Vishwaas Narasinh

1. Construction equipment demand forecasting, time series modelling with FB Prophet deployment, and delivering business value 2. Wind turbine power loss modelling, analysis, and optimal control system recommendation using SCADA data and gearbox degradation prediction using advanced statistical and forecasting techniques 4. Context completion and error code to issue mapping with sentence similarity and orchestration with LLM for manufacturing process fault tree analysis deployed on AWS and dockers

1. Leading a team of 3 members on Data to Text to convert weather tabular data to natural text based on user intent 3. Implemented an edge device compatible co-reference resolution in Tensorflow. 4. LSTM and attention based Information extraction, language translation, spelling correction, classification on Korean data to classify. 5. Closely working with the research scientists and linguists from leading universities, 3rd party companies and annotators in the domain.

1. Developed Remaining Useful Life prediction for Lithium Ion batteries based on Auto-Encoder DNN 2. Developed a next module recommendation based on the current state of the user defined workflow for Autosar configuration using RNN. This feature designed in Java and JavaFx is a USP and was well received

Bengaluru Area, India • Reduced Data consumption by Implementing Huffman encoding algorithm for TCP Transmission in C# • Implemented applications using .NET WPF, and used JSON formats to exchange data with REST webservices • Developed parts of the tool used to control light segments

• Image and video matching and comparisons in Java • Combined SIFT algorithm in OpenCV and correlation techniques to achieve better pattern matching

Statistical Learning, Structuring & Visualizing Analytics, Big Data on Hadoop, Spark, Real time, Machine learning – Supervised, Unsupervised, , Recommendation Systems, Graphical Models & Networks

Java , Assembly programming, Computer networks, microcontrollers, Linear algebra, Calculus, Complex analysis, Variational principles, probability theory, Statistics