Follow: Share:Share

2017 Graduate Student Research Grants – Additional Funding Opportunity for 2017

The IEEE Computational Intelligence Society is inviting applications for a second cycle competition for additional funding opportunity for 2017.

The IEEE Computational Intelligence Society (CIS) funds scholarships for deserving undergraduate, graduate and PhD students who need financial support to carry out their research during an academic break 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 CIS and students at the time the scholarship is awarded.

The primary intent of these scholarships is to cover the expenses related to a visit to another university, institute or research agency for collaboration with an identified researcher in the field of interest of the applicant. In certain cases, the scholarship may also be used to cover expenses related to support the student at their home institution for intensive work on a particular project, if – due to extenuating circumstances – such work cannot be continued as scheduled during the regular academic semester.

Funds cannot be used for stipend, salary, conference travel or buying computers or other equipment. Funds can be used to cover travel expenses as well as certain living expenses (such as housing).

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 dependents on the budget approved by CIS ADCOM. Renewals and continuations for a second year 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 proposal to the CIS Graduate Student Research Grants Sub-Committee. Your proposal, to be submitted as a single PDF file, should state the general purpose of your request, and should including the following:

  1. cover page with the applicant's address, student status, IEEE number, expected graduation date, host institution (if applicable).
  2. detailed explanation of the research to be conducted with the support from the scholarship (10pt font, 3 page maximum)
  3. references related to the proposed research (10pt font, 1 page maximum)
  4. a timeline of tasks required to complete research goals
  5. a fully explanatory and detailed budget with individual line items along with the justification of the requested item and amount (1 page maximum). If the work is to be conducted at home institution, an explanation why additional funds are needed to continue the work during the break, and why the work cannot be done during the academic semester, or simply cannot continue as normally progressing during the academic semester (additional 1 page maximum).
  6. your resume (1 page maximum). Please provide your IEEE member number
  7. 2 reference letters supporting your application (including letters from sponsoring professors, if applicable). These must be included with your application and are not to be received individually

Information in the file must follow the above presentation order.

Only if requested by the referee, reference letters can also be sent directly to the Graduate Student Research Grants Sub-Committee Chair in order to submit them without the intermediary of the student. Such letters will then not be viewable by the student.

All applications MUST BE RECEIVED no later than the deadline via email to the Graduate Student Research Grants Sub-Committee Chair.

Evaluation and selection will be based on:

  1. Merit of the proposed research
  2. Originality of the research
  3. Qualification and past performance of the applicant
  4. Supporting references
  5. Reasonableness of budget

After the end of the sponsored project:

  1. Student's research sponsor needs to provide a certification to the sub-committee chair stating that the student has performed satisfactory research work as proposed and has met the goals set forth in the proposal.
  2. Upon certification by the student's research sponsor, the student will receive funds as reimbursements for his/her expenses.
  3. Final technical report in the format of a major CIS conference publication are due on December 1 of the award year.

Note the following dates:

Deadline for submission of applications: April 30, 2017

Notification of Acceptance: May 15, 2017

Work must be completed and funds must be spent by: December 15, 2017




2016 Grant Recipients

  • Rong Xiao, "Spiking Neural Networks for Object Recognition by Exploiting Precise Timing Neural Information Encoding"
  • Kalyan Shankar Bhattacharjee, "Adaptive Reference Direction Control for Decomposition Based Evolutionary Algorithms"
  • Vikram Shenoy Handiru, "Supervised learning approach for cortical source space feature extraction and causal inference of cortical networks for applications in stroke rehabilitation"


2015 Grant Recipients and Final Reports


2013 Grant Recipients and Final Reports


2012 Grant Recipients and Final Reports


2011 Grant Recipients and Final Reports


2010 Grant Recipients and Final Reports


2009 Grant Recipients and Final Reports


2008 Grant Recipients and Final Reports

  • Andrea Arcuri, University of Birmingham, UK: Automatic Repair of Buggy Software
  • Anna V. Kononova, University of Leeds, UK: Differential Evolution with Scale Factor Local Search for Large Scale Problems
  • Yanchao Wang, Jilin University, China: Research on the Evolutionary Prediction of Very Complex Crystal Structures
  • Yu Wang, University of Science and Technology, China: Investigation on Large Scale Global Optimization with Noise-Induced


2007 Grant Recipients and Final Reports

  • Broderick Crawford, Universidad T'ecnica Federico Santa Maria, 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, 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 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