In this research, we propose a model learning documents to fixed-length embedding vector space. This is meaningful, because in vector space, we can find similar documents or measure the relations between documents by simple linear algebra calculation. One of state-of-the-art methods is to apply deep Convolutional Neural Network on language sequences and thus learn different […]

The proposed research project aims to increase the accuracy of a model used to predict future glucose levels 1 hour ahead of time, with ~90% accuracy. This model should be able to detect, ahead of time, situations where the blood-glucose level is either too high or too low which could lead to complications for the […]

ROSS Intelligence enables legal professionals to find analyze legal issues and find hidden information and cuts down on research time by using artificial intelligence specialized in legal research. Recent advances in neural networks applied to natural language processing have brought results that are close to human performance in some tasks. However, this approach is still […]

Currently, a number of public and private organizations have implemented various identity management solutions to manage authentication; authorization privileges of their users within or across system and enterprise boundaries. The idea of using a third party identity provider (IdP) to access a relying party (RP) is not new, and both RP and IdP have much […]

Nowadays, a number of public and private organizations have implemented various identity management solutions to manage authentication; authorization privileges of their users within or across system and enterprise boundaries. The idea of using a third party identity provider (IdP) to access a relying party (RP) is not new, and both RP and IdP have much […]

The “Intelligent Camera Switching” research project’s goal is to understand how multiple cameras can be utilized in a meeting space to ensure that remote participants have the best view of the people and activities that take place in the room. This “Best view” should be thought of as providing the best context for activities. A […]

We are conducting research on using techniques from Artificial Intelligence (specifically Machine Learning, Reinforcement learning, and computer vision) to automate the ability of a robotic arm equipped with a hand-like gripper to pick a wide variety of items. The robot uses the visual scene, provided through cameras, in order to choose which item to pick, […]

Machine learning is a discipline of teaching computers repeatable tasks that humans do well but slowly. At Interdata we are on a mission to use Artificial intelligence to understand the data being stored by organizations and the relationships between those data assets. As such Darrell will be working on methodologies and tools to expand our […]

TurnMeUp is an iOS app for always-on voice communications. Users leave the app running in the background and can talk to the recipient (also using the app) at any time. This app is especially useful for coworkers listening to their own music in the background without needing to enter and exit voice call sessions manually. […]

Blockchain is an emerging technology that has the potential to change the way financial participants transact with each other. It enables direct transfer of value and financial assets between participants over networks without the need for a central authority (internet of value). It does this by combining the functionality of different technologies – distributed systems, […]

The human pathogenic bacteria Salmonella enterica and Campylobacter jejuni are commonly found in the intestine of poultry. Consumption of infected chicken and eggs, and its derivatives, is the main and most important source of infection outbreaks in humans causing diarrhoea, fevers and abdominal cramps. In some cases, severe diarrhea and dehydration followed by systemic spreading […]

The intern will work on applying new advances from the field of Machine Learning to models which make predictions about time-series data. The models have the desirable property modeling the distribution of outcomes in a way that we can sample from, allowing us to account for uncertainty in the model’s predictions. By making more accurate […]