J.C.

Jun Chen


About Me

Algorithm Tech Lead, Baidu Intelligent Healthcare The algorithm tech lead in charge of the core of AI capabilities in clinical decison support system (CDSS, both for top-tier hospitals and primary healthcare facilities), intelligent medical/commercial insurance and intelligent medical record system as well as the extension of medical knowledge graph and natural language understanding in collaboration with other units inside Baidu. Lead of academic research, next-generation technology, college-firm collaboration, national/industry/alliance standards as well as high-tech projects authorized by the state council of China. A pioneer in AI-assisted diagnosis and treatment including the most recently released Seq2Subgraph framework that changes the paradigm of managing with clinical texts. Technically support projects that cover over 90% of provinces and major cities in China including two directly authorized by the state council. MIT Techology Reviews and other mainstream media have reported our achievements.

Contact

Email: chenjun22 at baidu.com, chenjun082 at gmail.com .

News

Research Interest

My principle research interests generally lie in machine learning and data mining from large scale datasets with the focus on personalization, recommender systems and learning from user behaviors. Besides, I also have broad interests in deep learning, natural language processing, multimedia, information retrieval as well as social networks.

Education

  1. Doctor of Philosophy, Software Engineering.
    Supervised by Prof. Jianmin Wang and Associate Prof. Chaokun Wang
    School of Software, Tsinghua University.
    Sept 2012 - July 2017.

  2. Bachelor of Science, Computer Software.
    School of Software, Tsinghua University.
    Sept 2008 - July 2012.

Working/Teaching Experience

  1. Staff Research Scientist and Algorithm Lead, Baidu Inc.

    Jul, 2017 - Now. I am currently the tech lead of the CDSS team in Baidu Intelligent Healthcare. We dedicate ourselves in advancing the AI technology for the healthcare problems. The AI driven healthcare is the major mission of our team. The example projects I drive include the clinical decision support system (CDSS), the automatic non-factoid question answering as well as the intelligent online triage system.

  2. Research Assistant, Tsinghua University.

    Jan, 2016 - Jul, 2017. I worked with Prof. Chaokun Wang on the research of pesonalized recommendation and social networks.

  3. Teaching Assistant for Digital Media (II): Multimedia (44100415), Tsinghua University.

    Sep, 2014 - Jan, 2016. I designed and evaluated the homework and the project (e.g. music resizing challange) for this course.

  4. Teaching Assistant for Architecture of Computer and Network (II) (34100344), Tsinghua University.

    Feb, 2014 - Jul, 2015. I designed and evaluated the homework and the project (e.g. the project of assembly language application and that of languge-to- language translation for compilers) for this course.

  5. Teaching Assistant for An Introduction to Modern Database System (84100162), Tsinghua University.

    Sep, 2013 - Jan, 2015. I designed and evaluated the homework and the project (e.g. similarity join of complex data, query engine for high dimensional data) for this course.

  6. Research Assistant, Tsinghua University.

    Sep, 2012 - Sep, 2013. I worked with Prof. Chaokun Wang on the research of the estimation of music stretching resistance.

  7. Software development engineer, summer intern, Amazon Inc.

    Jul, 2012 - Aug, 2012. I developed a system to enable the book merchants on Amazon.cn to easily manage the stocks of their selling books.

Selected Publications

Full Publications

  1. A Novel Sequence-to-Subgraph Framework for Diagnosis Classification. [Link]
    Jun Chen, Quan Yuan, Chao Lu, Haifeng Huang.
    The 30th International Joint Conference on Artificial Intelligence (IJCAI). 2021.

  2. Medical Image Enhancement for Lesion Detection Based on Class-Aware Attention and Deep Colorization. [Link]
    Jiachang Guo, Jun Chen, Chao Lu, Haifeng Huang.
    IEEE 18th International Symposium on Biomedical Imaging (ISBI). 2021.

  3. Towards Interpretable Clinical Diagnosis with Bayesian Network Ensembles Stacked on Entity-Aware CNNs. [Link][Data][Video Presentation]
    Jun Chen, Xiaoya Dai, Quan Yuan, Chao Lu, Haifeng Huang.
    The 58th Annual Meeting of the Association for Computational Linguistics (ACL). 2020.

  4. The Graph-based Mutual Attentive Network for Automatic Diagnosis. [Link]
    Quan Yuan, Jun Chen (Corresponding author), Chao Lu, Haifeng Huang.
    International Joint Conference on Artificial Intelligence (IJCAI). 2020, Yokohama, Japan.

  5. Knowledge Abstraction Matching for Medical Question Answering. [Link]
    Jun Chen, Jingbo Zhou, Zhenhui Shi, Bin Fan, Chengliang Luo.
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2019, San Diego, California, USA.

