Multiple Sclerosis (MS) can be divided into three clinical phenotypes: relapsing remitting (RRMS), secondary progressive (SPMS) and primary progressive (PPMS). RRMS is characterized by episodic worsening followed by full or partial recovery, whereas SPMS and PPMS are characterized by steady accrual of disability.Progressive MS remains poorly understood and generally fails to respond to therapies that are effective in RRMS. This may be related to fundamental differences in the biology that underlies relapsing vs.

Optina Diagnostics works on detection of Alzheimer’s Disease using hyperspectral eye imaging techniques. This project was an exploratory analysis of data gathered by Optina so far in order to optimize and fit models to most effectively predict cases. Recommendations from the analysis were then handed over to Optina for future work.

Modular synthesizers are becoming more commonplace in the studios of musicians around the globe. These instruments, first invented in the 1960s, are composed of modules, each of which performs a unique function, such as generating sounds or modifying them by applying effects such as distortion, echo and more.

Using simplified language understandable to a layperson; provide a general, one-paragraph description of the proposed research project to be undertaken by the intern(s) as well as the expected benefit to the partner organization. {100 - 150 words)
The project aims to develop a molecular compounds database to accelerate drug discovery. Compounds shared by chemical providers are currently stored in large library files. Due to their size and number, these files are a bottleneck in virtual screening.

The secure and reliable operation of an electric power grid is critical to national security. Power grid components such as the state estimator used to monitor the operating state of a power system are subject to cyber-attacks. Previous works show that an intruder can compromise the state estimation by injecting the pre-designed false data into meters without being detected if the detailed knowledge of a transmission grid is known.

In this project the intern will work with time series data containing different parameters from a flight simulator. The intern will take these data and assess different learning as well as change point detection algorithms that can identify and segment pilot reactions to malfunctions and assign these reactions a proficiency metric. One of the possible approaches would be to assess the use of change point detection algorithms using a data driven approach. This will allow the partner organization to understand important segments of the flight data where large changes have taken place.

Additive manufacturing offers new opportunities for designing high performance composite structures. However, sophisticated numerical approaches are required to tackle the complex task of designing structures which take full advantage of additive manufacturing capabilities. The proposed research project aims to apply topology optimization, a numerical approach capable of determining the best shape of a structure, to develop a design process producing optimal composite sandwich structures which include a 3D printed core.

The project aims to improve the amount of labelled samples in a semi-automatic or automatic manner using AI to impove a CNN performance. We will test various state-of-the-art AI methods, in the context of forest inventory, and select the most effective ones.

The benefits will be significant because labelling is an important but tedious task, in many cases, when working with natural forests, some tree species will not occur as often as others (hence creating a shortage in some classes), also there can be co-species to many other species and they are difficult to identify clearly.

Integration of an ontology for the representation of restaurants, menus and dishes for the catering industry and construction of a recommendation model using this ontology.

Innodem Neurosciences is developing a visible light gaze-tracking algorithms that can be sued to predic a user's gaze position on the screen of a mobile device without the need for any third-party hardware. This algorithm leverages various image processing techniques, and relies on the use of convolutional neural networks and computer vision. Enhancing the quality of this gaze prediction network will be the primary goal of the resident scientist over the course of this project.