Rong Yin – Graph Neural network – Best Researcher Award

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Rong Yin – Graph Neural network

Dr. Rong yin  distinguished academic and researcher in the field Graph Neural Network. She is a highly accomplished researcher with a focus on cutting-edge areas in artificial intelligence and machine learning. Over the past five years, she has made significant contributions, publishing over ten top conference and journal papers in esteemed venues such as NeurIPS, ICML, AAAI, IJCAI, IEEE TKDE, IEEE TNNL, PR, and IEEE TC. Recognized for her expertise, she has been invited to serve as a program committee member and reviewer for prestigious conferences and journals, including ICML, NeurIPS, ICLR, AAAI, and JMLR. One of her notable contributions includes proposing an efficient unsupervised learning algorithm based on the unified randomized sketches framework, paving the way for the application of machine learning in international important fields with massive data scenarios.

Additionally, she has designed a series of approximation algorithms for large-scale tasks such as regression, classification, ranking, and distributed learning. Her theoretical analyses have yielded optimal convergence rates for large-scale unsupervised learning, regression, and distributed learning, making significant strides in machine learning theory. As the principal or core backbone of more than 20 national or provincial key projects, including the Youth/General Fund of the National Natural Science Foundation of China and the National Key R&D Program, she has demonstrated leadership in advancing research in the field.

 

Professional Profiles:

Education

She earned her Ph.D. in Computer Science from the Institute of Information Engineering at the Chinese Academy of Sciences in July 2020, under the guidance of Prof. Dan Meng. Her research during this period has significantly contributed to the field, as evidenced by her subsequent achievements. Prior to her doctoral studies, she completed her M.S. in Computer Science at Harbin Institute of Technology in China in July 2016, with Prof. Xiaohong Su as her advisor. Her academic journey commenced with a B.S. in Thermal Energy and Power Engineering from Shenyang Aerospace University, China, in July 2014, under the mentorship of Prof. Rangshu Xu. Throughout her educational trajectory, she has demonstrated a commitment to academic excellence and has seamlessly transitioned from her undergraduate studies to achieving a Ph.D. in Computer Science, showcasing a continuous pursuit of knowledge and expertise in her chosen field.

Experience

She has been an integral part of the Institute of Information Engineering at the Chinese Academy of Sciences in China, serving as an Associate Researcher since December 2023. Her journey with the institute commenced in August 2020 when she was designated as an Associate Researcher to be Appointed, a position she transitioned into officially in December 2023 and continues to hold to the present. In her capacity as an Associate Researcher, she plays a crucial role in the ongoing research activities of the institute, contributing her expertise and insights to further the objectives of the organization. Her commitment to the field and the institute is evident in her sustained role, where she actively contributes to the research endeavors of the Institute of Information Engineering.

Academic achievements

  • Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Scalable Kernel k-Means with Randomized Sketching: From Theory to Algorithm. In IEEE Transactions on Knowledge and Data Engineering, 2023, 35(9): 9210 – 9224. (TKDE 2023) (CCF-A, SCI-1, IF: 9.235). [PDF]
  • Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Randomized Sketches for Clustering: Fast and Optimal Kernel k-Means. In Proceedings of Advances in Neural Information Processing Systems, 2022, 35: 6424-6436. (NeurIPS 2022) (CCF-A). [PDF]
  • Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Distributed Nystrom Kernel Learning with Communications. In Proceedings of the 28th International Conference on Machine Learning, PMLR, 2021: 12019-12028. (ICML 2021) (CCF-A). [PDF]
  • Rong Yin, Yong Liu, Dan Meng. Distributed Randomized Sketching Kernel Learning. In Proceedings of the 36th AAAI Conference on Artificial Intelligence, 2022, 36(8): 8883-8891. (AAAI 2022) (CCF-A). [PDF]
  • Ruyue Liu, Rong Yin*, Yong Liu, Weiping Wang. ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network. In Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024. (AAAI 2024) (CCF-A, Corresponding author).
  • Rong Yin, Yong Liu, Lijing Lu, Weiping Wang, Dan Meng. Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm. In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020, 34(04): 6696-6703. (AAAI 2020) (CCF-A). [PDF]
  • Xueyan Wang, Jianlei Yang, Yinglin Zhao, Xiaotao Jia, Rong Yin, Xuhang Chen, Gang Qu, Weisheng Zhao. Triangle counting accelerations: From algorithm to in-memory computing architecture. IEEE Transactions on Computers, 2021, 71(10): 2462-2472. (TC 2021) (CCF-A, SCI-1, IF: 3.7). [PDF]
  • Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Sketch Kernel Ridge Regression using Circulant Matrix: Algorithm and Theory. In IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(9): 3512-3524. (TNNLS 2020) (SCI-1, IF: 11.683). [PDF]
  • Ruyue Liu, Rong Yin*, Yong Liu, Weiping Wang. Unbiased and Augmentation-Free Self-Supervised Graph Representation Learning. In Pattern Recognition, 2024. (PR 2024) (SCI-1, IF: 8, Corresponding author). [PDF]
  • Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Extremely sparse Johnson-Lindenstrauss transform: From theory to algorithm. In Proceedings of IEEE International Conference on Data Mining, 2020: 1376-1381. (ICDM 2020) (CCF-B). [PDF]
  • Lijing Lu, Rong Yin, Yong Liu, Weiping Wang. Hashing Based Prediction for Large-Scale Kernel Machine. In Proceedings of the International Conference on Computational Science, 2020: 496-509. (ICCS 2020). [PDF]
  • Jian Li, Yong Liu, Rong Yin, Weiping Wang. Multi-Class Learning using Unlabeled Samples: Theory and Algorithm. In Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019: 2880-2886. (IJCAI 2019) (CCF-A). [PDF]
  • Jian Li, Yong Liu, Rong Yin, Weiping Wang. Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis. In Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019: 2887-2893. (IJCAI 2019) (CCF-A). [PDF]

