Created a tool for text-based programming of software for e-Textiles.

A smart hip bandage for preventing hip dislocation after hip replacement surgery.

Redesigned, added unit tests and evaluated the Interactex development environment for eTextiles.

Development of the KneeHapp bandage. See: http://dl.acm.org/citation.cfm?id=2800909

Identified patterns of movements that are usually performed by patients in the field of rehabilitation and described ways to realize them using wearables.

Identified different designs to make an e-Textile provide output to a user (wearer or other individuals around the wearer) and integrated it in Interactex.

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Needless to say that, for any act of team organisation like task management the importance of having an overview of the activities and the strength of the team members in different fields is of no doubt. As elements of task management, the features of task board management and assignee recommender cover the former and the latter respectively. Through task board management, the organiser tracks the sequence of the tasks and the arrangement of the assigned tasks, so he or she could minimize the idle status of the team. To this end, the task should be distributed optimally among the developers based on their level of desirability. This implicitly brings the necessity of a mechanism to evaluate their desirability quantitatively which is normally assessed intuitively and qualitatively. As a result, through more rational assignment of the tasks among the developers based on their quantitative desirability, more tasks would be accomplished in the same specific sprint. Therefore, the effectiveness of the team would be improved. In this thesis we develop a light weight assignee recommendation and association algorithm, which is integrated within an android application for task management

A new approach to create datasets for classification of different nuts, considering the inner threads and camera angle. The challenge is to preserve the size information of the small part, using a fixed camera and fixed distance to that, while pointing out the camera lens to the nut in specific angles that it can capture its threads, length and overall shape. Using this setup and also other pictures, you will train a model with convolutional neural network to classify different nuts.

Studying methods to create datasets from 3D models and use them in training a model for small parts classifier. This method will be compared with the normal manually photographing approach in terms of usability of dataset creation and performance of the classifiers.

Creating a model to detect damaged small parts (screws, bolts, nuts, pins, washers, etc.) in overhauling industrial machineries, using deep learning and convolutinal neural networks

Implementing a Speech Recognition System, which can learn from the user input. The idea is to build an application to be able to monitor the system performance and give feedback regarding the recognized phrases. The samples, together with the corrected labels, will be used to retrain the model to improve the performance.