The Societe Generale Bank possesses a network of trading applications which generate the hardware consumption data (CPU, memory and network communication). The main usage of this trading system is to receive/ send orders from the market and/ or the clients or vice versa, and based on these order information, business decisions are made accordingly. The […]

A plethora of business models have encouraged the proliferation and expansion of devices connectivity through network densification through 5G core solution. The complexity of the network as well as its ability to evolve constantly have change the way to secure is operated. Security needs to be based on constant monitoring to detect malicious behavior across […]

Better understanding Drug-Drug interactions (DDIs) is crucial for planning therapies and drugs co-administration. While, considerable efforts are spent in labor-intensive in vivo experiments and time-consuming clinical trials, understanding the pharmacological implications and adverse side-effects for some drug combinations is challenging. The majority of interactions remains undetected until therapies are prescribed to patients. We propose to […]

Inferring underlying properties of a dataset is a fundamental task in the fields of learning, statistics, and data analysis. In recent years, the amount of data which we have access to and would like to analyze continues to grow at an astronomical rate. Algorithms that were previously considered efficient for learning properties of the data […]

Character motion in games and animations often have high requirements of realism, aesthetics, and interactivity. For instance, in soccer simulation games, users control the players to move in different directions and perform actions such as passing and shooting. Modern data-driven approaches like motion fields provide convenient ways to synthesizing natural motions from a given database […]

Reinforcement learning (RL) provides a unified framework for sequential decision-making problem, where a computer agent interacts with an environment while trying to learn optimal decisions to maximize its long-term reward. This makes RL a suitable choice for many real-world applications, including finance. RL applications in finance have created a lot of in-depth innovation such as […]

Social networks like maps with real-time traffic are good examples of streaming graphs. These streaming graphs are processed and analyzed to answer the queries in real time. Conventional iterative graph processing algorithms estimate the results by approximating the intermediate values. Upon receiving a query, the computation is performed on these intermediate values. This setting gives […]

IoT devices gather a huge amount of information and, consequently, bring many privacy threats. For example, the huge amount of information collected with IoT devices could be used in individual and behavioral patterns profiling. Thus, new safeguards for privacy and data integrity must be specified. This project aims to resolve data privacy issues using a […]

DriveABLE Inc uses a set of simple video tasks to identify the impaired drivers. Video tasks come in the form of simple games and measure cognitive ability. The test results are analysed by AI powered algorithm that predicts the impairment level of the driver. Our project’s main objective is to redesign the AI in such […]

The proposed research project is aimed at the development of text-to-speech systems that leverage the power of deep neural networks. Our goal is to leverage powerful generated models for speech and combine them with mechanisms to incorporate text information. We hope to explore several such techniques and propose novel methods to achieve this goal. The […]

The focus of the project is to develop an packet-optical network resource optimization model that minimizes the total network cost across IP-optical platform while meeting the following requirements: (i) Offers full protection from any network node and link level failure. (ii) Ability to handle large scale networks and traffic demand (i.e., network scalability). (iii) Meets […]

Deep neural networks have demonstrated state-of-the-art modeling accuracy on a wide range of real-life problems, with some cases surpassing human performance. Despite the promise of deep neural networks as an enabling technology for a large number of industries and fields, there are two particular key challenges in the design of deep neural networks in real-world, […]