Apurva Narayan

Assistant Professor

Computer Science, Data Science
Other Titles: Associate Member, Mechanical Engineering
Office: SCI 110
Phone: 250.807.8272
Email: apurva.narayan@ubc.ca

Graduate student supervisor



Research Summary

Artificial intelligence/machine learning with emphasis on explainable AI/ML and quantum machine learning; data mining; data analytics, safety and security of cyber physical systems; software engineering; graph theoretic analysis of complex systems; decision making under uncertainty.

Courses & Teaching

Machine learning; data structures; data mining and analytics; software engineering.

Biography

Dr. Apurva Narayan obtained his Ph.D. from the Department of Systems Design Engineering, University of Waterloo and his Bachelor’s degree in Electrical Engineering from Dayalbagh Educational Institute in 2015 and 2008 respectively. His PhD thesis was an archetype of a holistic systems approach for modeling and designing engineering systems under uncertainty. Dr. Narayan was a NSERC post-doctoral fellow with the Real-Time Embedded Systems Group in the Department of Electrical and Computer Engineering at the University of Waterloo.

Dr. Narayan’s research investigates artificial intelligence/machine learning with emphasis on explainable AI/ML and quantum machine learning, data mining, data analytics, safety and security of cyber physical systems, software engineering, graph theoretic analysis of complex systems, and decision-making under uncertainty. He has authored and co-authored more than 20 peer-reviewed publications in top-tier ACM/IEEE conferences and journals.

Dr. Narayan’s current research focuses on data mining, data analytics, and machine learning in context of safety, security and understanding complex Cyber Physical Systems. He is currently interested in developing models for reverse engineering complex software systems. He is also interested in developing interpretable/explainable machine learning models. These models could be used for anomaly detection, specification mining, cyber-physical system security, and other applications.

Websites

www.anarayan.com

Degrees

PhD, University of Waterloo

Research Interests & Projects

Dr. Narayan’s research interests include artificial intelligence/machine learning with emphasis on explainable AI/ML and quantum machine learning, data mining, data analytics, safety and security of cyber physical systems, software engineering, graph theoretic analysis of complex systems, and decision-making under uncertainty.

Selected Publications & Presentations

D. Bhandari, S. Paul and A. Narayan., 2019. Multimodal Data Fusion and Prediction of Emotional Dimensions Using Deep Neural Network. In Computational Intelligence: Theories, Applications and Future Directions-Volume II (pp. 215-228). Springer, Singapore.

A. Narayan, D. P. Srivastava, V. Sahni, P. S. Satsangi, “Implementation and Simulation Studies of the Multi-Particle Quantum Teleportation Model”, 22nd International Conference on Towards a Science of Consciousness, East-West Forum, April 2 – 7, 2018, Tucson, Arizona USA [PDF]

A. Narayan. and Roe, P.H.N., 2018. Learning Graph Dynamics using Deep Neural Networks. IFAC-PapersOnLine51(2), pp.433-438.

A. Narayan, G. Cutulenco, Y. Joshi, and S. Fischmeister. “Mining Timed Regular Specifications from System Traces”. ACM Trans. Embed. Comput. Syst. 17, 2, Article 46 (January 2018), 21 pages. DOI: https://doi.org/10.1145/3147660

A. Narayan, N. Bennan, and S. Fischmeister, “Mining Properties using Nested Word Automaton in System Traces”, The Sixth International Workshop on Software Mining (SoftwareMining-2017) at the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017), October 30 – November 3, 2017, Urbana-Champaign, IL, USA [PDF]

L. Schmidt, A. Narayan, S. Fischmeister, “TREM: A Tool for Mining Timed Regular Specifications from System Traces”, 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017), October 30 – November 3, 2017, Urbana-Champaign, IL, USA [PDF]

A. Narayan and Keith W. Hipel, “Deep Learning for Short Term Electric Load Forecasting”, 2017, IEEE International Conference on Systems, Man, and Cybernetics, Banff, Canada, Oct 5-8, 2017 [PDF]

A. Narayan; Ponnambalam, K.; Pagsuyoin, S.A. Spatial Dependence Modeling of Wind Resource under Uncertainty Using C-Vine Copulas and Its Impact on Solar-Wind Energy Co-Generation. Preprints 2017, 2017090053 (doi: 10.20944/preprints201709.0053.v1) [PDF]

U. Mukherjee, A. Maroufmashat, A. Narayan, A. Elkamel, and M. Fowler, “A Stochastic Programming Approach for the Planning and Operation of a Power to Gas Energy Hub with Multiple Energy Recovery Pathways,” Energies, vol. 10, no. 7, p. 868, Jun. 2017 [Online]. [PDF]

R. S. Narayan and A. Narayan, “Quantum Information Storage and Processing in Biological Molecules”, 21st International Conference on Towards a Science of Consciousness, June 5 – 10, 2017, San Diego, USA [PDF]

A. Narayan, D. P. Srivastava, V. Sahni, P. S. Satsangi, “Robustness of n-qudit quantum Hopfield network against noise and decoherence”, 21st International Conference on Towards a Science of Consciousness, East-West Forum, June 5 – 10, 2017, San Diego, USA [PDF]

A. Narayan, 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]

A. Narayan, K. Ponnambalam, “Risk-averse stochastic programming approach for microgrid planning under uncertainty”, Renewable Energy, Volume 101, February 2017, Pages 399-408, ISSN 0960-1481, http://dx.doi.org/10.1016/j.renene.2016.08.064 [PDF]

G. Cutulenco, Y. Joshi, A. Narayan, and S. Fischmeister, “TRE Mining using Timed Automaton in System Traces”, The Fifth International Workshop on Software Mining (SoftwareMining-2016) – 31st IEEE/ACM International Conference on Automated Software Engineering, Sep 3 – 7, 2016, Singapore [PDF]

S. Fischmeister, A. Narayan, G. Cutulenco, Y. Joshi, “Mining Timed Regular Expressions”, US Provisional Patent Filed, Application Number: 62437436, December 2016

Selected Grants & Awards

  • Awarded the prestigious Systems Society of India’s Young Scientist Award (under age of 40)
  • MITACS Accelerate Award Sep 2013 – Dec 2013
  • Dr. T.E. Unny Memorial Award, University of Waterloo, 2011 – 2012
  • University of Waterloo Graduate Student Scholarship, 2011
  • Graduate Student Association, University of Waterloo, Travel Grant 2011
  • IEEE Student Travel Grant to IEEE WCCI 2008, Hong Kong
  • Nominated for the Best Teaching Award in the Department of Systems Design Engineering, University of Waterloo for Fall 2016
  • Nominated for the Best Teaching Assistant award twice in the Department of Systems Design Engineering, University of Waterloo

 

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