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Detailed Information

Program of Study

The doctoral program in Cognitive Science was launched in 2003 with the aim of training the next generation of world-class cognitive scientists, and making seminal contributions to the field. In keeping with the interdisciplinary nature of cognitive science, this program trains students to integrate theories, methods, and tools from a variety of fields. Students become engaged in research from the beginning of their first semester in the program, working closely with individual faculty members whose research interests include computational cognitive modeling, artificial intelligence, human and machine reasoning, computational linguistics, perception and action, theoretical neuroscience, cognitive robotics, cognitive engineering, and advanced synthetic characters. There is a strong emphasis on building models of natural and artificial cognitive systems using formal, quantitative, and mathematical tools. The Department has excellent research facilities, such as eye tracking equipment, a robotic arm, and a large-scale immersive virtual environment lab.

The general requirements for completion of the Ph.D. in cognition science consist of a combination of research and other scholarly activities, course work, and attendance at and participation in the Department’s colloquia series. Individual and team-taught seminars are offered on a range of topics, from low-level perception-and-action to high-level reasoning and problem-solving. The program prepares students to become modelers, experimentalists, and theorists and to apply their research to solving real-world problems.

Research Facilities

Research is supported by state-of-the-art facilities and equipment including the Rensselaer Libraries, whose electronic information system provides access to collections, databases, and the Internet from campus and remote terminals; the Rensselaer Computing System, which permeates the campus with a coherent array of more than 7,000 nodes of distributed laptops, desktops, advanced workstations, and servers; a shared toolkit of applications for interactive learning and research and high-speed Internet connectivity; one of the country’s largest academically based, class 100 clean room facilities; high-performance campuswide computing facilities that allow for serial or parallel computation; and five core laboratories for molecular biology, proteomics, bio-imaging, and tissue engineering.

Rensselaer’s research capabilities have been enhanced with the addition of the Computational Center for Nanotechnology Innovations (CCNI). The result of a $100-million collaboration with IBM and New York State, the CCNI is the world’s most powerful university-based supercomputing center and a top ten supercomputing center of any kind in the world. The CCNI is made up of massively parallel Blue Gene supercomputers, POWER-based Linux clusters, and Opteron-based clusters, providing more than 100 teraflops of computational muscle and approximately a petabyte of shared online storage.

Other facilities and research centers include the Center for Biotechnology and Interdisciplinary Studies; the George M. Low Center for Industrial Innovation; research centers for integrated electronics, terahertz science,  nanotechnology, fuel cell and hydrogen research, lighting research, science and technology policy, and infrastructure and transportation studies; the Geotechnical Centrifuge Research Center; the Darrin Fresh Water Institute; and the Scientific Computation Research Center. In addition, academic departments and faculty laboratories have extensive discipline-specific research capabilities and equipment.

Within the Cognitive Science Department, research is conducted in the following labs: the CogWorks Laboratory, the Rensselaer Artificial Intelligence and Reasoning (RAIR) Laboratory, the PandA Labs, the Human-Level Intelligence Laboratory, and the Cognitive Architecture Laboratory (CogArch Lab).

At the CogWorks Laboratory, researchers conduct basic and applied research focused on understanding the interplay of cognition, perception, and action in interactive behavior. These interests entail understanding top-down versus bottom-up control of behavior, the role of implicit versus explicit knowledge, internal versus external representations, and knowledge in-the-head versus knowledge in-the-world.

Research and development in the RAIR Lab ranges across a number of applied projects as well as across many of the fundamental questions AI raises (e.g., Are we machines ourselves? If so, what sort of machines?). Everything is unified to a high degree by the fact that the formalisms, tools, techniques, systems, etc., that underlie the lab’s R&D are invariably based on reasoning.

Research in the PandA Labs is aimed at understanding intelligence by studying the tight linkage between perception and action. Basic questions about visual perception and motor control and coordination are addressed by investigating routine and skilled perceptual-motor tasks, with a specific focus on visually guided actions. Experimental research is conducted in real and virtual environments, and mathematical models are developed using tools from dynamical systems theory and artificial intelligence.

The goal of the Human-Level Intelligence Laboratory is to explain human intelligence and design machines with human-level intelligence. Research is conducted in the integration of reasoning and learning, language understanding, metacognition, and physical reasoning.

The CogArch Lab is focused on research developing comprehensive models of human cognition, that is, cognitive architectures. Research is ongoing investigating the fundamental interaction of implicit and explicit cognition and the interaction of motivation, metacognition, and cognition, consciousness, and computation, as well as cognitive social simulation.

Financial Aid

Financial aid is available in the forms of teaching and research assistantships and fellowships, which include tuition scholarships and stipends. Rensselaer assistantships cover the academic year, with summer support available in many departments. University, corporate, or national fellowships fund many of Rensselaer’s full-time graduate students. Outstanding students may qualify for university-sponsored Rensselaer Graduate Fellowship Awards, which carry a minimum stipend of $22,000 and a full tuition and fees scholarship. All fellowship awards are calendar-year awards for full-time graduate students. Low-interest, deferred-repayment graduate loans are available to U.S. citizens with demonstrated need.