  6. Understanding Item Consumption Orders for Right-Order Next-Item Recommendation. [Link]
    Jun Chen, Xuecheng Wang, Chaokun Wang.
    Knowledge and Information Systems (KAIS). Volume:57. 2018.

  7. Learning the Personalized Intransitive Preferences of Images. [Link][Data][Codes]
    Jun Chen, Chaokun Wang, Jianmin Wang, Xiang Ying, Xuecheng Wang.
    IEEE Transactions on Image Processing (IEEE TIP). Volume:26, Issue:9, 2017.

  8. Modeling the Intransitive Pairwise Image Preference from Multiple Angles. [Link][AudioSlides][Poster]
    Jun Chen, Chaokun Wang, Jianmin Wang.
    ACM International Conference on Multimedia (MM'17), 2017, Mountain View, California, USA.

  9. Learning the Structures of Online Asynchronous Conversations. [Link][Slides][Data]
    Jun Chen, Chaokun Wang, Heran Lin, Weiping Wang, Zhipeng Cai, Jianmin Wang.
    Proceedings of the 22nd International Conference on Database Systems for Advanced Applications (DASFAA'17), 2017, Suzhou, China.

  10. Recommendation for Repeat Consumption from User Implicit Feedback. [Link][Codes]
    Jun Chen, Chaokun Wang, Jianmin Wang, Philip S. Yu.
    IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE). Volume:28, Issue:11, 2016.

  11. A Personalized Interest-Forgetting Markov Model for Recommendations. (oral presentation, acceptance rate 11.75%) [Link][Slides]
    Jun Chen, Chaokun Wang, Jianmin Wang.
    Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), 2015, Austin, TX, USA.

  12. Will You "Reconsume" the Near Past? Fast Prediction on Short-term Reconsumption Behaviors. (acceptance rate 26.67%) [Link][Poster][Data]
    Jun Chen, Chaokun Wang, Jianmin Wang.
    Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), 2015, Austin, TX, USA.

  13. CrowdMR: Integrating Crowdsourcing with MapReduce for AI-hard Problems. [Link][Poster][Demo]
    Jun Chen, Chaokun Wang, Yiyuan Bai.
    Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), 2015, Austin, TX, USA.

  14. Modeling the Interest-Forgetting Curve for Music Recommendation. [Link][Poster]
    Jun Chen, Chaokun Wang, Jianmin Wang.
    Proceedings of the 22nd ACM International Conference on Multimedia (MM'14), 2014, Orlando, FL, USA.

Datasets

  1. Disease-Finding Relationship: A dataset of disease-finding causal relationship mining from real-world Chinese electronic medical record documents.
    *Published with my ACL'20 paper.

  2. Douban Group Conversations: A corpus of online chats on the Chinese web forum Douban Group.
    *Published with my DASFAA'17 paper.

  3. Holidays Image Preference: A dataset of pairwise preference on some images from INRIA Holidays.
    *Published with my IEEE TIP paper.

  4. ManicTime PC APP Usage: The logs of APP usage on personal computers.
    *Published with my AAAI'15 paper.

  5. Music Stretching Resistance: The maximum elongating rate and the minimum compressing rate of 894 songs, the title and genre of the songs as well as the name of the artists.
    *Published with my IEEE Singal Processing Letters 2013 paper.

Honors and Awards

  1. Baidu ACG-TC Tech Inspiration Award (Group), 2020.

  2. Baidu ACG Outstanding Group Award (CDSS Group), 2020.

  3. Baidu ACG Outstanding Mentor Award, 2020.

  4. Baidu AIG-PC Innovative Product Award, 2019.

  5. Baidu AIG Star of the Quarter Award, 2018.

  6. Baidu AIG-TC Tech Inspiration Award, 2018.

  7. Outstanding Ph.D graduate of Tsinghua University, 2017.

  8. Outstanding Ph.D dissertation of Tsinghua University, 2017.

  9. Outstanding Ph.D graduate of Beijing city, 2017.

  10. Huayu Principle Scholarship, Tsinghua University, 2016.

  11. Graduate National Scholarship of China, Ministry of Education, 2015.

  12. Graduate National Scholarship of China, Ministry of Education, 2014.

  13. Sashixuan Best Student Paper Award, China Computer Federation, 2014.

  14. RIM Scholarship, Tsinghua University, 2013.

  15. Outstanding academic undergraduate thesis, Tsinghua University, 2012.

  16. Huangyicong Scholarship, Tsinghua University, 2010.

  17. AEON Scholarship, Tsinghua University, 2009.

Research Service