Publication

Hongxia Song – Graph Analytics- Best Researcher Award

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Hongxia Song – Graph Analytics

Dr. Hongxia Song   distinguished academic and researcher in the field Graph Analytics.  Song Hongxia, born in 1979 in Changzhi, Shanxi, is a highly accomplished individual with a Ph.D. and the title of associate professor, specializing in vegetable cultivation and stress physiology. Serving as a master’s supervisor, she is deeply involved in research on horticultural plant functional substance mining and product development. Song Hongxia holds the esteemed position of a post expert in the Shanxi Vegetable Industry System and is an active member of the Professional Technical Committee of Agricultural Products and Animal Husbandry Inspection and Testing in the Shanxi Inspection and Testing Alliance. Additionally, she contributes to standardization efforts as a member of the Standardization Committee in Jinzhong City.

Recognized for her exceptional contributions, Song Hongxia has received various accolades, including the title of “One hundred Gold Medal Lecturers” by the Shanxi Provincial Department of Agriculture. Her expertise extends to leadership roles, where she serves as the Chief Expert of Shilou County and holds the distinguished title of Expert in the Expert Group of Jinzhong Rural Revitalization Association. Notably, she is acknowledged as a Distinguished Expert in Shangdang District, Taigu District, and Zezhou County, showcasing her commitment and impact in the field of agriculture and rural development.

Eduvation

She embarked on her academic journey in 1998, pursuing a Bachelor’s degree in Horticulture and Economic Management at Shanxi Agricultural University. Demonstrating a strong commitment to her field, she continued her studies at the same institution and earned a Master’s degree in Vegetable Science from 2002 to 2005. Undeterred in her pursuit of knowledge, she further advanced her academic qualifications by undertaking a Ph.D. in Vegetable Science at Shanxi Agricultural University from 2011 to 2015. Throughout her educational trajectory, she exhibited a dedicated focus on horticulture and vegetable science, laying the foundation for her subsequent contributions to these domains.
Professional Profiles:

Professional Experience

She has accumulated a wealth of professional experience, currently holding the position of Associate Professor in the Department of Vegetables at the College of Horticulture, Shanxi Agricultural University, a role she has undertaken since 2017. Prior to her current position, she served as a Lecturer in the same department from 2008 to 2017, showcasing her commitment to academic and professional growth. Her journey in academia began as an Assistant Professor in the Department of Vegetables at the College of Horticulture, Shanxi Agricultural University, where she contributed from 2005 to 2008. Across these roles, she has played a pivotal role in the academic and research endeavors related to vegetables, enriching both her expertise and the educational landscape at the university.

Teaching and scientific research projects

She has been actively involved in a multitude of research and educational initiatives, showcasing her leadership and expertise in the field. In 2023, she assumed the role of principal investigator for the “Research and Practice of Smart Teaching Reform of ‘Vegetable Science Experiment'” (Project No: J20230323), which is part of the Shanxi Provincial Higher Education General Teaching Reform and Innovation Project. Her dedication to advancing education is further evident as the course leader for “Vegetable Cultivation,” a course recognized as an offline first-class offering in Shanxi Province in 2022.

