Wei-Yao Wang

Wei-Yao Wang

Research Scientist || Data Enthusiast

Wei-Yao Wang’s Homepage

My name is Wei-Yao Wang (王威堯 in Chinese). I am a research scientist at Sony, working on multimodal foundation models. I received my Ph.D. and BSc degrees from National Yang Ming Chiao Tung University and National Chiao Tung University in Taiwan respectively, advised by Prof. Wen-Chih Peng. During his academic journey, Dr. Wang served as a visiting researcher at the ScAi lab advised by Prof. Wei Wang at the University of California, Los Angeles. He was a research intern at Document AI in Microsoft in Seattle and Microsoft AI R&D Center in Taipei advised by Paul Hsu, working on low-resource field extractions from multi-modal documents with LLMs.

My research intersts include Large Foundation Models, Natural Language Processing, Sport Science, and Representation Learning, which has been published more than 30 papers in international journals and major peer-reviewed conference proceedings, including multiple best paper awards. I serve on the program committees of international conferences including ICLR, AAAI, ACL ARR, KDD, IJCAI, CIKM, and PAKDD and workshop organizers (IT4PSS 23-24, SocialNLP 22).

For more information, please visit my CV. I am also open to research collaboration. Please drop me an email if you are interested in.

Education

  • [Sep. 2020 - Mar. 2024] Ph.D. at Institute of Computer Science and Engineering, National Yang Ming Chiao Tung University (advisor: Prof. Wen-Chih Peng)
  • [Mar. 2023 - Mar. 2024] Visiting Researcher in Scalable Analytics Institute, University of California, Los Angeles (advisor: Prof. Wei Wang)
  • [Sep. 2016 - Jun. 2020] B.S. in Department of Computer Science, National Chiao Tung University

Research Experience

  • [Sep. 2024 - Present] Research Scientist, Sony Group Corporation
  • [Jul. 2020 - Mar. 2024] Ph.D. Researcher, Advanced Database System Laboratory, NYCU
  • [Mar. 2023 - Mar. 2024] Visiting Researcher, Scalable Analytics Institute, UCLA
  • [Sep. 2023 - Dec. 2023] Research Intern, Microsoft (Document AI)
  • [May 2022 - Nov. 2022] Research Intern, Microsoft AI R&D Center (Document AI)
  • [Jun. 2018 - Jun. 2022] Project Lead & Research Scientist, Precision Sport Science - Coach AI in Badminton (project link)
  • [Jul. 2018 - Jun. 2020] Database Administrator, NCTU CS Curriculum Assistant

Publications

Preprints

  1. Ching Chang, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen, “LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters”. [preprint]
  2. Wei-Yao Wang, Wen-Chih Peng, Wei Wang, Philip Yu, “ShuttleSHAP: A Turn-Based Feature Attribution Approach for Analyzing Forecasting Models in Badminton”. [preprint]

