蜜桃传媒

Senior research associate in System Engineering Research Group at 蜜桃传媒, UK.

Morad currently works on Horizon 2020 Z-Factor which focuses on zero defects in manufacturing systems. He is a member of IET.

Real-Time Systems Modelling and optimisation, Machine Learning, Data Science and Engineering, Software/ Application Design and Development, instrumentation, and process control.

He received his PhD degree from 蜜桃传媒 in 2015. Over the years he has gained industrial experiences in industry and participated in numerous research projects.

Journal:

• Morad Danishvar, Alireza Mousavi, Sebelan Danishvar (2019). The Genomics of Industrial Process through the Qualia of Markovian Behaviour, under review IEEE Transactions on Systems, Man and Cybernetics: Systems.
• Foivos Psarommatis, Morad Danishvar, Ali Mousavi, Dimitris Kiritsis (2019). Cost-Based Optimization of manufacturing Key Performance Indicators for Zero Defect Manufacturing, Under review at International Journal of Production Research.
• Morad Danishvar, Alireza Mousavi, Peter Broomhead (2018). EventiC: A Real-Time Unbiased Event-Based Learning Technique for Complex Systems, 2018 IEEE Transactions on Systems, Man and Cybernetics: Systems.
• Huang, Z., Li, M., Mousavi, A., Danishvar, M., & Wang, Z. (2018). EGEP: An Event Tracker Enhanced Gene Expression Programming for Data-Driven System Engineering Problems. IEEE Transactions on Emerging Topics in Computational Intelligence.

Conferences:

• Fadzil, F.Z.M., Mousavi, A. and Danishvar, M., 2019, January. Simulation of Event-Based Technique for Harmonic Failures. In 2019 IEEE/SICE International Symposium on System Integration (SII) (pp. 66-72). IEEE.
• Huang, Z., Angadi, V. C., Danishvar, M., Mousavi, A., & Li, M. (2018, November). Zero Defect Manufacturing of Micro semiconductors鈥揂n Application of Machine Learning and Artificial Intelligence. In 2018 5th International Conference on Systems and Informatics (ICSAI) (pp. 449-454). IEEE.
• M. Danishvar, V. Vasilaki, Z. Huang, E. Katsou, A. Mousavi (July 2018), Application of Data-Driven methods to Predict N2O Emission in Full-scale WWTPs, IEEE 16TH INTERNATIONAL CONFERENCE OF INDUSTRIAL INFORMATICS INDIN2018.
• V. Vasilaki, M. Danishvar, Z. Huang, A. Mousavi, Katsou, and (May 2017): Application of Event Based Real-Time Analysis for Long-Term N2O Monitoring in Full-Scale WWTPs, Frontiers International Conference on Wastewater Treatment and Modelling FICWTM 2017: Frontiers in Wastewater Treatment and Modelling pp 436-443.
• Morad Danishvar, Alireza Mousavi (2014): EventClustering for improved real-time Input Variable Selection and Data Modelling: 2014 IEEE Multi-conference in Systems and Control (MSC 2014), Antibes, France.