About me.

I'm a Research Engineer at Google DeepMind.

I've defended my Ph.D. in Computer Science from Purdue, where I am very fortunate to work with Samuel D. Conte Distinguished Professor Elisa Bertino. 

My research interests include Data Management for LLMs and their applications in various domains (such as Agent Memory, Retrieval, and Recommendation Systems). A key question here is how systems can effectively leverage databases and LLMs together. My recent research includes:

• Serverless vector data management for RAG retrieval workloads: Vexless @SIGMOD 2024

• Semantic file systems within OS: LLM-based Semantic File System for AIOS @ICLR 2025

• Causal Cascade Updates in Relational Databases with LLMs: Castle @EMNLP 2025

• Efficient LLM Memory integrated in Google ADK: @? 2026 - to be revealed soon, stay tuned!

I’ve worked across both research and production environments at Meta, Tursio, Amazon, and Microsoft Research, where I worked on scalable systems and LLM-data applications. Before my Ph.D. journey, I got my Bachelor's degree from Sun Yat-sen University in 2022. During my undergrad, I also worked as a research intern at Microsoft Research Asia and SAP Labs. 

Please don't hesitate to reach out to me if you are interested in a discussion or collaboration.

Thanks to the easygoing upbringing my family and alma mater gave me, I have a bunch of hobbies, like hitting the trails and snapping some pics. I used to practice Nunchucks, Karate, and Taekwondo, but those kicks, including my favorite, Taegeuk Pal Jang, have slipped my mind over the years. To know more about me, please have a brief glimpse of my Miscs and my Adventures. 

By the way, I love chocolate, especially dark chocolate from South America and Africa.

News:

• I've joined Google DeepMind as a Research Engineer.

• I have successfully defended my Ph.D. thesis. Thanks to my advisor and my Ph.D. committee.

• Our work done at Meta: Modernizing Facebook Scoped Search: Keyword and Embedding Hybrid Retrieval with LLM Evaluation is now available on Arxiv! Many thanks to my team and leadership!

• [Paper accepted to EMNLP 2025] Our work "Castle: Causal Cascade Updates in Relational Databases with Large Language Models" is accepted to EMNLP 2025 Main Conference, many thanks to my collaborators and my advisor! 

• Started my internship at ᵃ⤻ᶻ Amazon this fall semester.

• I've passed my Ph.D. prelim exam, many thanks to my advisor for her continued support!

• Started my internship at ♾️ Meta this summer.

• Served as a shadow PC of Eurosys 2026.

• Served as a shadow PC of VLDB 2026.

• Served as a reviewer of COLM 2025.

• Served as a reviewer of NeurIPS 2025.

• [Paper accepted to ICLR 2025] Our work "From Commands to Prompts: LLM-based Semantic File System" is accepted to ICLR 2025, many thanks to my collaborators!

• Served as a reviewer of ACL 2025.

• Served as a reviewer of ICML 2025.

• Served as a reviewer of AISTATS 2025. 

• Served as a reviewer of SIGKDD 2025.

• Served as a reviewer of ICLR 2025.

• I'm very honored to receive the invitation from ACM to become an ACM member. My ACM page.

• Served as a reviewer of NeurIPS 2024.

• Participated as an AE committee of EuroSys 25' (Spring Round)!

• Started my internship at Tursio.ai, working with a group of sharp minds in Azure databases and making great innovations… of course, I’m on vector databases.

• I'm grateful to receive the ACM SIGMOD 2024 Student Scholarship!

• I'm grateful to receive the NSF ICDE Travel Award!

• I will present my work to some DB/ML/AI/LLM companies 🎤, feel free to reach out if you are also interested.

• [Paper accepted to SIGMOD 2024] Our work "Vexless: A Serverless Vector Data Management System Using Cloud Functions" is accepted to SIGMOD 2024, can't wait to see you all in Santiago, Chile! 🇨🇱 My deepest gratitude to my collaborators!

• Participated as an AE committee at EuroSys 24' (Autumn Round)!

• [Google Cloud Next 24'] Grateful to receive Datawhale & Google's generous support to attend Google Cloud Next '24 (Apr 9-11), looking forward to seeing how databases can better serve Generative AI, see you in Vegas 🎰!

• Participated as an AE committee at EuroSys 24' (Spring Round)!

• My first 1st author paper was accepted! Many thanks to my collaborators!

Talks & Interviews:

• Omni-structured data management for LLMs, indexing, retrieval, and reasoning, invited talk at Snowflake.

• The first serverless vector search, oral presentation at SIGMOD 2024, Santiago, Chile 🇨🇱.

• "Serverless Vector Database on Cloud Functions", invited talk at FedML.

• "Cloud Techniques & Challenges", interview by Google & SegmentFault. (Video available@Google CN)