In 2021 and continuing into the present, she holds the esteemed position of a position expert within the vegetable industry technology system in Shanxi Province, underlining her influence in shaping the technological landscape of the local industry. Her commitment to innovation is demonstrated through her leadership as the principal investigator for the “Integration and Demonstration of Efficient Production Technology for Fruits and Vegetables in Facilities” (Project No: XDHZRCZXY-04) under the College of Talent Revitalization at Shanxi Agricultural University in 2023.

Additionally, she actively contributes to addressing critical challenges in the field, such as the participation in the key R&D project of Shanxi Province titled “Research on key technologies for overcoming temperature and light stress obstacles and environmental regulation of fruits and vegetables” (Project No: 202102140601013). Through her multifaceted involvement in research, education, and technology integration, she continues to make significant strides in advancing the understanding and application of vegetable science.

Textbooks

Vegetable Seedling science, China Agriculture Press, 2014, Editor-in-Chief

Honorable achievements

1. Technical Regulations for Drought-resistant and Light Simplified Cultivationof Pepper in Open Field Shanxi Province Local Standard (DB 14/T 2412-2022), Shanxi Provincial Agricultural Standardization Technical Committee, 2022, No. 1. 2.Technical Regulations for Dryland Tomato Cultivation, Shanxi Provincial Local Standard (DB 14/T 2064—2020), Shanxi Provincial Agricultural Standardization Technical Committee, 2020, No. 1. 2. “2+1+1” School-Enterprise (Institute) Joint Talent Training Model, Special Prize for Teaching Achievements in Shanxi Provincial Colleges and Universities, Shanxi Provincial Department of Education, 2018, fourth. 3. Technical specification for efficient carbon sequestration production of celeryin solar greenhouse, Shanxi Provincial Local Standard (DB 14/T 1555-2018), Shanxi Provincial Agricultural Standardization Technical Committee, 2018, first. 4.Technical specification for efficient carbon sequestration production of carrots in early spring in solar greenhouse, Shanxi Provincial Local Standard (DB14/T1284-2016), Shanxi Provincial Agricultural Standardization Technical Committee, 2016, No. 1. 5. One of the “100 Gold Medal Teachers”, Shanxi Provincial Department of Agriculture, 2020. need bullats

Patents

Song Hongxia, Yang Yanwei, Li Yanping, Li Meilan, Hou Leiping, Lu Qiang. Acooking and crushing device for producing tomato paste, 2021.1.15. China, ZL20202 14856687
Song Hongxia, Li Meilan, Hou Leiping, Xu Xiaoyong, Nie Hongmei. . Asupport
for tomato planting, 2021.4.23. China, ZL 2020 2 1050095.5 2021.01

Publication

1. Hongxia Song, QiangLu, Tianyue Song, et al. Study on the Mechanism of Carotenoid
Production and Accumulation in Orange Red Carrot (Daucus carota L.). Scientia
Horticulturae, 327(3). doi: org/10.1016/j.scienta.2023.112825(2024)

2. Song H, Wu P, Lu X, Wang B, Song T, Lu Q. (2023) Comparative physiological and
transcriptomic analyses reveal the mechanisms of CO2 enrichment in promoting the growthand quality in Lactuca sativa. PLoS ONE 18(2): e0278159. doi:10.1371/journal.pone.0278159

3. Hongxia Song, Qiang Lu, Leiping Hou, Meilan Li. The genes crucial to carotenoidmetabolism under elevated CO2 levels in carrot (Daucus carota L.). Sci Rep. 2021 Jun 8;
11(1):12073. doi: 10.1038/s41598-021-91522-7.

4. Hongxia Song, Qiang Lu & Xiaoyu Guo Identification of candidate genes associated with JAunder elevated CO2 in carrot (Daucus carota L.). Biotechnology & Biotechnological
Equipment, 2021, 35 (1), 1065–1075.

5. Hongxia Song; Yanling Li; Xiaoyong Xu; Jing Zhang; Shaowen Zheng; Leiping Hou;
Guoming Xing; Meilan Li. Analysis of genes related to chlorophyll metabolismunder
elevated CO2 in Cucumber (Cucumis sativus L.), Scientia Horticulturae, 261(5). doi: org/10