2023.02.10: our paper has been presented at AAAI23 in Washington D.C., USA!
2022.10.25: our paper has been accpeted by AAAI23!
2022.03.01: our journal paper has been published in IEICE TRANSACTIONS on Information and Systems!
2020.07.01: our journal paper has been published in IJMDEM!
A self-motivated researcher with rich implementation experience in deep learning,
including computer vision, multimodal processing, contrastive learning, and imbalanced learning.
Strong interest in media contents
with subjective evaluation. Experienced in collaborative research with researchers from different fields. Also
experienced in AI interface development.
Department of Information and Communication Engineering, The University of Tokyo
04/2023 – PresentDepartment of Information and Communication Engineering, The University of Tokyo
Thesis title: Presentation Skill Assessment Systems using Deep Neural Networks
04/2020 – 03/2023Department of Information and Communication Engineering, The University of Tokyo
Thesis title: Impression Analysis on Presentations using Attention-based LSTM
04/2018 – 03/2020Fuji International Language Institute
07/2016 – 03/2018Software Engineering, Sun Yat-sen University
Thesis title: Plant Recognition Based on GoogleNet
10/2012 – 07/2016Research experience in computer vision, multimodal processing, and natural language processing. Current research on contrastive learning and prompt learning.
Experienced in collaborative research with companies and research institutes, and cooperation with other engineers.
1. Shengzhou Yi, Junichiro Matsugami, and Toshihiko Yamasaki. Assessment System of Presentation Slide Design using Visual and Structural Features. IEICE TRANSACTIONS on Information and Systems, vol. E105-D, no. 3, pp. 587-596, 2022. [URL]
2. Shengzhou Yi, Koshiro Mochitomi, Isao Suzuki, Xueting Wang, and Toshihiko Yamasaki. Attention-based Multimodal Neural Network for Automatic Evaluation of Press Conferences. International Journal of Multimedia Data Engineering and Management, vol. 11, issue 3, pp. 1-19, 2020. [URL]
[Oral, with review]
3. Shengzhou Yi, Koshiro Mochitomi, Isao Suzuki, Xueting Wang, and Toshihiko Yamasaki. Attention-based LSTM for Automatic Evaluation of Press Conferences. In IEEE Third International Conference on Multimedia Information Processing and Retrieval (MIPR 2020), pp. 187-192, Aug. 6-8, 2020, Shenzhen, China. [URL]
4. Shengzhou Yi, Xueting Wang, and Toshihiko Yamasaki. Emotion and Theme Recognition of Music Using Convolutional Neural Networks. In MediaEval Benchmark Workshop (MediaEval 2019), Oct. 27-29, 2019, Sophia Antipolis, France.
5. Shengzhou Yi, Xueting Wang, and Toshihiko Yamasaki. Impression Prediction of Oral Presentation using LSTM and Dot-product Attention Mechanism. In IEEE Fifth International Conference on Multimedia Big Data (BigMM 2019), pp. 242‒246, Sep. 11-13, 2019, Singapore. [URL]
[Demo, with review]
6. Shengzhou Yi, Junichiro Matsugami, Hiroshi Yumoto, and Toshihiko Yamasaki. An Online Presentation Slide Assessment System Using Visual and Semantic Segmentation Features. In Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), Demo. Feb. 7-14, 2023, Washington D.C., USA.
7. Shengzhou Yi, Hiroshi Yumoto, Xueting Wang, and Toshihiko Yamasaki. PresentationTrainer: Oral Presentation Support System for Impression-related Feedback. In Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), Demo, pp. 13644-13645. Feb. 7-12, 2020, New York, USA. [URL]
[Poster, without review]
8. Shengzhou Yi, Xueting Wang, and Toshihiko Yamasaki. Impression Prediction of Oral Presentation using LSTM and Dot-product Attention Mechanism. Third International Workshop on Symbolic-Neural Learning (SNL-2019), P-16, Jul. 11-12, 2019, Tokyo, Japan.
9. Chen Fu, Yuesong Liu, Naoto Tanji, Hiroyuki Seshime, Shengzhou Yi, Ling Xiao, and Toshihiko Yamasaki. Constrained Advertisement Layout Generation based on Graph Neural Networks. Meeting on Image Recognition and Understanding (MIRU), Aug. 6-9, 2024, Kumamoto.
10. Tomoya Sugihara, Shuntaro Masuda, Shengzhou Yi, and Toshihiko Yamasaki. Price Prediction of Handmade Items using Multimodal Data. Image Engineering Technical Group (IE), IEICE Technical Report, Jun. 6-7, 2024, Niigata.
11. Shengzhou Yi, Toshiaki Yamasaki, and Toshihiko Yamasaki. AEnhancing Online Structured Job Interviews: A Comprehensive Personality Assessment Using Multimodal Neural Networks. Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), May 28-31, 2024, Hamamatsu.
12. Shengzhou Yi, Toshiaki Yamasaki, and Toshihiko Yamasaki. Online Structured Job Interview Assessment Using Multimodal Transformer and Prompt Learning. Media Experience Virtual Environment (MVE), vol. 123, no. 228, pp. 34-39, Oct. 26-27, 2023, Muroran.
