Naresh Vempala is an Industrial research associate at the SMART Lab, with over 15 years of combined experience in industry and academia. He works on industry-academia collaborative projects. His work involves conducting applied research in the lab and translating that into innovative product development for WaveDNA, a music software company. He has been developing experimental protocols and algorithms to cognitively inform and improve WaveDNA’s framework. His research involves computational modelling and behavioural approaches, and includes music emotion prediction, melodic similarity perception, melody recognition, and musical creativity. Naresh is also the co-founder and chief organizer of CogMIR, a society with annual seminars on cognitively based music informatics. Naresh completed his Ph.D in Cognitive Science from the Institute of Cognitive Science at the University of Louisiana at Lafayette.

For more information about Naresh and his research, please visit his personal website here.

List of Publications:

Russo, F. A., Vempala, N. N., & Sandstrom, G. M. (2013). Predicting musically induced emotions from physiological inputs: linear and neural network models. Frontiers in Psychology, 4, 468.

Vempala, N. N., & Russo, F. A. (2013). Exploring cognitivist and emotivist positions of musical emotion using neural network models. Proceedings of the 12th International Conference on Cognitive Modeling (ICCM), Ottawa, ON, Canada, July 11-14.

Vempala, N. N., & Russo, F. A. (2012). Predicting emotion from music audio features using neural networks. Proceedings of the 9th International Symposium on Computer Music Modeling and Retrieval (CMMR), Lecture Notes in Computer Science, London, UK, June 19-22.

Vempala, N. N., & Maida, A. S. (2011). Effects of memory size on melody recognition in a simulation of cohort theory. Cognitive Systems Research, 12, 66-78.

Vempala, N. N., & Maida, A. S. (2009). Modeling melody recognition using a sequence recognition neural network with meta-level processes. Proceedings of the International Joint Conference on Neural Networks (IJCNN), Atlanta, GA, June 14-19, 3204-3211.

Vempala, N., & Dasgupta, S. (2007). A computational model of the music of Stevie Ray Vaughan. Proceedings of the Sixth ACM SIGCHI conference on Creativity and Cognition, 203-212.