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Note to Prospective Students
Pennsylvania State University offers outstanding research and graduate training opportunities in Artificial Intelligence, Machine Learning, Big Data Analytics, Bioinformatics, Neuroscience and related areas through several graduate programs including:
-
PhD programs in:
and
- Masters Programs in:
The Artificial Intelligence Research Laboratory
welcomes prospective graduate students from around the world with an interest in pursuing research in the lab to apply for admission to a graduate program at Pennsylvania 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 me 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 Pennsylvania State University with the goal of pursuing research in Artificial Intelligence, Bioinformatics and Computational Systems Biology, Machine Learning, Data Mining, Big Data Analytics, Social Informatics, 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 Information Sciences and Technology graduate program accepts
approximately 10-15 new students from among hundreds of 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., in Bioinformatics, Health Informatics, and Social Informatics) 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, Informatics,
or, occasionally, primary training in mathematics, engineering, statistics, physics, or related discipline with some exposure to Computer Science. Students interested in pursuing research in
Bioinformatics typically have, in addition to training in Computer Science,
some background in biological sciences.
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 Information Sciences and Technology, Bioinformatics and Genomics,
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 Genomics
might qualify for graduate traineeships in Computation, Bioinformatics and Statistics in Biomedical Data Sciences, or Clinical and Translational Research funded by the National Institutes of Health.
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.
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 prospective or current graduate students at the Pennsylvania State University.
Best Wishes,
Vasant Honavar
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