Madhav Mishra
Madhav Mishra

Madhav Mishra

Luleå tekniska universitet
Drift och underhållsteknik
Drift, underhåll och akustik
Institutionen för samhällsbyggnad och naturresurser
F115 Luleå


Currently, Madhav Mishra is a senior researcher at the Division of Operation and Maintenance Engineering, Luleå. He is a visiting researcher at the NASA Ames Research Center, California, USA.

Dr. Madhav Mishra has completed a PhD Degree at the Division of Operation and Maintenance Engineering at Luleå University of Technology in Sweden within the framework of the SKF-University of Technology Center (UTC). His research focus lies to improve the diagnosis and prognosis of the RUL of an asset by the development of hybrid models based on Industrial Artificial Intelligence or Industrial AI, Machine Learning & Deep Learning. He obtained Master degree in Control Systems Engineering with specialisation in Mechatronics from the Netherlands. He worked at Philips Semiconductors/NXP in Nijmegen in the Netherlands as a Senior Design Engineer Mechatronics where he has involved in design and developed of the high speed rotating machine.

Research interests:

  • Industrial Artificial Intelligence or  industrial AI, Machine Learning & Deep Learning
  • Diagnostics, Prognostics, and Health Monitoring
  • Current research includes development of model-based and data-driven diagnostic and prognostic approaches
  • Model-based algorithms for diagnosis and prognosis
  • Bayesian tracking (Kalman filtering, particle filtering)
  • Fusion based algorithms for Prognostics



Artikel i tidskrift

A channel model for power line communication using 4PSK technology for diagnosis: Some lessons learned (2018)

Artikel i tidskrift

Bayesian hierarchical model-based prognostics for lithium-ion batteries (2018)

Mishra. M, Martinsson. J, Rantatalo. M, Goebel. K
Reliability Engineering & System Safety, Vol. 172, s. 25-35
Artikel i tidskrift

Hierarchical model-based prognostics for Li-ion batteries (2018)

Mishra. M, Martinsson. J, Rantatalo. M, Goebel. K

Model-Based Prognostic Approach for Battery Variable Loading Conditions (2017)

Some Accuracy Improved
Mishra. M
Ingår i: Proceedings of the Asia Pacific Conference of  the Prognostics and Health Management Society 2017, s. 147-149, 2017