Ribosome biosynthesis is one of the most multifaceted and energy-demanding processes in biology. It involves over 250 factors that transiently associate with the nascent pre-ribosome in a well-orchestrated manner. Importantly, increased ribosome biogenesis has a critical role in cancer initiation and progression. Owing to the advances in cryo-electron microscopy, this pathway's detailed mechanism started to be revealed, setting the grounds for new therapeutic interventions. The current project seeks to develop chemical probes for WD repeat proteins, a new drug target class.
While taking foreign language tests, people may record responses with different background noises. The contaminated audios can lead to unusual results in speech recognition and scoring by the scoring systems. Pearson would like to develop a more robust system for the automated speech recognition machine to work with clean and noisy records. Audio files are typically from 5 to 90 seconds long. There are popular softwares which are built to address these problems, but their results need to be tested with the particular kinds of inputs that is obtained as test responses.
Accurately recommending items of interests is essential for users to improve their experience. To acquire better performance, a recommender system can utilize multiple sources of data and the social knowledge graph. This can lead to efficient use of information to improve the recommender system. By exploring the data and extract crucial features to feed to designed models, the recommending engine can increase its performance dramatically. Furthermore, a social knowledge graph contains the description and relation of users, which can act as a knowledge base for inference.
Surgical Safety Technologies aims to provide healthcare professionals with the opportunity to perform research in areas of surgical performance and education and implement evidence-based solutions to improve patient safety. Search on video content would an ideal functionality to assist with healthcare professionals’ research. This project uses computer vision model to rank the relevance of the surgical video.
Many retailers are interested in forecasting demand for the products they sell. Deloitte has used machine learning methods to tackle this problem in the past. However, this requires the creation of hand-crafted features based on product sales data, which is a costly and time-intensive process. Using alternative models to perform this task would remove the need for laborious data manipulation. It will also allow model enhancements to scale across many clients rather than requiring from-scratch data manipulation for each new client.
Voice of the Customer (VoC) is how companies hear and listen to customer feedback about their brand, products, and services. Voice of the Customer solutions convert gathered feedback into valuable data and insights at scale. Data-driven VoC analytics programs are proven to increase customer lifecycle value and lower customer churn. Companies in various industries including insurance, financial services, and healthcare are leveraging this technology to generate insights into customer needs.
Everyday millions of customers move through the sales cycles of companies, generating numerous data for potential use. The main objective of the research project is to advance the current state of the art techniques inside the company, with respect to the application of new algorithms on customer behavior data. From a research perspective, access to large sets of complex real world data can enhance great possibilities to apply and evaluate existing techniques at scale and to develop exciting new ones.
Autonomous unmanned aerial vehicles (UAVs) are receiving significant attention in many communities, including academia, industry, and consumer electronics. SOTI is the world’s most trusted provider of mobile and IoT management solutions and its new aerospace division, SOTI Aerospace is focusing on hardware and software systems to support self-navigating situationally aware aerial drones. This project belongs to SOTI aerospace division and focuses on a vision system for the indoor environment.
Machine learning has great potential in detecting cognitive, mental and functional health disorders from speech, as acoustic properties of speech and corresponding patterns in language are modified by a variety of health-related effects. Specifically, neural language models, have recently demonstrated impressive abilities in tasks involving linguistic knowledge. Their success in language understanding and classification tasks could be attributed to their effective representations of linguistic knowledge.