Journals and Conferences

  1. Wei-Yao Wang, Wei-Wei Du, Derek Xu, Wei Wang, Wen-Chih Peng, “A Survey on Self-Supervised Learning for Non-Sequential Tabular Data”, The 16th Asian Conference on Machine Learning (ACML), 2024. [paper]
  2. Wei-Yao Wang*, Xiusi Chen*, Ziniu Hu, David Reynoso, Kun Jin, Mingyan Liu, P. Jeffrey Brantingham, Wei Wang, “Professional Basketball Player Behavior Synthesis via Planning with Diffusion”, 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024 (acceptance rate: 33.3%). [paper]
  3. Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng, “Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion”, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2024 (acceptance rate: 24.5%). [paper]
  4. Wei-Yao Wang, Wei-Wei Du, Wen-Chih Peng, “Benchmarking Stroke Forecasting with Stroke-Level Badminton Dataset”, 33rd International Joint Conference on Artificial Intelligence (IJCAI Demo), 2024. [paper]
  5. Ching Chang, Chiao-Tung Chan, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen, “TimeDRL: Disentangled Representation Learning for Multivariate Time-Series”, IEEE International Conference on Data Engineering (ICDE), 2024. [paper]
  6. Chih-Chia Li, Wei-Yao Wang, Wei-Wei Du, Wen-Chih Peng, “Look Around! A Neighbor Relation Graph Learning Framework for Real Estate Appraisal”, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024. [paper]
  7. Wei-Yao Wang, Yu-Chieh Chang, Wen-Chih Peng, “Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection”, 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2024 (acceptance rate: 20.3%). [paper]
  8. Zheng-Ming Lin, Ching Chang, Wei-Yao Wang, Kuang-Da Wang, Wen-Chih Peng, “Root Cause Analysis In Microservice Using Neural Granger Causal Discovery”, 38th AAAI Conference on Artificial Intelligence (AAAI), 2024 (acceptance rate: 23.75%). [paper]
  9. Ying-Ying Chang, Wei-Yao Wang, Wen-Chih Peng, “SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter”, 38th AAAI Conference on Artificial Intelligence (AAAI), 2024 (acceptance rate: 23.75%). [paper]
  10. Kuang-Da Wang, Yu-Tse Chen, Yu-Heng Lin, Wei-Yao Wang, Wen-Chih Peng, “The CoachAI Badminton Environment: Bridging the Gap Between a Reinforcement Learning Environment and Real-World Badminton Games”, 38th AAAI Conference on Artificial Intelligence (AAAI Demo), 2024. [paper]
  11. Kuang-Da Wang, Wei-Yao Wang, Yu-Tse Chen, Yu-Heng Lin, Wen-Chih Peng, “The CoachAI Badminton Environment: A Novel Reinforcement Learning Environment with Realistic Opponents (Student Abstract)”, 38th AAAI Conference on Artificial Intelligence (AAAI), 2024. [paper]
  12. Yu-Chien Tang, Wei-Yao Wang, An-Zi Yen, Wen-Chih Peng, “RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training”, 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), 2023. [paper]
  13. Wei-Wei Du, Wei-Yao Wang, Wen-Chih Peng, “DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal”, 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023 (acceptance rate: 32%). [paper]
  14. Wei-Yao Wang, Yung Chang Huang, Tsi-Ui Ik, Wen-Chih Peng, “ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis”, 29TH ACM SIGKDD Conference On Knowledge Discovery And Data Mining (KDD), 2023 (acceptance rate: 25.4%). [paper]
  15. Kai-Shiang Chang, Wei-Yao Wang, Wen-Chih Peng, “Where Will Players Move Next? Dynamic Graphs and Hierarchical Fusion for Movement Forecasting in Badminton”, 37th AAAI Conference on Artificial Intelligence (AAAI), 2023 (acceptance rate: 19.6%). [paper]
  16. Li-Chun Huang, Nai-Zen Hseuh, Yen-Che Chien, Wei-Yao Wang, Kuang-Da Wang, Wen-Chih Peng, “A Reinforcement Learning Badminton Environment for Simulating Player Tactics (Student Abstract)”, 37th AAAI Conference on Artificial Intelligence (AAAI), 2023. [paper]
  17. Wei-Yao Wang, “Modeling Turn-Based Sequences for Player Tactic Applications in Badminton Matches”, 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. [paper]
  18. Wei-Yao Wang, Teng-Fong Chan, Wen-Chih Peng, Hui-Kuo Yang, Chih-Chuan Wang, Yao-Chung Fan, “How Is the Stroke? Inferring Shot Influence in Badminton Matches via Long Short-Term Dependencies”, ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 14, No. 1, pp1-22, 2022. [paper]
  19. Wei-Yao Wang, Hong-Han Shuai, Kai-Shiang Chang, Wen-Chih Peng, “ShuttleNet: Position-Aware Fusion of Rally Progress and Player Styles for Stroke Forecasting in Badminton”, 37th AAAI Conference on Artificial Intelligence (AAAI), 2022 (acceptance rate: 15%). [paper]
  20. Wei-Yao Wang, Teng-Fong Chan, Hui-Kuo Yang, Chih-Chuan Wang, Yao-Chung Fan, Wen-Chih Peng, “Exploring the Long Short-Term Dependencies to Infer Shot Influence in Badminton Matches”, The 21st IEEE International Conference on Data Mining (ICDM), 2021 (acceptance rate: 20%). [paper]
  21. Wei-Yao Wang, Kai-Shiang Chang, Teng-Fong Chen, Chih-Chuan Wang, Wen-Chih Peng, Chih-Wei Yi, “Badminton Coach AI: A badminton match data analysis platform based on deep learning”, Physical Education Journal, vol.53, no.2, pp.201–213, 2020. [paper]

