Vinod Alase

• Requirement Analysis, Design, Development and Implementation of application • Development of User-friendly HMI web-based application for additive manufacturing tools. • Development of HMI simulation tool for MPURE using Kivy and Python. • Very strong knowledge in metal Additive manufacturing sector. • Very good hands-on experience in usage of development tools such as ASANA, MIRO, Kivy. • Providing end-to-end solution for the user in additive manufacturing sector • Worked in start-up with Agile mindset

Topic: Authentication Using Facial Recognition for Next Generation Mobility in IoT Environment • Development of Face recognition algorithm using Image Processing/Computer Vision(using OpenCV ) and Deep Learning techniques • The Face recognition system is built on service-oriented architecture: it’s Industry 4.0 application (IoT) • The algorithm is built with of different artificial intelligent classifiers, clustering, deep learning methods and libraries like KNN, SVM, TensorFlow, Scikit-learn, CNN, GAN.

Topic: Object Recognition with Tensorflow and NCS Movidius stick on Raspberry Pi • Evaluation of Different Object detection pre-existing algorithms • Development of Object detection algorithm using Mobile SSD deep neural network (CNN) with Tensorflow. • The Object detection for ADAS application is achieved for 20 classes with higher accuracy • Evaluation and comparison of results with various models such as YOLO 2, Faster R-CNN and Haar-Cascade

• Responsible for Design and Development of Embedded software modules and algorithms for various industry-applications. • Responsible for Requirement Analysis, Concept design, and testing of software modules • Integration of software and hardware modules at application level • Knowledge of Agile methodology and V-Model • Usage of vector software tools to develop • Very good hands-on experience in delivering quality software modules • Responsible to lead small QA team of 5 members

Embedded Systems, system on chip and OpenCv.