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Faults Diagnostic Sensors


Term:

IAP and Spring

Department:

2: Mechanical Engineering

Faculty Supervisor:

Kamal Youcef Toumi

Faculty email:

youcef@mit.edu

Apply by:

01/15/2020

Contact:

Ali Alshehri: ashehri@mit.edu

Project Description

Candidates required for Two roles: a) Machine Learning & Data Analytics & b) IoT- based Instrumentation Mechatronics Research Lab (MRL) is looking for UROP candidates with strong skills and/or interest in a) Machine Learning & data analytics and b) IoT-based instrumentation. This project aims to give us insights on diagnostics and prognostic of various industrial manufacturing systems.

Pre-requisites

Machine learning candidates will help us analyze and classify information hidden in vast amounts of data collected from multiple sensors such as strain gauges, radar and embedded magnet. The primary focus will be in applying deep learning techniques, doing statistical analysis, and building prognostic systems. The candidate will have the liberty to develop what is seen the best regarding the creation and analysis of the neural network models. We expect well explained results and metrics to enable the research team to solve the problem and provide product intelligence. A strong familiarity with programming in Python and usage of TensorFlow deep learning tools is mandatory. Also, the project requires another set of skills in the instrumentation side where an IoT communication interface need to be developed between users and hardware sensing components. Candidates must have a good experience in Python and microcontrollers programming. UROP candidates are expected to gain various technical knowledge & skills in different domains such as mechanical engineering and electrical sensors with projection on real industrial applications. The project will give candidates good opportunities and real potential for publications and patents. This role involves regular communication meetings with project members and principle investigator on progress and risks.