Cost of Study

Full-time graduate tuition for the 2008–09 academic year is $36,950. Other costs (estimated living expenses, insurance, etc.) are projected to be about $13,680. Therefore, the cost of attendance for full-time graduate study is approximately $50,630. Part-time study and cohort programs are priced differently. Students should contact Rensselaer for specific cost information related to the programs they wish to study.

Living and Housing Costs

Graduate students at Rensselaer may choose from a variety of housing options. On campus, students can select one of the many residence halls and immerse themselves in campus life or choose from a select number of apartments designed for graduate students only. There are abundant, affordable options off campus as well, many within easy walking distance.

Student Group

Of the 1,176 graduate students, 29 percent are women and 92 percent are full-time, with 75 percent of full-time graduate students studying at the doctoral level.

Student Outcomes

Rensselaer’s graduate students are hired in a variety of industries and sectors of the economy and by private and public organizations, the government, and institutions of higher education. Their starting salaries average $74,807 for master’s degree recipients and $82,750 for Ph.D. recipients.

Location

Located just 10 miles northeast of Albany, New York State’s capital city, Rensselaer’s historic 275-acre campus sits on a hill overlooking the city of Troy, New York, and the Hudson River. The area offers a relaxed lifestyle with many cultural and recreational opportunities, with easy access to both the high-energy metropolitan centers of the Northeast–such as Boston, New York City, and Montreal, Canada–and the quiet beauty of the neighboring Adirondack Mountains.

The Institute

Recognized as a leader in interactive learning and interdisciplinary research, Rensselaer continues a tradition of excellence and technological innovation dating back to 1824. Rensselaer has five schools–Architecture, Engineering, Management, Science, and Humanities and Social Sciences–that offer more than 100 graduate programs in over forty-eight disciplines that attract top students, researchers, and professors. The discovery of new scientific concepts and technologies, especially in emerging interdisciplinary fields, is the lifeblood of Rensselaer’s culture and a core goal for the faculty, staff, and students. Fueled by significant support from government, industry, and private donors, Rensselaer provides a world-class education in an environment tailored to the individual.

Applying

The admission deadline for the fall semester is January 1. Basic admission requirements are the submission of a completed application form (available online), the required application fee ($75), a statement of background and goals, official transcripts, official scores on the GRE General Test, TOEFL or IELTS scores (if applicable), and two recommendations.

