Pipeline for Identifying Potentially Hazardous Asteroids

Potentially hazardous objects (PHOs) are currently defined based on parameters that measure the object's potential to make threatening and close approaches to the Earth. To be considered a PHO, objects generally have an Earth minimum orbit intersection distance (MOID) of 0.05 AU or less and an absolute magnitude (H) of 22.0 or brighter (a rough indicator of large size).

Dynamic Factor Selection for Determining Market Exposure

Market exposure is a key concept in quantitative finance. This is classically measured by estimating a beta coefficient in a linear equation where beta (exposure) expresses the returns of the market. Returns with low exposure to the market are desired, as they are not affected by downturns. This exposure modeling can be generalized to multiple factors and the exposures to factors are used to determine if a strategy or asset is protected enough from changes in certain risk factors, and to purchase hedges that cancel out this risk exposure.

Student: Delaney Granizo-Mackenzie 

Stochastic Query Optimization and Bias Characterization for Large Scale Text Search

Legendary is a leading film production company, with 43 Feature films released, 6 films currently in production and 13 billion box office until 2015. Identifying the correct search terms to find social media posts about an entity or concept is a highly challenging task. For instance, the word Fargo may refer to a place (in North Dakota), a TV show, a movie, or a bank (Wells Fargo). The student team analysed 4 million tweets to produce a text-query generation & optimization system.

Restaurant Photo Classification Algorithm and Business Viability Tool for Tripadvisor

TripAdvisor users write reviews and upload photos from their various restaurant visits. These photos can be categorized/analysed so they can reveal information about the restaurant's menu, dishes, pricing, etc. The first step in this analysis is the classification of photos into simple, broad groups: food, drinks, menus, inside and outside photos of the establishment. Students' goal for this project was to build an image classifier using Convolutional Neural Networks and images aquired by the students themselves.

Nester for Design

Nester is a platform where companies can find the best designs for a project, using Kaggle. Kaggle is a platform that hosts machine learning competitions where companies and researchers post data and pose challenges. Data scientists from all over the world compete to answer the questions and to produce the best results, in effect, crowdsourcing the most efficient technique or solution to the questions.