Workshops

  1. Ching Chang, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen, Sagar Samtani, “Align and Fine-Tune: Enhancing LLMs for Time-Series Forecasting”, NeurIPS 2024 on Time Series in the Age of Large Models.
  2. Ching Chang, Chan Chiao-Tung, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen, “Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series”, NeurIPS 2024 on Self-Supervised Learning - Theory and Practice.
  3. Kuang-Da Wang, Yu-Tse Chen, Yu-Heng Lin, Wei-Yao Wang, Wen-Chih Peng, “The CoachAI Badminton Environment: Improving Badminton Player Tactics with A Novel Reinforcement Learning Environment”, ACM SIGKDD Workshop on on Data Science and AI for Sports, 2023.
  4. Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng, “Generating Turn-Based Player Behavior via Experience from Demonstrations”, ICML 2023 Workshop on Structured Probabilistic Inference & Generative Modeling, 2023. [paper]
  5. Chih-Chia Li, Wei-Yao Wang, Wei-Wei Du, Wen-Chih Peng, “Look Around! A Neighbor Relation Graph Learning Framework for Real Estate Appraisal”, AAAI Workshop on Modelling Uncertainty in the Financial World, 2023 (Best paper award). [paper]
  6. Wei-Wei Du, Hong-Wei Wu, Wei-Yao Wang, Wen-Chih Peng, “Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification”, AAAI Workshop on Multimodal Fact Checking and Hate Speech Detection, 2023. [paper]
  7. Wei-Wei Du, Wei-Yao Wang, Wen-Chih Peng, “Track2Vec: Fairness Music Recommendation with a GPU-Free Customizable-Driven Framework”, CIKM Workshop on A Rounded Evaluation of Recommender Systems, 2022. [paper]
  8. Wei-Yao Wang, Wei-Wei Du, Wen-Chih Peng, “RecFormer: Personalized Temporal-Aware Transformer for Fair Music Recommendation”, CIKM Workshop on A Rounded Evaluation of Recommender Systems, 2022. [paper]
  9. Lun-Wei Ku, Cheng-Te Li, Yu-Che Tsai, Wei-Yao Wang, “Proceedings of the Tenth International Workshop on Natural Language Processing for Social Media (SocialNLP 2022)”, NAACL Workshop on International Workshop on Natural Language Processing for Social Media, 2022. [paper]
  10. Wei-Yao Wang*, Yu-Chien Tang*, Wei-Wei Du*, Wen-Chih Peng, “NYCU_TWD@LT-EDI-ACL2022: Ensemble Models with VADER and Contrastive Learning for Detecting Signs of Depression from Social Media”, ACL Workshop on Language Technology for Equality, Diversity, Inclusion, 2022. [paper]
  11. Lun-Wei Ku, Cheng-Te Li, Yu-Che Tsai, Wei-Yao Wang, “SocialNLP’22: 10th International Workshop on Natural Language Processing for Social Media”, WWW Workshop on Natural Language Processing for Social Media, 2022. [paper]
  12. Yu-Wun Tseng, Hui-Kuo Yang, Wei-Yao Wang, Wen-Chih Peng, “KAHAN: Knowledge-Aware Hierarchical Attention Network for Fake News Detection on Social Media”, WWW Workshop on Natural Language Processing for Social Media, 2022. [paper]
  13. Wei-Yao Wang, Wen-Chih Peng, “Team Yao at Factify 2022: Utilizing Pre-trained Models and Co-attention Networks for Multi-Modal Fact Verification”, AAAI Workshop on Multimodal Fact Checking and Hate Speech Detection, 2022 (Best Paper Award). [paper]

Honors and Awards

  1. [Dec. 2024] Dissertation Award, Taiwanese Association for Artificial Intelligence
  2. [Sep. 2023] Sports Science Research Award, Sport Administration, Ministry of Education
  3. [Aug. 2023] KDD Student Scholarship, ACM
  4. [Aug. 2023] Top Research of AI and Information Technology Scholarship, Appier
  5. [May 2023] 21st Y.Z. Hsu Science Paper Award, Far Eastern Y.Z. Hsu Foundation
  6. [Feb. 2023] AAAI Student Scholarship, AAAI
  7. [Jan. 2023] Google Conference Scholarships, Google
  8. [Jan. 2023] AAAI Student Scholarships, AAAI
  9. [Mar. 2022] Google Conference Scholarships, Google
  10. [Feb. 2022] Best Paper Award, AAAI DeFactify Workshop
  11. [Feb. 2022] AAAI Student Scholarships, AAAI
  12. [Jan. 2022] Top Research of AI and Information Technology Scholarship, Appier
  13. [Aug. 2019] The Yin Zhi Tong Memorial Scholarship, National Yang Ming Chiao Tung University
  14. [Jul. 2019] College Student Research Scholarship, Ministry of Science and Technology

Competition Awards

  1. [Dec. 2022] 1st Place in Factify 2.0 Challenge, De-Factify @ AAAI 2023 Workshop [code]
  2. [Oct. 2022] 4th Place in Rounded Evaluation of Recommender Systems, EvalRS @ CIKM’22 Workshop
  3. [Feb. 2022] 2nd Place in Detecting Signs of Depression from Social Media Text, LT-EDI @ ACL 2022 Workshop [code]
  4. [Nov. 2021] 5th Place and Best Paper Award in Factify Challenge, De-Factify @ AAAI 2022 Workshop [code]
  5. [Sep. 2021] 3rd Place and National Judges Award, Legal-Tech Hackathon 2021. [code]
  6. [Jun. 2021] 1st Place in Fake-EmoReact Challenge, SocialNLP @ NAACL 2021 Workshop [code]
  7. [Jan. 2021] Bronze Medal in Riiid Answer Correctness Prediction Challenge, AAAI 2021 Workshop [code]
  8. [Jun. 2020] 3rd Place in EmotionGIF Challenge, SocialNLP @ ACL 2020 Workshop [report, code]
  9. [Dec. 2019] Excellent Award on Research Project Competition, National Chiao Tung University

Academic Services

Conference Program Committee ICLR’25, KDD’25, AAAI (22-now), IJCAI (23-now), ACL ARR (22-now), ISACE (23-now), LT-EDI-ACL 2022 @ ACL’22

Organizer ITPSS @ IJCAI’23-24, CoachAI Challenge @ IJCAI’23, SocialNLP 2022 @ WWW’22 and NAACL’22

Student Volunteer IJCAI’23, KDD’23