Hi, my name is Yin Lin. I am a senior algorithm engineer at Tongyi Lab, Alibaba Group. My current research focuses on agent harness design, particularly memory systems and reasoning paradigms that enable agents to manage context, reason effectively, and execute long-horizon tasks.
Our team develops QwenPaw , a secure and extensible personal AI assistant that runs locally or in the cloud and uses Scroll Context to persist and index its full interaction history for on-demand recall. Alongside my work on agent harnesses, I also develop techniques for AI-powered data management, including semantic operators and AI agents that enhance data processing, analytics, and reasoning.
Before joining Alibaba, I earned my Ph.D. from the University of Michigan, Ann Arbor, where I was advised by Dr. H. V. Jagadish. My thesis research focused on data equity systems.
If you are interested in a research internship or collaboration, feel free to reach out!
Ph.D., Computer Science and Engineering
B.S., Computer Science
Senior Algorithm Engineer, Tongyi Lab
Research Intern, Data Management, Exploration and Mining (DMX)
Summer Intern, Software Architecture Group
I am currently exploring how AI agents can better manage, reason over, and interact with data. Here are some of my ongoing projects:
Natural language queries to databases are often ambiguous. AmbiSQL is an interactive system that detects and resolves ambiguities in text-to-SQL translation, enabling users to clarify their intent and receive accurate query results.
Semantic operators bring AI-powered data transformations to large-scale data processing pipelines. These operators are now part of Data-Juicer, enabling intelligent filtering, enrichment, and transformation of training data for foundation models.
DojoZero is an agent arena where AI agents react to real-time data streams to make predictions for sports events. It serves as a testbed for evaluating agents' capabilities in dynamic, time-sensitive decision-making scenarios.
Exploring novel agent applications for data analytics, including using LLMs for feature engineering and data engineering tasks.
VLDB 2026 (Tutorial)
SIGMOD 2026 (Demo)
IEEE Data Engineering Bulletin 2025
CoRR, 2024, Arxiv/2412.16864
ICDE 2024
CIDR 2024
SIGMOD 2023 (Best Paper Award)
ACM Computing Surveys
Highly cited survey in the field of AI fairnessVLDB 2022 (Demo)
VLDB 2022
VLDB 2020
CoRR, 2020, Arxiv/2010.08807
MLG@KDD 2020
DEXA 2018
Program Committees / Reviewers: ACL, NeurIPS, TKDE, CIKM, IEEE BigData, AIBSD (AAAI Workshop on AI with Biased or Scarce Data), ReLM (AAAI Workshop on Responsible Language Models)