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The Introduction of The Fifth Domain Expert Candidate-Dr. Yu, Multi-Model Machine Learning Expert

The true development direction of Artificial Intelligence: Multi-Model Machine Learning

The first round of “Domain Expert Election Month” released by the EpiK Protocol Foundation will be officially ended today.

We have successively announced 5 experts in different domains:

Aken, an Emotion AI expert;

Becky, a financial knowledge graph expert;

Professor Wu, a finance and artificial intelligence expert;

Andy, a smart transportation and smart IoT expert;

and Yu Hongyuan, a domain expert candidate in the field of multi-modal learning that we will introduce today.

This time, we are going to introduce the fifth domain expert-Hongyuan, an algorithm engineer who has made a lot of achievements in the field of Multi-Modal Machine Learning. The knowledge graph is one of the core driving forces for the development of smart artificial intelligence, and it is the consensus of artificial intelligence academia.

The data source of knowledge graphs is never limited to text and structured data, but also visual or auditory data such as images, videos, and audio. The ability to process and understand multi-source modal information through machine learning is Multi-Modal Machine Learning (MMML).

Introduction of EpiK Protocol’s fifth Domain Expert Candidate-Multi-Model Machine Learning Expert

Hongyuan Yu is a PH.D. from the State Key Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences. And his current research interests mainly include machine learning, multi-model representation learning, and computer vision.

Dr. Yu once won the international visual tracking competition VOT RGBD track champion, ROBCUP JAPAN OPEN competition runner-up, the International Document Recognition Conference ICDAR Best Paper Award. In addition, he has conducted academic research with Baidu, Microsoft Research Asia, and Alibaba Ant Group and published several papers in international conferences such as NeruIPS, ECCV, and top journals such as IJCV, PR, and TCSVT.

After a deep understanding of EpiK Protocol’s grand vision and solid efforts in the field of the knowledge graph, Dr. Yu applied to be a domain expert in the field of Multi-Modal Machine Learning, hoping to improve the implementation of Multi-Model Machine Learning algorithm with the support of the collected high quality AI data by innovative AI data annotation system.

At the same time, Dr. Yu believes that through accurate and high-quality data annotation work, we can obtain better algorithms. Through the multi-modal training algorithm, It can also provide more accurate and efficient automated data screening tools for the domain experts admin system of EpiK Protocol, which truly realize the algorithm to feedback data.

As the concept of Linked Data, the knowledge graph itself is multi-modal. At present, commercial knowledge graphs that have been put into use mostly associate various modal data through knowledge graphs to provide multi-modal search capabilities. Thus, there is no doubt that the research of multi-modal machine learning and knowledge graph still has huge development space and innovation opportunities.

EpiK Protocol also looks forward to that the join of Dr. Yu will bring new vitality to the EpiK Protocol ecosystem.




An AI-first blockchain that aims at an open and collaborative AI data network accessible to all AI bots in Web3. It provides the infrastructure for the community to curate high-quality human-labeled AI training data and contributes to AI bots both in real world and metaverse.

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EpiK Protocol

EpiK Protocol

The World’s First Decentralized Protocol for AI Data Construction, Storage and Sharing. https://www.epik-protocol.io/ | https://twitter.com/EpikProtocol

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