Nabanita Das
Angestellt, Research Assistant, Fraunhofer IEM
Abschluss: Masters, Universität Paderborn
Reutlingen, Deutschland
Über mich
Computer Engineering graduate with a combined experience of 5 years of software development in the field of Computer Vision and Artificial Intelligence. I have exposure to coding in multiple languages, skills to analyze complex technical information and working with teams from different parts of the world.
Werdegang
Berufserfahrung von Nabanita Das
Data analysis and visualization. Advice customers regarding errors in data collection. Research and development(data-driven) of machine learning algorithms for prediction of wear and tear of tools used in the production system by düspohl Maschinenbau GmbH.
Topic: Prediction of Geometrical Features from technical product specifications Tasks: Data analysis and visualization. Research and development of unsupervised machine learning techniques for data annotation. Research and development of supervised machine learning techniques for classification.
1 Jahr, Apr. 2018 - März 2019
Student Research Assistant
University of Paderborn
Development of a Framework for Heterogeneous High-Performance Image Processing Applications. Modified existing software to correct errors and optimize efficiency.
3 Jahre und 6 Monate, Okt. 2013 - März 2017
Software Developer
Larsen and Toubro
Research and development of Computer Vision algorithms, eg. lane detection, optical character recognition(OCR). Research on machine learning algorithms and implementation of state-of-the-art algorithms. Automation of processes for calibration of Fluke devices. Development of techniques for medical image enhancement for international clients. Customer interaction for requirements analysis
Ausbildung von Nabanita Das
3 Jahre und 10 Monate, Apr. 2017 - Jan. 2021
Computer Engineering
Universität Paderborn
Focus: Signal, Image, and Speech Processing Projects: Real-time 3D object detection and pose estimation, development of stereo camera using webcams, Image classification, Automatic speech recognition (Natural Language Processing), Development of a multi-class classification model with Random Forest, Neural Networks, and SVM. Relevant courses: Statistical signal processing, Statistical machine learning, Digital image processing, Robotics, etc.
Sprachen
Deutsch
Grundlagen
Englisch
Fließend
Hindi
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Assamese
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