Updated News


The paper entitled "Extending the k-means Clustering Algorithm to Improve the Compactness of the Clusters" got accepted for publication in the Journal of Pattern Recognition Research(JPRR).


The paper entitled "Backpropagation Neural Network for Interval Prediction of Three-Phase Ampacity Level in Power Systems" got accepted for publication in the International Journal of Monitoring and Surveillance Technologies Research (IJMSTR)


Professor Lefteri H. Tsoukalas has been invited as keynote speaker in the 28th International Conference on Tools with Artificial Intelligence


Sophomore student Sophie Weidenbenner joins AISL to work in nonproliferation policy


ME undergraduate student Sotirios Dassyras joins AISL group to work in Global energy analysis


AISL Director, Prof. Tsoukalas invited as keynote speaker in the 7th International Conference on Information, Intelligent Systems and Applications, Porto Carras, Chalcidiki, July 13-15, 2016


Pola-Lydia Lagari completed her internship at Oak Ridge National Laboratory | ORNL

About Us

Applied Intelligent Systems Laboratory (AISL) is a research unit at Purdue University for theoretical and experimental research on intelligent systems and their applications on Nuclear Science and Technology. AISL's research also aims at promoting the various aspects of smart energy technologies including the "Energy Internet". Members of the AISL focus on interdisciplinary research dedicated to advancing intelligent problem solving techniques to modeling of complex systems, with emphasis on nuclear applications. Among others, the techniques include neural networks, fuzzy logic, genetic algorithms, expert systems and evolutionary computing. AISL is part of the School of Nuclear Engineering and occupies laboratory space in the Nuclear Engineering Building and experimental facilities located in the Aviation Technology Center at Purdue University.)

Mission and Vision

Application of artificial intelligent methods to real-world engineering systems
Improvement of artificial intelligence methods through engineering applications
Enhancement of understanding of the human-machine relation