Graduate Student Research Grants
The IEEE Computational Intelligence Society is inviting applications for a competition for additional funding opportunity for 2019.
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:
- cover page with the applicant's address, student status, IEEE number, expected graduation date, host institution (if applicable).
- detailed explanation of the research to be conducted with the support from the scholarship (10pt font, 3 page maximum)
- references related to the proposed research (10pt font, 1 page maximum)
- a timeline of tasks required to complete research goals
- 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).
- your resume (1 page maximum). Please provide your IEEE member number
- 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.
Evaluation and selection will be based on:
- Merit of the proposed research
- Originality of the research
- Qualification and past performance of the applicant
- Supporting references
- Reasonableness of budget
After the end of the sponsored project:
- 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.
- Upon certification by the student's research sponsor, the student will receive funds as reimbursements for his/her expenses.
- 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: March 31, 2019
Notification of Acceptance: April 15, 2019
Work must be completed and funds must be spent by: November 30, 2019
Graduate Student Research Grants Committee Chair
Manchester Metropolitan University
Graduate Student Research Grants Committee Member
South Dakota State University
Engineering and Computer Science
Instituto Superior Técnico
2019 Grant Recipients
- Xue Jiang for the project "Active Learning and Deep Learning for Adversarial Attacks in EEG-Based Brain-Computer Interfaces"
- Xiaohu Zhou for the project "A Neural-Network-Based Multilayer Learning Framework for Cardiovascular Robots"
- Chandan Kumar Behera for the project "Brain circuits and emotional learning"
- Jinli Yao for the project "An Area-based Similarity Measure for Interval Type-2 Fuzzy Set and Its Application to Multi-attribute Decision Making"
- Artur Luis Fernandes de Souza for the project "Automated Adaptation of Deep Learning Topologies Applied to Serial Crystallography"
2018 Grant Recipients and Final Reports
- Jes´us Guillermo Falc´on-Cardona, "On the Combination of Quality Indicators for Multi-Objective Optimization"
- Yaran Chen, "A temporal-based deep learning method for multiple objects detection in autonomous driving"
- Guoji Fu, "Learning Topological Representation for Networks via Hierarchical Sampling"
- Wenjing Hong, "Large-Scale Multi-Objective Evolutionary Optimization"
2017 Grant Recipients and Final Reports
- Chandranath Adak, "Adaptive Metaheuristic Deep Learning for Study towards Human Cognition using Complex Handwriting Pattern"
- Qichao Zhang, "Event-triggered integral reinforcement learning for nonlinear continuous-time systems"
- Subhashis Banerjee, "Brain Tumor Detection and Classification from Multi-Channel MRIs using Deep Learning and Transfer Learning"
- Saeid Samadidana, "A Distributed Approach to Design Satellite Tracking System"
- Soham Mandal, "Theoretical Analysis of Convergence and Associated Issues in Generative Adversarial Network (GAN) Using Evolutionary Algorithm"
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"
- Mohamed El Yafrani, "A Study of Multi-objectiveness in the Travelling Thief Problem"
2015 Grant Recipients and Final Reports
- Hongwen Ma, "Distributed control of second-order nonlinear time-delayed multiagent systems with disturbance using neural networks"
- Yuanheng Zhu, "Solving Nonlinear Zero-Sum Game with Completely Unknown Dynamics via Iterative Adaptive Dynamic Programming"
- Peng Yang, "Robust Optimization with Multiple Solutions"
- Ehsan Hosseini-Asl, "Part-based Feature Extraction in Deep Learning Models" (report to be posted soon)
- Abhijit Das, "A Semi-supervised Pipelined Deep Learner for an Adaptive and Efficient Biometric System"
2013 Grant Recipients and Final Reports
- Hongliang Li, Chinese Academy of Sciences, "Adaptive Dynamic Programming for Two-Player Zero-Sum Differential Games with Completely Unknown Systems"
- Kanishka Tyagi, Seoul National University, "Applications of Deep Learning Network on Audio and Music Problems"
- Xiaofen Lu, University of Science and Technology of China, Hefei, Anhui, China "Evolutionary Optimization with Hierarchical Surrogates"
2012 Grant Recipients and Final Reports
- Dawei He, Georgia Institute of Technology, USA: Short-Term Wind Power Forecasting Based on a New Feature Selection Technology and Support Vector Machine
- Rui Jorge Almeida, Erasmus University Rotterdam, The Netherlands: Linguistic Summaries of Intensive Care Unit Septic Shock Patients
- David Zhou, Carnegie Mellon University, "Computing a percolation model of information transmission for modeling general anesthesia"
2011 Grant Recipients and Final Reports
- Minlong Li, University of Science and Technology, China: Selective Further Learning for Class Imbalanced Incremental Learning
- Mostafa M. Ellabaan, Nanyang Technological University,Singapore: A Computational Intelligence Methodology for Unique, Low-Energy Glutamic Acid Isomers Discovery
- Rafael Falcon, University of Ottawa, Canada: Music-Aware Artificial Fireflies to Sensor Relocation by a Robot Team
2010 Grant Recipients and Final Reports
- Yifeng Li, University of Windsor, Canada: Non-Negative Matrix and Tensor Factorization Methods for Microarray Data Analysis
- Bipul Luitel, Missouri University of Science & Technology, USA: Real-Time Implementation of Cellular Neural Networks for Smart Grid Applications
- Zai Wang, University of Science and Technology of China, China: An Efficient Particle Swarm Optimizer for Multi-level Redundancy Allocation Problem
2009 Grant Recipients and Final Reports
- Yi Mei, University of Science and Technology, China: Decomposition-Based Memetic Algorithm for Multi-Objective Capacitated Arc Routing Problem.
- Joshua Payne, Dartmouth Medical School, USA: Toward computational evolution: Incorporating ecological interactions and conditional dispersal into biologically-inspired algorithms.
- ThanhVu Nguyen, University of New Mexico, USA: A closed-loop repair of software bugs.
- Pinaki Mitra, Missouri University of Science and Technology, USA: Adaptive Critics with Spiking Neural Networks for Applications in Smart Power Grids.
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