industry, will change dramatically in the next decade or two. We have the process, technology and knowledge to effect this change correctlysimulate the physical world with images that are faithful and we believe that studies that integrate computer technology in the arts and graphics arenas will become an avenue of importance. The focus is on many areas, including, but not limited to music, art, and arcitecture. As technology becomes more integrated into their artistic enterprises, Cornell students from many disciplines will gain an understanding of the computer fundamentals that will help them grow as artists.

Information Science

Information Science at Cornell is an interdisciplinary program in the FCI that allows graduate and undergraduate students to study new theories, models, concepts and design principles that incorporate an understanding of both social and technical information systems. The field of information science combines aspects of computer science and human-computer interaction with an examination of the social, economic, political, and legal contexts in which information systems function. Students in the information science program will obtain an understanding of the core topics of study emerging in this new and quickly growing field: the design and analysis of computing applications, information infrastructures, and human-centered systems; the legal, economic, and ethical issues that surround the construction of information systems; and the ways in which information technology is transforming society. Specific topics emphasized in the information science program include electronic communication; knowledge networking; collaboration within and across groups, communities, organizations, and society; the web and web information systems; natural language processing; computational techniques in the collection, archiving and analysis of social science data; information privacy; methods of collecting, preserving, and distributing information; information system design; cognition and learning; and human interface design and evaluation.

Computational Science and Engineering

Many of the faculty in engineering and the sciences engage in research that is computationally driven. Computational science and engineering (CS&E) at Cornell continues to be as strong as ever. Critical to the overall environment is the Cornell Theory Center, whose Velocity Cluster supports lines of inquiry that require intensive, large-scale computation.

This year the CS&E subgroup of the FCI accomplished several things. First, it created four "FCI short courses" to be offered during the coming academic year:

CS 401 Applied Scientific Computing with MATLAB

CS 402 Scientific Visualization with MATLAB

CS 403 Development of Scientific Computing Programs in a Unix Environment

CS 404 Survey and Use of Libraries for Scientific Com- puting

These practical, 4-week courses are directed at beginning graduate students across the campus. With FCI support, the Department of Earth and Atmospheric Sciences hired Dr. Andrew Pershing, who will serve as the instructor. We expect to be able to offer these courses and other courses as "CIS" courses in future years.

The CS&E subgroup also put together a website that publicizes the CS&E activities at Cornell. Faculty and courses are presented in a way that is useful to current and incoming students.

Finally, the CS&E subgroup helped orchestrate the hiring of Professor Hod Lipson in the School of Mechanical and Aerospace Engineering. This appointment will do a great deal to enrich the connection between the FCI and the College of Engineering.