Iowa State University

    Department of Computer Science
    Center for Computational Intelligence, Learning, and Discovery

Artificial Intelligence Research Laboratory

   Note to Prospective Students   

  


Note to Prospective Students

Iowa State University offers outstanding research and graduate training opportunities in Artificial Intelligence, Bioinformatics, and related areas through graduate programs in:

The Artificial Intelligence Research Laboratory welcomes prospective graduate students from around the world with interest in these areas to apply for admission to a graduate program at Iowa State University that best matches their background and interests.

If you are already enrolled in one of these graduate programs, or would like to visit the department to explore graduate or postdoctoral research opportunities in the Artificial Intelligence Research Laboratory please e-mail me or phone me to set up a visit.

If you are interested in applying for admission to a graduate program at Iowa State University with the goal of pursuing research in Artificial Intelligence, Bioinformatics and Computational Systems Biology, Machine Learning, Data Mining, Information Integration, Semantic Web, Computational Neuroscience, or a closely related area, I would encourage you to carefully review the information provided below before you apply.

The Ph.D. program is a research-intensive program aimed at preparing graduates to research careers in academia or industry. The primary goal of the M.S. program is to prepare graduates for employment in industry. Admission to Ph.D. programs is extremely competitive. For example, the Computer Science graduate program accepts approximately 10 new students from over 500 or more applicants each year. All of our Ph.D. students who do not have their own sources of support receive financial support in the form of a fellowship, a graduate research assistantship, or a graduate teaching assistantship (more on this later). M.S. students typically receive no financial support from the department although many often find part-time employment on campus.

Given the large number of requests for information, my colleagues and I are unable to individually respond to email messages asking for routine information about the application process, application status, etc. from prospective students who wish to join my research group. Such information can be found on the respective graduate program web pages.

Prospective applicants can review information about current research projects, current students, and graduate alumni of our laboratory on our web page. Summaries of current research projects as well as representative publications can be found there.

I am primarily interested in exceptional Ph.D. students with diverse backgrounds (ranging from very theoretical to very experimental, highly focused within Computer Science to highly interdisciplinary e.g., spanning Computer Science and biology) whose research interests match the research foci of our lab. Occasionally, I accept highly qualified M.S. students and undergraduates interested in research.

Students in my group benefit from strong mentoring and close interaction on a daily basis within a collaborative research environment that is tailored to prepare each student for a productive and rewarding research career. Research-based training in our graduate programs in general, and my research group in particular, emphasizes: identification of fundamental research problems, development of creative and innovative solutions, dissemination of research results to the community through publication in top peer-reviewed journals and conferences, and through release of open-source software tools that demonstrate effective solutions to open research problems. In addition to providing a strong technical skills in the relevant research area(s), my group also fosters the development of strong writing and presentation skills.

Graduate students who join my lab typically have a broad-based training in Computer Science, or a closely related discipline. Students interested in pursuing research in Bioinformatics and Computational Biology typically have, in addition to training in Computer Science, some background in biological sciences. Students with primary background in mathematics, statistics, physics, cognitive science or engineering, with some exposure to Computer Science. My students' interests, like the research foci of my lab, span information processing models of intelligent behavior (including learning, perception, multi-agent interaction, algorithms and software for scientific discovery (e.g., in data-driven analysis and prediction of macromolecular sequence-structure-function relationships, and macromolecular interaction networks and pathways), and formulation and solution of machine learning problems motivated by applications in bioinformatics, cheminformatics, and security informatics. Students in the lab enjoy close interaction with each other through research seminars and research collaborations.

Our group takes a problem-centered approach to research. In addition to all the usual requirements for successful research, this calls for a willingness to acquire, adapt, develop, and apply techniques and tools from areas that lie outside the traditional boundaries of the discipline (e.g., Computer Science) or a subdiscipline (e.g., Machine Learning) when necessary to solve a research problem. Fundamental scientific questions (e.g., what is the algorithmic basis of cumulative multi-task learning?) or important practical problems (how do we extract, assimilate, and use information from heterogeneous, distributed, autonomous data and knowledge sources to facilitate collaborative scientific discovery in biology?) drive our research.

All of my former Ph.D. students have found tenure-track faculty positions or research and development positions in industry. M.S. graduates typically seek employment in industry. Undergraduates who have worked in my lab often pursue graduate study at universities with strong programs in Artificial Intelligence or a related area (e.g., Computational Biology).

I seldom offer research assistantships to new students before their arrival on campus. In order to be considered for a research assistantship in my lab, the student must have taken a course or two from me, or participated in research seminars that I run, and interacted with my research group. This helps ensure mutual compatibility in terms of research interests, work habits, and other intangible factors that contribute to the success of a student-mentor relationship. However, once in a while, I have been known to bend this rule in the case of exceptional students with a track record in research.

Admission to graduate programs in Computer Science, Bioinformatics and Computational Biology, and Neuroscience are based primarily on merit. Graduate assistantships or fellowships are awarded to most of our top Ph.D. applicants. If you are applying to any of these programs, and have an interest in joining my lab, please be sure to mention it in your statement of objectives along with a brief description of your research interests as they relate to the research foci of my lab.

Strong applicants who are U.S. citizens or permanent residents and have an interest in Bioinformatics and Computational Biology might qualify for IGERT fellowships.

As noted earlier, because of resource limitations, we typically are unable to offer graduate assistantships to M.S. students. However, M.S. students are often able to find part-time employment on campus, or in the case of US citizens or permanent residents, fellowships for study in specific areas (e.g., security informatics).

Good luck with the application process. Please consult the respective graduate program web pages for information on admissions criteria, application process, sources of financial support - including graduate assistantships and fellowships, and other relevant information. You might also find it useful to check out my collection of pointers to information for prospective and current graduate students.

I welcome inquiries about research opportunities in the Artificial Intelligence Research Laboratory from Ph.D. students who have been accepted into our graduate program.

Best Wishes,

Vasant Honavar
Professor
Director, Center for Computational Intelligence, Learning, and Discovery
Director, Artificial Intelligence Research Laboratory
Professor of Computer Science and of Bioinformatics and Computational Biology.
211 Atanasoff Hall
Iowa State University
Ames, IA 50011-1040

honavar@cs.iastate.edu
voice: 515 294 1098
fax: 515 294 0258