13. Shengzhou Yi, Junichiro Matsugami, Takuya Yamamoto, Yukiyoshi Katsumizu, and Toshihiko Yamasaki. Online Presentation Skill Training Systems Using Multi-Modal Neural Network. Meeting on Image Recognition and Understanding (MIRU), Demo-10, Jul. 25-28, 2023, Hamamatsu.
14. Shengzhou Yi, Toshiaki Yamasaki, and Toshihiko Yamasaki. An Assessment System of Online Structured Job Interviews Supported by Multi-Modal Deep Learning. Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), Jun. 6-9, 2023, Kumamoto.
15. Shengzhou Yi, Junichiro Matsugami, Takuya Yamamoto, Yukiyoshi Katsumizu, and Toshihiko Yamasaki. A Presentation Training System Based on Multi-modal Neural Networks. Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), Jun. 6-9, 2023, Kumamoto.
16. Shengzhou Yi, Toshiaki Yamasaki, and Toshihiko Yamasaki. Assessment System of Remote Structured Interview using Bimodal Neural Network. Image Engineering Technical Group (IE), IEICE Technical Report, Feb. 21-22, 2023, Sapporo.
17. Shengzhou Yi, Junichiro Matsugami, and Toshihiko Yamasaki. Presentation Slide Assessment System using Visual and Semantic Segmentation Features. Media Experience Virtual Environment (MVE), vol. 122, no. 175, pp. 16-21, Sep. 8-9, 2022, Tokyo.
18. Shengzhou Yi, Junichiro Matsugami, and Toshihiko Yamasaki. Presentation Slide Design Evaluation using Two-Level Vision Transformer. Meeting on Image Recognition and Understanding (MIRU), IS2-88, Jul. 25-28, 2022, Himeji.
19. Shengzhou Yi, Toshiaki Kikuchi, and Toshihiko Yamasaki. User Satisfaction Prediction for Dialogue System in Mental Health Interventions. Image Engineering Technical Group (IE), IEICE Technical Report, vol. 121, no. 374, pp. 1-6, Feb. 21-22, 2022, Sapporo.
20. Shengzhou Yi, Junichiro Matsugami, and Toshihiko Yamasaki. Identifying Design Problems of Presentation Slides using a Bimodal Neural Network. Media Experience Virtual Environment (MVE), IEICE Technical Report, vol. 121, no. 179, pp. 21-26, Sep. 17-28, 2021, Tokyo.
21. Shengzhou Yi, Li Tao, Xueting Wang, and Toshihiko Yamasaki. Class-Balanced Contrastive Pre-Training for Improving Long-Tailed Recognition. Meeting on Image Recognition and Understanding (MIRU). Jul. 27-30, 2021, Nagoya.
22. Shengzhou Yi, Junichiro Matsugami, Xueting Wang, and Toshihiko Yamasaki. Slide Design Assessment Featuring Visual and Structural Analysis. 人工知能と知識処理研究会 (AI), IEICE Technical Report, vol. 120, no. 281, pp. 13-18, Dec. 10-11, 2020, Hamamatsu.
23. Shengzhou Yi, Takuya Yamamoto, Osamu Yamamoto, Yukiyoshi Katsumizu, Hiroshi Yumoto, Xueting Wang, Toshihiko Yamasaki. Make Your Presentation Better: Oral Presentation Support System using Linguistic and Acoustic Features. Image Engineering Technical Group (IE), IEICE Technical Report, vol. 119, no. 421, pp. 317-322, Feb. 27-28, 2020, Sapporo.
24. Shengzhou Yi, Xueting Wang, and Toshihiko Yamasaki. CNN-based Music Emotion and Theme Recognition Featuring Shallow Architecture. Media Experience Virtual Environment (MVE), IEICE Technical Report, vol. 119, no. 386, pp. 99-100, Jan. 23-24, 2020, Nara.
25. Shengzhou Yi, Koshiro Mochitomi, Isao Suzuki, Xueting Wang, Toshihiko Yamasaki. Automatic Evaluation of Press Conferences Using LSTM with Self-Attention Mechanism. Human Communication Group (HCG) Symposium, Dec. 11-13, 2019, Hiroshima.
26. Shengzhou Yi, Wang Xueting, and Yamasaki Toshihiko. Impression Prediction of Oral Presentation Using LSTM with Dot-product Attention Mechanism. Media Experience Virtual Environment (MVE), IEICE Technical Report, vol. 119, no. 75, pp. 1-6, Jun. 10-11, 2019, Tokyo.
27. Shengzhou Yi, Toshihiko Yamasaki, Izumi Masumura, Yoshinori Yasui, Takako Misaki, Nobuhiko Okabe. Prediction of the National Epidemiological Surveillance of Infectious Diseases Using LSTM. Image Media Processing Symposium (IMPS), P-1-11, Nov. 19-21, 2018, Gotemba.
