Veerendra C Angadi

a Research Fellow in the Systems Engineering Research Group (SERG) in Brunel University,UK.

He is currently working on H2020 FoF Z-BRE4K project to investigate and predict the sudden breakdowns in the manufacturing machines by incorporating artificial intelligence in the manufacturing process.

Industrial IoT - Statistical inferences, Machine learning, data analytics, data mining in Industry 4.0, Image/Video processing, Computer Vision algorithms, Spectral analysis in Microscopy and related domain.
He is also involved in Building (MATLAB) apps for interactive technical tasks.

His expertise is on Industrial IoT - Statistical inferences, Machine learning, data analytics, data mining in Industry 4.0, Image/Video processing, Computer Vision algorithms, Spectral analysis in Microscopy and related domain.
He is also involved in Building (MATLAB) apps for interactive technical tasks.
He has interests in working and designing with microcontrollers such as Arduino, Raspberry Pie, MSP430, eZ430-RF2500 etc.

Journal Publications:

• V C Angadi, F Benz, I Tischer, K Thonke, T Aoki and T Walther: Evidence of terbium and oxygen co-segregation in annealed AlN:Tb. Applied Physics Letters, Vol - 110, No - 22, pp 222102, May 2017. DOI: 10.1063/1.4984237.
• T Walther, X Wang, V C Angadi, P Ruterana, P Longo and T Aoki: Study of phase separation in an InGaN alloy by electron energy loss spectroscopy in an aberration corrected monochromated scanning transmission electron microscope. Journal of Material Research, pp 1 - 13, December 2016. DOI: 10.1557/jmr.2016.447.
• V C Angadi, C Abhayaratne and T Walther: Automated background subtraction technique for electron energy-loss spectroscopy and application to semiconductor heterostructures. Journal of Microscopy, Vol - 262, Issue - 2, pp 129 - 188, May 2016. DOI: 10.1111/jmi.12397.
• M M Dixit, P K Kulkarni, P S Somasagar and V C Angadi: Variable scaling factor based invisible image watermarking using hybrid DWT - SVD compression - Decompression technique. 2012 IEEE SCEECS, pp 1 - 4, March 2012. DOI: 10.1109/SCEECS.2012.6184847.

Conferences Proceedings:

• Z Huang, V C Angadi, M Danishvar, A Mousavi, M Li: Zero Defect Manufacturing of Microsemiconductors - An Application of Machine Learning and Artificial Intelligence. ICSAI - 2018, Nanging, China; November 2018. DOI: 10.1109/ICSAI.2018.8599292
• V C Angadi, C Abhayaratne, T Walther: Determination of bandgap onset by Richardson-Lucy deconvolution of electron energy-loss spectra (EELS): 1D EELS vs 2D EEL spectrum images. MSM - XX, Oxford, UK; April 2017.
• V C Angadi, T Walther: Influence of background subtraction and deconvolution on calculation of EELS core-loss intensities. EMC 2016, Lyon, France; August 2016. DOI: 10.1002/9783527808465.EMC2016.6237.
• V C Angadi, T Walther: Systematic study of background subtraction technique for EELS. EMAG 2016, Durham, UK; April 2016. DOI: 10.13140/RG.2.1.4020.6320.
• V C Angadi, C Abhayaratne, T Walther: Development of automated background subtraction for electron energy-loss spectroscopy. MMC - EMAG 2015, Manchester, UK; July 2015. DOI: 10.13140/RG.2.1.2972.0566.
• V C Angadi, T Walther: Core-Loss Edge Detection and Background Subtraction Techniques for EELS. HSI 2014, Coventry, UK; October 2014. DOI: 10.13140/2.1.4887.4565.
• M M Dixit, P K Kulkarni, P S Somasagar and V C Angadi: Computational Analysis of Variable Scaling Factor based Invisible Image Watermarking using Hybrid SVD - DCT Compression - Decompression Technique. IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Levengipuram, Kanyakumari, India; December 2011.