Chia-Yuan's Homepage

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611 Cowper St

Palo Alto, CA 94301

About me

I’m Chia-Yuan (Scott) Chang, an Applied Scientist at Amazon Rufus team. Before entering the industry, I was a Ph.D. student in the Department of Computer Science and Engineering at Texas A&M University, advised by Dr. Na Zou and Dr. Xia “Ben” Hu.

My research interests include Long-context extension, RAG, and Generative Model Applications.

Currently, I focus on RoPE-base context window extension training and sparse attention mechanisms, making LLMs more grounded for real-world applications.

I’m open to full-time Research Scientist or MLE opportunities. Please don’t hesitate to reach out if you are seeking a candidate for these roles.

Email: cychang at tamu dot edu

News

  • Jun. 2025: Start my full-time job as an applied scientist at Amazon Rufus team at Palo Alto, CA

  • May. 2025: One paper accepted by ACL 2025 Main: MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation

  • May. 2025: One paper accepted by KDD 2025: CODA: Temporal Domain Generalization via Concept Drift Simulator

  • Nov. 2024: Start my internship as an applied scientist intern at Amazon Rufus team at Palo Alto, CA

  • Jul. 2024: One paper accepted by TKDD

  • Jun. 2024: One paper is selected as a Spotlight Paper by ICML 2024: LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning [GitHub]

  • May 2024: Start my internship as a research intern at Visa Research at Foster City, CA

  • May 2024: Two papers accepted by ICML 2024

  • Mar. 2024: One paper accepted by NAACL 2024

  • Oct. 2023: One paper accepted by NeurIPS 2023 AI for Science Workshop

  • Oct. 2023: One paper selected as CIKM 2023 Best Demo Paper Honorable Mention

  • Oct. 2023: One paper selected as AMIA 2023 Best Student Paper Finalist

  • Aug. 2023: One paper accepted by CIKM 2023

  • Aug. 2023: Give an invited tutorial on Machine Learning in Finance Workshop at KDD 2023
    [Website][Slides][Code]

  • Jul. 2023: Two papers accepted by AMIA 2023

  • Jun. 2023: Give an invited tutorial on Fairness in Machine Learning for Healthcare at QPRC 2023

  • Jun. 2023: Receive NSF Travel Award for Quality and Productivity Research Conference (QPRC 2023)

  • Feb. 2021: One paper accepted by AAAI 2021

  • Oct. 2020: One paper accepted by TREC 2020 (2nd Place Award) [Website]