The Faculty and Their Research

• Selmer Bringsjord, Professor and Chair; Ph.D., Brown. Artificial intelligence and cognitive science, including reasoning (computational, empirical, logico-mathematical, educational dimensions), logico-mathematical foundations of AI and Cog Sci, and computational creativity (especially literary), narrative, story generation; philosophy of mind, including philosophical and psychological foundations of AI & Cog Sci. (selmer@rpi.edu)
• Toward a general logicist methodology for engineering ethically correct robots. IEEE Intel. Syst. 21.4:38–44, 2006.
• A new Godelian argument for hypercomputing minds based on the busy beaver problem. J. Appl. Math. Comput. 176:516–30, 2006. With Yang.
• Advanced synthetic characters, evil, and e. In Sixth International Conference on Intelligent Games and Simulation, pp. 31–9, Ghent-Zwijnaarde, Belgium: European Simulation Society, 2005.
• Nick Cassimatis, Assistant Professor; Ph.D., MIT. Understanding and creating human-level intelligence. (cassin@rpi.edu)
• A cognitive substrate for human-level intelligence. AI Magazine 27(2), 2006.
• A model of syntactic parsing based on domain-general cognitive mechanisms. In Proceedings of 28th Annual Conference of the Cognitive Science Society, 2006.
• Mark A. Changizi, Assistant Professor; Ph.D., Maryland. Theoretical and evolutionary neurobiology and cognitive science: understanding the design principles underlying the organization of organisms, cultural artifacts, and ourselves. (changizi@rpi.edu)
• Scaling the brain and its connections. In Evolution of Nervous Systems, ed. J. H. Kaas. Oxford: Elsevier, 2007.
• The structures of letters and symbols throughout human history are selected to match those found in objects in natural scenes. Am. Nat. 167:E117–39, 2006. With Zhang and Shimojo.
• Bare skin, blood, and the evolution of primate color vision. Biol. Lett. 2:217–21, 2006. With Zhang and Shimojo.
• Brett Fajen, Associate Professor; Ph.D., Connecticut. Perception and action, visual perception, motor control, virtual environments, ecological psychology, dynamical systems modeling. (fajenb@rpi.edu)
• The scaling of information to action in visually guided braking. J. Exp. Psych. Hum. Percept. Perform. 31(5):1107–23, 2005.
• Perceiving possibilities for action: On the necessity of calibration and perceptual learning for the visual guidance of action. Perception 34(6):741–55, 2005.
• The behavioral dynamics of steering, obstacle avoidance, and route selection. Journal of Experimental Psychology: Human Perception and Performance 29(2):362, 2003.
• Wayne D. Gray, Professor; Ph.D., Berkeley. Integrated cognitive systems, computational cognitive modeling, cognitive engineering: understanding the interplay of cognition, perception, and action in routine interactive behavior. (grayw@rpi.edu)
• Integrated Models of Cognitive Systems. W. D. Gray, ed. New York: Oxford University Press, 2007.
• The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior. Psych. Rev. 113(3):461–82, 2006.
• Project Ernestine: Validating a GOMS analysis for predicting and explaining real-world performance. Human-Computer Interaction 8(3):237–309, 1993.
• Mike Kalsher, Associate Professor; Ph.D., Virginia Tech. Human factors, industrial/organizational psychology, applied experimental psychology. (kalshm@rpi.edu)
• Human factors design considerations for on-product medical device labels. In Human Factors in Medical Device Design: A Handbook for Designers, eds. M. Wiklund, D. Gardner-Bonneau, and M. B. Weinger. Mahwah, New Jersey: Lawrence Erlbaum & Associates, in press.
• Psychology: From Science to Practice, Needham Heights, Massachusetts: Allyn & Bacon, 2005. With Baron.
• Behavioral compliance and methodology. In Handbook of Warnings, ed. M. Wogalter. Mahwah, New Jersey: Lawrence Erlbaum & Associates, 2005.
• Ralph G. Noble, Associate Professor; Ph.D., Berkeley. Psychobiology of choice and decision making. (nobler@rpi.edu)
• Bill Puka, Professor; Ph.D., Harvard. Ethics and moral development, cognitive science: ethical problem-solving processes using protocol analysis. (pukab@rpi.edu)
• Supporting ethical problem solving: An exploratory investigation. Proceedings of the 2004 SIGMIS Conference on Computer Personnel Research: Careers, Culture, and Ethics in a Networked Environment, pp.134–43. New York: ACM Press, 2004.
• Fundamental Research in Moral Development. New York: Garland, 1994.
• Larry Reid, Professor; Ph.D., Utah. Physiological psychology of reinforcement, drug and alcohol addiction. (reidl@rpi.edu)
• Periodic naltrexone and propensity to take alcoholic beverage. Alcoholism: Clinical and Experimental Research 20:1329, 1996.
• Ron Sun, Professor; Ph.D., Brandeis. Cognitive science and artificial intelligence, cognitive architectures, learning and skill acquisition, cognitive social simulation and multiagent systems, everyday commonsense reasoning, computational studies of consciousness, connectionist models and hybrid systems. (rsun@rpi.edu)
• The interaction of the explicit and the implicit in skill learning: A dual-process approach. Psychol. Rev. 112(1):159–92, 2005.
• From implicit skills to explicit knowledge: A bottom-up model of skill learning. Cog. Sci. 25(2):203–44, 2001.
• Robust reasoning: Integrating rule-based and similarity-based reasoning. Artif. Intell. 75(2):241–96, 1995.
• Yingrui Yang, Associate Professor; Ph.D., NYU. Cognitive psychology; thinking, reasoning, and decision making; cognitive science. (yangyri@rpi.edu)
• Mental possible world mechanism: A new method for analyzing logical reasoning problems on the GRE. J. Exp. Theo. Artif. Intell. l18(2):157–68, 2006. With Bringsjord.
• Strategies in sentential reasoning. Cognitive Sci. 26:425–68, 2002.
• Some empirical justifications of one mental predicate-logic model. In Mental Logic, pp. 333–65, eds. M. D. S. Braine and D. P. O’Brien. Mahwah, New Jersey: Lawrence Erlbaum Associates, 1998.
• Michael Zenzen, Professor; Ph.D., Rensselaer. Philosophy of science and foundations of physics, especially the use of mathematics in the construction of physical theory; general relation between rationality and intuition, specifically, the use of formalism to extend intuitive understanding. (zenzem@rpi.edu)
• Superminds: People Harness Hypercomputation, and More. Dordrecht, The Netherlands: Kluwer, 2003. With Bringsjord.
• Toward a formal philosophy of hypercomputation. Minds and Machines 12(2):241–58, 2002. With Bringsjord.
• Cognition is not computation: The argument from irreversibility. Synthese 113(2):285–320. 1997. With Bringsjord.

Correspondence and Information

Rensselaer Polytechnic Institute
Cognitive Science Department
Carnegie 108
110 8th Street
Troy, New York 12180
Telephone: 518-276-6472
Email: osgane@rpi.edu