| home |
| research |
| publications |
| courses |
| funding |
| personal |
| bic research group |
| is&r focus group |
| eece department |
| kansas state university |
| related links |
This graduate research assistantship position at Kansas State University involves a variety of research and development activities leading to a Ph.D. in Electrical Engineering. The candidate will work in close collaboration with the following faculty investigators, Profs. Noel Schulz, Sanjoy Das, Caterina Scoglio, and Bala Natarajan, as well as other graduate and undergraduate students. Key Responsibilities Necessary Qualifications Preferred Qualifications Experience with some of the following: (1) computational intelligence and/or evolutionary algorithms, (2) power systems modeling, (3) Matlab programming, and (4) previous publication record.Compensation The position is for 20 hours/week at the standard departmental rate for Ph.D. students, 12 months for an initial period of three years. Tuition fees will be reimbursed for up to 9 credit hours per semester during the Spring and Fall semesters.Starting Date Summer semester, 2010 or until filled.Application Procedure Interested applicants should send a resume preferably in pdf format, including education, employment, publications, relevant coursework, GRE and TOEFL scores, and a list of three references, including email and phone numbers.A separate application for admission into the graduate program at KSU is required. Check here for details. Please send applications electronically to: sdasATksuDOTedu and to onrpositionsdasATgmailDOTcom with ONR Project Ph.D. Application in the heading. Applications will be accepted until the position is filled. For full consideration apply before Jan 15, 2010. Project Description The two objectives for this research work are (1) development of initial configurations for power system and sensor placement as well as various reconfiguration strategies within a unified design for reconfigurability framework and (2) centralized and decentralized implementation of the optimal reconfiguration strategies developed in the first objective.One of the core components of the proposed research is the development of multi-objective genetic and hybrid algorithms for novel tasks in ship reconfiguration. The use of such algorithms in this application domain and the use of look up tables for further processing/rapid decision making are features that would be of interest in multi-objective optimization. The look up tables can be obtained from the optimization algorithms in two ways possible ways, (1) explicit use of Pareto front solutions and (2) ant colony based pheromones. Through these computational intelligence methods, the collaborative research team will develop a knowledge base related for the integrated MVDC shipboard power system to help in both the design and operational phases. All algorithms will be tested and integrated with MVDC test systems. This integrated approach will demonstrate that the systems can be combined to develop comprehensive optimization schemes that incorporate many objectives representing the diverse missions for tomorrow's navy.
Overall, it is expected that the proposed research would be beneficial to the
evolutionary computation, computational intelligence and power
systems communities. |