Princeton, NJ, United States of America

Yao Qin


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2019-2021

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2 patents (USPTO):Explore Patents

Title: Yao Qin: Innovator in Time Series Prediction

Introduction

Yao Qin is a prominent inventor based in Princeton, NJ (US). He has made significant contributions to the field of time series prediction, holding 2 patents that showcase his innovative approach to technology.

Latest Patents

His latest patents include a "Dual stage attention based recurrent neural network for time series prediction." This invention describes systems and methods for predicting future events by encoding driving series into hidden states. The encoding process adaptively prioritizes driving series at each timestamp using input attention, which includes data sequences collected from sensors. The decoding of these hidden states generates a predicting model that utilizes temporal attention to prioritize encoded hidden states. This system is capable of generating predictions of future events and initiating actions based on those predictions.

Another notable patent is the "Video system using dual stage attention based recurrent neural network for future event prediction." This invention involves systems and devices equipped with an imaging sensor to capture video sequences in environments with safety concerns. A processor generates driving series based on observations from the video sequences and predicts future events using a dual-stage attention-based recurrent neural network (DA-RNN). The DA-RNN employs an input attention mechanism to extract relevant driving series, an encoder to encode these series into hidden states, and a temporal attention mechanism to extract relevant hidden states for decoding. The processor also generates signals to initiate actions that mitigate harm to items.

Career Highlights

Yao Qin is currently employed at NEC Corporation, where he continues to develop innovative solutions in technology. His work focuses on enhancing predictive models that can be applied in various fields, including safety and automation.

Collaborations

He collaborates with notable colleagues such as Dongjin Song and Haifeng Chen, contributing to a dynamic research environment that fosters innovation.

Conclusion

Yao Qin's contributions to time series prediction through his patents reflect his expertise and commitment to advancing technology. His work at NEC Corporation and collaborations with fellow inventors further enhance the impact of his innovations in the field.

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