陈锶奇
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主要研究方向:人工智能、多agent系统、管理科学、生物信息计算



近3年论文:

  • MFA-DTI : Drug-target interaction prediction based on multi-feature fusion adopted framework. Methods. 2024. (IF=4.8)

  • PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants. Plant Physiology. 2024.(IF=7.4)

  • ANOTO: Improving Automated Negotiation via Offline-to-Online Reinforcement Learning. AAMAS 2024(CCF-B会议).

  • An effective negotiating agent framework based on deep offline reinforcement learning. UAI 2023 (CCF-B会议).

  • Transfer Learning based Agent for Automated Negotiation. AAMAS 2023(CCF-B会议).

  • DNN-PNN: A parallel deep neural network model to improve anticancer drug sensitivity. Methods. 2023. (IF=4.8)

  • Transfer Reinforcement Learning Based Negotiating Agent Framework. PAKDD 2023 (CCF-C会议).

  • A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data.PLoS Computational Biology. 2022. (IF=4.3)

  • An autonomous agent for negotiation with multiple communication channels using parametrized deep q-network. Mathematical Biosciences and Engineering. 2022. (IF=2.6)

  • An Intelligent Chatbot for Negotiation Dialogues. UIC 2022 (CCF-C会议).

  • Detecting and Learning Against Unknown Opponents for Automated Negotiations. PRICAI 2021(CCF-C会议,Best paper runner-up award)



  • Education Background
  • Work Experience
  • Maastricht University
  • 博士研究生毕业
  • 博士学位

  • 电子科技大学
  • 大学本科毕业
  • 学士学位

  • Social Affiliations
  • Research Focus
  • AAAI, AAMAS, PRICAI 等国际重要人工智能会议程序委员会委员(PC member)

Personal information

Supervisor of Master's Candidates

Gender : Male

Education Level : 博士研究生毕业

Degree : 博士学位

Status : Job

Discipline : engineering Management

Contact Information : siqi.chen09@gmail.com

Email :

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