State of Computer Science Research

Let me just first share to you insights on what computer science is. As stated in the Wikipedia, Computer science (or computing science) is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that describe and transform information. According to Peter J. Denning, the fundamental question underlying computer science is, "What can be (efficiently) automated?". Computer science has many sub-fields; some, such as computer graphics, emphasize the computation of specific results, while others, such as computational complexity theory, study the properties of computational problems. Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing computations, while computer programming applies specific programming languages to solve specific computational problems, and human-computer interaction focuses on the challenges in making computers and computations useful, usable, and universally accessible to people. However, the focus of computer science is more on understanding the properties of the programs used to implement software such as games and web-browsers, and using that understanding to create new programs or improve existing ones. As a discipline, computer science spans a range of topics from theoretical studies of algorithms and the limits of computation to the practical issues of implementing computing systems in hardware and software. The Computer Sciences Accreditation Board (CSAB) – which is made up of representatives of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers Computer Society, and the Association for Information Systems – identifies four areas that it considers crucial to the discipline of computer science: theory of computation, algorithms and data structures, programming methodology and languages, and computer elements and architecture. In addition to these four areas, CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.

The prediction that computers will be increasingly important in our schools, offices, and homes has become a cliché. Word-processing, electronic mail, databases, spreadsheets, analytic tools, and telecommunications have allowed researchers, office workers, and families to have access to a resource that was previously the territory of government, big businesses, and large universities. The way we live and work is being changed and enhanced by improved access to public databases, increased availability of sophisticated computational software, and world-wide communications facilities at a relatively modest price. Artificial intelligence, particularly robotics and expert systems, is a field of computer science that will have a powerful impact on our culture in the near future. What some have perceived as a revolution, however, is actually an evolution of the influence of computing on our society over the past 40 years. Though several generations of computers have matured during this period, their distinctions are not at all clear, primarily because they provide a continuum of capabilities, rather than a succession of preemptive advances. Thus microcomputers, the most recent result of this process, do not replace their mainframe and minicomputer predecessors, function concurrently and complimentarily with them.

Latanya Sweeney from the Carnegie Mellon University stated that Computer Science research and practice are raising growing privacy concerns among the public and government. Computer technology’s increasing ability to capture, organize, interpret and share data about individuals raises questions about what privacy practices computer science researchers should adopt, if any. Not all areas of computer science research are affected by privacy issues.

In the crudest classifications possible, computer science research can be divided into:
(1) theoretical computer science, which has a close relationship to logic and mathematics;
(2) programming languages and systems, which concerns the general development and operation of physical computer systems and networks; and,
(3) artificial intelligence (AI), which has a long-term vision of producing machines that can think, reason and function comparable to humans
Most of the research facing privacy concerns fits into the crudely classified third group, AI.

In more fine-grained classifications, computer science research involving human-computer interaction, personal robots and assistants, biomedical applications, data mining, sensor technology, ubiquitous computing, cybersecurity, and data privacy (a new emerging area aimed at providing technical solutions to privacy problems) are more likely today to face privacy controversies than are any other research areas in computer science.

Two kinds of privacy issues arise in computer science research:
(1) privacy issues inherent in applications of developing technology; and,
(2) privacy issues related to information or practices needed to develop technology.
This shift in computer science research is due in great part to two trends:
(1) the field’s increasing ability to capture and share large volumes of person-specific information and (2) the field’s increasing development of methods to use that information to develop more useful machines.

Latanya Sweeney also pointed out that if developments in computer technology have raised privacy issues, then many believe computer technology can be instrumental in resolving them.

Another article related on Computer Science research also discussed the state of computer science research in India. India prides itself in having one of the largest technical manpower in the world. Her software industry has seen tremendous growth -- over 50% each year during the last 10 years -- which is the envy of many software exporting countries throughout the world. The students from India's top science and technology educational institutions are highly sought after by research universities in the US and Europe. Computer Science (CS) research in India started in earnest only in the mid-80's triggered by the establishment of post-graduate programs in many institutions throughout the country at that time. Today, almost all areas of computer science research are covered by researchers in India, including topics that are "hot" elsewhere such as multi-media, workflow automation, virtual reality, and hardware-software co-design. Some of the research has even attracted international attention including work on neuro-fuzzy systems, machine learning, genetic and neural algorithms, the modeling and control of flexible manufacturing systems, speech synthesis, databases, and complexity theory. There are many in Indian computer science who argue that the goals of research and development in India ought to be manpower development, increasing competence, and keeping faculty up-to-date with current techniques. Towards this end, it is said that "reinventing the wheel" is not only necessary but also important. This might be one of the reasons that even though it is said (repeatedly) that India has one of the world's largest technical manpower, the manpower needed to do state-of-the-art research is found to be wanting, both in quality and quantity.

Without Computer Science-sponsored research, complex, inefficient computer systems could overwhelm scientists. The software industry is unlikely to commit to long-term research or to develop programming for the relatively few machines equipped with tens to hundreds of thousands of processors. Yet, these powerful computers and the applications that run on them are vital to maintaining the United States’ competitiveness in the world economy. Computer Science research will focus on scalable software and applications that can weather system reliability. Such efforts are pushing computer science into unknown realms of discovery.
Various topics on computer science research have been mentioned in the previous paragraphs but I think the current topic which I considered to be really relevant nowadays are those that pertain to the environment which topics are usually termed as “green”.

References:
http://reports-archive.adm.cs.cmu.edu/anon/isri/CMU-ISRI-03-102.pdf
http://www.fas.org/nuke/guide/india/agency/krithi2.html
http://arjournals.annualreviews.org/doi/abs/10.1146/annurev.pu.06.050185.001545?cookieSet=1&journalCode=publhealth
http://www.science.doe.gov/ascr/Research/ComSci.html