Finished (Postdoc), 2018
 

Apurva NarayanApurva Narayan got his Bachelors in Engineering from the Dayalbagh Educational Institute, Agra, India. He finished his PhD in Systems Design Engineering department at the University of Waterloo. His research interests are in Artificial Intelligence; Machine Learning & Deep Learning; Stochastic Optimization; Multidisciplinary Design Optimization under Uncertainty and the modeling, design and evaluation of safety-critical real time systems. 

For additional information see the external CV page.

Affiliation: 
University of Waterloo

Publications with this group

2019

Sucholutsky, I., A. Narayan, M. Schonlau, and S. Fischmeister, "Deep Learning for System Trace Restoration", International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 2019. PDF icon [pdf] (198.57 KB)

2018

Narayan, A., G. Cutulenco, Y. Joshi, and S. Fischmeister, "Mining Timed Regular Specifications from System Traces", ACM Transactions on Embedded Computing Systems, vol. 17, issue 2, 2018. PDF icon [paper] (611.3 KB)

2017

Narayan, A., N. Benann, and S. Fischmeister, "Mining Specifications using Nested Words", Proceedings of the 6th International Workshop on Software Mining, Urbana-Champaign, USA, 2017. PDF icon [paper] (398.65 KB)
Narayan, A., S. Kauffman, J. Morgan, G. Martin Tchamgoue, Y. Joshi, S. Fischmeister, and C. Hobbs, "System Call Logs with Natural Random Faults: Experimental Design and Application", Silicon Errors in Logic -- System Effects (SELSE), Boston, USA, 2017. PDF icon [pdf] (251.78 KB)
Schmidt, L., A. Narayan, and S. Fischmeister, "TREM: A Tool for Mining Timed Regular Specifications from System Traces", Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering, Urbana-Champaign, USA, 2017. PDF icon [paper] (409.66 KB)

2016

Cutulenco, G., Y. Joshi, A. Narayan, and S. Fischmeister, "Mining Timed Regular Expressions from System Traces", Proceedings of the 5th International Workshop on Software Mining, Singapore, pp. 3 - 10, 2016. PDF icon [paper] (417.1 KB)