Abhilash Yelahanka Ramanjaneya

•Knowledge inIndustry 4.0, edge devices and cloud infrastructure. •Automatic separation of used tools on sensor data based on different features such as Dynamic time wrapping,Standard deviation etc. •Anomaly/Outlier detection of sensor data collected from industrial machinery. •OneClass SVM’s , Auto encoders, K-means to classify the data and Training data onMicrosoft Azure. •libraries used :Matplotlib, NumPy, Scipy, Pandas, ScikitLearn etc.

TOOLS: DOORS for Requirements ,RQM for Test Specification. Specifying system level test cases for level 3 autonomous testing. Testing features like ACC, AEB, TSR based on System Requirements. Creating python scripts for web browser automation. libraries used :Selenium, urllib, Beautiful Soup, Tkinter.

Building convolutional neural network models. Semantic segmentation of image datasets. Tensorflow, Keras, NumPY, OpenCV.

Java Implementation of MapReduce Frameworks. Documentation of the project.

Peer-to-Peer networks, communication networks, Quality of services, Formal Methods, Ubiquitous Computing (TK1- Distributed system and algorithms, TK3- ubiquitous or mobile computing), Parallel programming (Large Scale parallel computing), Software engineering for Multicore systems)

Programming languages (Java and J2EE, Data Structures with c, Programming the web, Object oriented programming with c++), Communication networks 1 & 2, Database managements systems, Storage Area Networks, Software Engineering, Software Testing.