Hand Pose Reconstruction with Advanced Sensor And Deep Learning

This project explores 3D pose hand reconstruction using machine learning models with sensor data from innovative input devices. The goal is to propose an approach that provides real-time high fidelity hand reconstruction and understand how users perceive its quality to improve user experience and social interaction in AR/VR. The proposed methodology is to train a […]

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Goal-Conditioned Reinforcement Learning

The goal of the project is to improve upon the methodology behind goal conditioned learning. In this framework, similar to the setup in traditional reinforcement learning, an agent interacts with an environment. However, instead of training the agent to maximize return, the agent is trained to reach a given goal at the end of the […]

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Learning Discussion Thread Representations to Empower Content-based Recommendation

VerticalScope is a company that owns online forums in many domains, such as automotive, health, technology, and powersports. VerticalScope uses a content based recommender system to mitigate the cold start problem, where a large portion of traffic on the forums are made by unregistered users. The goal of this project is to learn representations of […]

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Designing ‘Zero credit touch’ (ZCT) pre-approved credit underwriting program for retail customers

ICICI Bank has developed various ‘Zero credit touch’ (ZCT) strategies where without any credit intervention and additional information taken from customers, credit facilities can be provided. But there are several challenges in the expansion of ZCT strategies, namely, (i) current credit models which are a combination of business rules, scorecards and machine learning models, do […]

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Multilingual B2B Supplier Detection and Information Extraction

At Tealbook, we search the web to make the world’s business-to-business supplier websites readily accessible. We extract important sentences and keywords to create a searchable database that buyers can then use to find the right supplier for their needs. But right now, we are limited to servicing English-language organizations. Can we expand our services to […]

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iStandardize: Recommendations for Healthcare Form Standardiz

iStandardize is an AI-powered machine learning solution that is designed to streamline the standardization of clinical order sets (i.e., forms) by using machine learning and natural language processing techniques. Currently, hospital networks use multiple versions of forms and order sets, many of them are similar in nature. The lack of standardization poses a challenge in […]

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Explore efficiently automated parallel hyperparameter search for optimizing machine learning models over large scale cloud cluster

Machine learning has been applied in various fields and shown promising results in recent years. Researchers have found that tuning machine learning models in a proper way can vastly boost the model performance with respect to the specific AI task. However, tuning machine learning models at scale, especially finding the right hyperparameter values, can be […]

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An Investigation of Service Mesh(es) and Security Models Within and Across Multiple Distributed Systems

Global service providers in highly regulated financial sectors must accommodate an ever-changing, sometimes competing, landscape of regulatory concerns. This project seeks to determine a reasonable path forward in technology design and adoption to accommodate current and anticipated infrastructure changes. Moreover, bridging the service layer across multiple, distinct distributed systems of varying complexity will pose new […]

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Applied Machine Learning for Early Detection of Retinal Toxicity

Hydroxychloroquine (HCQ) is an anti-inflammatory drug that is widely prescribed for a range of auto-immune disorders such as lupus and rheumatoid arthritis. An unwanted side effect of long-term use of HCQ is vision loss by retinal toxicity. If detected early, it could lead to early intervention to prevent vision loss and improve the quality of […]

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