IEEE CIS > Educational Activities

Walter Karplus Summer Research Grants

Walter J. Karplus - In Memoriam

The IEEE Computational Intelligence Society (CIS) will fund scholarships for deserving graduate students who need financial support for their research during a summer period. Any student with a meritorious project is invited to apply, but scholarships will be granted only to applicants who are student members of the IEEE at the time of the grant.

Each scholarship may cover expenses connected with, but not limited to:

1. summer support at their home institution for intensive work on a particular project;
2. a visit to another university, institute or research agency for collaboration with an identified researcher in the field of interest of the applicant; or
3. other expenses (such as software) that are justifiable and relevant to the research being conducted.

The field of interest of applicants is open, but should be connected with identifiable component of the CIS (neural networks, fuzzy systems, or evolutionary computation).

The amount of a CIS scholarship varies from $1,000 to $4,000. We expect to award 3-5 scholarships every year. The number of scholarships is dependent on budget approval by CIS ADCOM. Renewals and continuations for a second year of summer support will be considered only if the justification for such a request is sufficiently compelling.

To apply for a CIS scholarship, interested applicants should submit a proposals to the chair of the CIS Education Committee. Your proposal should state the general purpose of your request, and should follow these guidelines:

1. detailed explanation of the research to be conducted with the support from the scholarship (10pt font, 3 page maximum)
2. references related to research (10pt font, 1 page maximum)
3. a timeline of tasks required to complete research goals
4. a fully explanatory budget (1 page maximum)
5. your resume (1 page maximum)
6. 2 reference letters supporting your application (including letters from sponsoring professors, if applicable). These must be included with you application and are not to be received individually
7. you need to be a member of IEEE and the IEEE Computational Intelligence Society (provide IEEE member number).

Note: Reference letters can also be sent directly to the Grant Application System administrator or the Educational Activities Committee Chair in order to submit them without the intermediary of the student. Such letters will then not be viewable by the student.

The deadline for applications is March 15 of each year. All applications MUST BE RECEIVED no later than this date through the Grant Application System. Decisions of the Educational Committee, which will work with the CIS VP for Membership Development and VP for Technical Activities will be announced within 2-3 months of the application deadline. Research grant recipients are required to submit a report to the IEEE CIS Education Committee Chair after they complete the sponsored project.

Evaluation and selection will be based on:

1. Merit of the research to be supported
2. Originality of the research
3. Qualification and past performance
4. Supporting references
5. Reasonableness of budget

On behalf of the IEEE Computational Intelligence Society, we want to extend our congratulations to all of you. The CIS is certain this Walter Karplus Summer Research Program is a great investment in the future of computational intelligence. We regret that we are not able to support all of those who applied this time. We would like to thank all of you for applying to the program, and encourage those who did not succeed this time to apply for future CIS opportunities.

Sincerely,
Education Activities Chair
 

2007 Grant Recipients and Final Reports

• Broderick Crawford, Universidad T'ecnica Federico Santa Mar'ia, Valpara'iso, Chile: Integrating Ant Computing and Constraint Programming
• Maciej Mazurowski, University of Louisville, USA: Computational Intelligence in Patient-Sensitive Medical Decision Systems
• Olga Nechaeva, Novosibirsk State University, Russia: Neural network approach to construction of 3D surface and volume adaptive meshes based on self-organization
• Dongrui Wu, University of Southern California, USA: A Comparative Study of Ranking Methods, Similarity Measures and Uncertainty Measures for Interval Type-2 Fuzzy Sets
• Yusuf Yare, Missouri University of Science and Technology, Rolla USA: Optimal Maintenance Scheduling of Power Systems using an Algorithm Inspired by Swarm Intelligence and Quantum Evolution

2006 Grant Recipients and Final Reports

• Christopher J. Rozell, Rice University at Houston, USA: Dynamic systems for sparse coding
• Mostafa Z. Ali, Wayne State University, USA: Exploring Knowledge and Population Swarms via an Agent-Based Cultural Algorithms Simulation Toolkit (CAT)
• Ting Huang, University of Illinois at Chicago, USA: Neuarl Network Modeling and Feedback Error Learning Control for Automotive Fuel-Injection Sysetms
• Feilong Liu, University of Southern California, USA: An efficient centroid type reduction strategy for general Type-2 fuzzy logic system
• Changbo Yang, Wayne State University, USA: Region-based image annotation using multiple-instance learning
• Wojciech Stach, University of Alberta, Canada: Parallel Genetic Learning of Fuzzy Cognitive Maps
• Tridib K. Das, University of Missouri Rolla, USA: Bio-Inspired Algorithms for the Design of Optimal Controllers for Power System Stabilization

2005 Grant Recipients and Final Reports

• Srinivas Andra, Rensselaer Polytechnic Institute, USA: Combining dichotomizers for MAP field classification
• Andrea Kulakov, Sts Cyril and Methodius University, Macedonia: Efficient data management in wireless sensor networks using artificial neural networks
• Swakshar Ray, University of Missouri-Rolla, USA: Computaional intelligence for large power systems
• Lingfeng Wang, Texas A&M University, USA: Hybrid electric vehicle design based on a multi-objective optimization evolutionary algorithm

2004 Grant Recipients and Final Reports

• Pedro DeLima, Oklahoma State University, USA: Application of adaptive critic designs for fault tolerant control
• Zuwairie Ibrahim, Meiji university, Japan: Towards solving weighted graph problems by direct-proportional length-based DNA computing
• Dragana Jankovic, Technical University of Delft, Netherlands: Moisture transport and drying shrinkage cracking in cement-based materials at early age
• Ivana Ljubic, Technical University of Vienna, Austria: An evolutionary approach to the fractional prize-collecting Steiner tree problem
• Roberto Santiago, Portland State University, USA

2003 Grant Recipients and Final Reports

• Jian-Hung Chen: Theoretical analysis of multi-objective genetic algorithms convergence time, population sizing, and disequilibrium
• Min Chen: Modeling of plasma-enhanced chemical vapor deposition of nano-crystalline silicon carbide films using neural network
• Dan-Marius Dobrea: Bio-psychical and physical fatigue state analysis and assessment
• Timo Horeis: Intrusion detection with neural networks - combination of self-organizing maps and radial basis function networks for human expert integration

2002 Grant Recipients and Final Reports

• Zhe Chen: Proportionate adaptation paradigms and application in network echo cancellation
• Haiming Lu: Dynamic population strategy sssisted particle swarm optimization in multiobjective evolutionary algorithm design

2001 Grant Recipients and Final Reports

• Ivana Ljubic: An evolutionary approach to weighted biconnectivity augmentation problems on graphs
• Phayung Meesad: Quantitative measures of a fuzzy expert system
• Ganesh Kumar Venayagamoorthy: Adaptive critic design based neurocontrollers for turbogenerator control
• Khurram Waheed: Blind source recovery: state space formulations

2000 Grant Recipients and Final Reports

• George Chronis: Spatial relations for mobile agent navigation
• Karen Haines: The functionality of extracellular diffusion in electrical neural processing
• Serdar Iplikci: An improved algorithm for convergence in training feedforward neural networks
• Chung-Chu Leung: The nth-term generalized fuzzy tree algorithm applied in edge detection
• Slawo Wesolkowski: Shading and highlight invariant color image segmentation