Research Interests

Scalable Knowledge-Intensive Document Analysis. Harnessing multiple generative language models to perform large-scale, high-fidelity analysis of complex, knowledge-rich documents such as patents, insurance policies, and academic research papers. This research enables advanced applications, including intelligent document processing, automated content expansion, synthesis, and contextual tagging. By orchestrating multiple models in parallel, the system achieves deep contextual understanding and high analytical precision while maintaining scalability and cost-efficiency.

Education

Ph.D., Electrical Engineering, National Taiwan University, Taiwan
Thesis: "A Cost-Effective System for Real-Time Big Data Processing"
Advisor: Wanjiun Liao, PhD

M.S., Computer Science and Information Engineering, National Taiwan University, Taiwan
Thesis: "SWARM-Secure Wireless Ad-hoc network Reliance Management"
Advisor: Feipei Lai, PhD

B.S., Mathematical Sciences, National Chengchi University, Taiwan

Professional Experience

Assistant Professor, Soochow University, Taiwan

Visiting Scientist, IBM T. J. Watson Research Center, NY, USA
Advisor: Chung-Sheng Li, PhD

Senior Data Scientist, InQuartik, Taiwan

Engineer, Institute for Information Industry, Taiwan

Contact Information

No. 56, Sec. 1, Guiyang St., Zhongzheng Dist., Taipei City 100006, Taiwan

linjiun.tsai@gmail.com or linjiun.tsai@scu.edu.tw

Tel +886-2-2311-1531 ext. 3815

Fax +886-2-2375-6878