Scholar
Chih-Ya Shen (沈之涯)
Google Scholar ID: FkIpoVMAAAAJ
Professor of Computer Science, National Tsing Hua University
Citations & Impact
Citations
933
H-index
21
i10-index
31
Publications
20
Co-authors
9
list available
Contact
No contact links provided.
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- K. T. Li Cornerstone Award, 2025
- Youxian Technology Paper Award, 2024
- Young Scholar Innovation Award, Foundation for the Advancement of Outstanding Scholarship, 2022
- Pan Wen-Yuan Foundation Research Fellowship, 2021
- Outstanding Teaching Award, College of EECS, NTHU, 2020
- Outstanding Young Electrical Engineer Award, Chinese Institute of Electrical Engineering, 2019
- New Faculty Research Awards (University and College level), National Tsing Hua University, 2019
- K. T. Li Distinguished Young Scholar Award, ACM Taipei/Taiwan Chapter, 2018
- MOST Young Scholar Fellowship (Columbus Program), Ministry of Science and Technology, 2018
- Short-Term Overseas Research Grant, College of EECS, NTHU (UC Santa Barbara), 2017
- Postdoc Academic Publication Award, MOST, 2016
- PAKDD Best Runner-Up Paper Award, Ho Chi Minh City, Vietnam, 2015
- Postdoctoral Research Abroad Program Award (‘Thousand-Mile Horse’), MOST, 2015
- Graduate Students Study Abroad Program Award (‘Thousand-Mile Horse’), National Science Council, 2012
- Publications in top-tier venues including CIKM, WWW, SIGKDD, VLDB, AAAI, IEEE TKDE, ACM TKDD, EDBT, and PAKDD
Research Experience
- Leading the LoBSTeR Lab on big data analytics for mental healthcare in online social networks
- Developed the first machine learning framework to identify potential patients using only social network data, achieving 90% accuracy
- Formulated and solved the first therapy group formation problem with an approximation algorithm for timely intervention
- Proposed graph mining and ML approaches for group discovery in large social and spatial databases, applied to impromptu activities, disaster response teams, and friend-making optimization
- Conducted research on graph-based recommendation systems, blockchain-integrated federated learning, graph adversarial attacks and defenses, network compression, and neural network watermarking
- Designed the first graph generator preserving structural patterns (e.g., clustering coefficient, degree distribution), capable of generating billion-node graphs in minutes, freely available for download
