Featured open-source project
NeuG
A graph-native data engine for agentic applications. Graph, vector, and full-text retrieval over the same transactional data, embedded in your application or running as a service.
Researcher & engineer · Graphs / Data / AI
Building systems that make
connected data useful.
Staff Engineer at Token Foundry. My work spans graph databases, distributed processing, query optimization, and applications of large language models.
01 / Engineering
Featured open-source project
A graph-native data engine for agentic applications. Graph, vector, and full-text retrieval over the same transactional data, embedded in your application or running as a service.
Graph Database / Query Language
GOpt is built on top of a unified intermediate representation (IR) that is capable of capturing both graph and relational operations, thereby streamlining the optimization of graph queries.
Graph Database / Distributed System
We develop GLogS system, allowing users to interactively submit queries using a declarative language, which will be compiled and automatically optimized, and eventually executed on the GAIA dataflow engine.
Distributed System / Query Execution Engine
GAIA (former name, Pegasus) is a distributed data-parallel compute engine based on the cyclic dataflow computation model. GAIA serves as the computation engine, lying at the core of the GraphScope system. Users can construct the computation via a directed acyclic graph (DAG), and easily run the job on their laptop or even a distributed environment across a cluster of computers.
Graph Database / Graph Pattern Matching
GraphScope Interactive is a specialized construction of GraphScope Flex, designed to handle concurrent graph queries at an impressive speed. Its primary goal is to process as many queries as possible within a given timeframe, emphasizing a high query throughput rate.
Graph Database / Distributed System
To develop a graph pattern matching system in the distributed context, while gluing together the academic results of optimal join algorithms and industrial efforts of query language
02 / Research
ACM SIGMOD/PODS International Conference on Management of Data 2025 (to appear)
ACM SIGMOD/PODS International Conference on Management of Data 2025, Demo Paper (to appear)
ACM SIGMOD/PODS International Conference on Management of Data 2024
USENIX Annual Technical Conference (ATC) 2023
18th USENIX Symposium on Networked Systems Design and Implementation
03 / Notes
04 / Background
Dr. Longbin (Robin) Lai obtained his Bachelor’s and Master’s degrees from Shanghai Jiao Tong University (SJTU) in 2010 and 2013, respectively. He then pursued his Ph.D. studies in the Database Group at the School of Computer Science and Engineering (CSE), University of New South Wales (UNSW), Sydney, under the supervision of Prof. Xuemin Lin and Prof. Lu Qin. He completed his Ph.D. in March 2017, and his thesis is available here. Dr. Lai joined Alibaba to develop large-scale graph data analytics systems for its e-commerce platform. He is also a lead contributor to the open-source project GraphScope. His work includes GAIA, a distributed dataflow system for large-scale graph queries; GLogS, a distributed interactive pattern matching system; and GOpt, a unified graph query optimization framework. Currently, he is a member of Token Foundry, where he leads research and development initiatives focusing on innovative applications of Large Language Models (LLMs).
Education
Research interests
Big Data Management · Graph Database · Distributed Processing · Query Optimizations · Large Language Models
Get in touch
Ideas, projects, and life beyond the code.
Follow along, or drop me a message.
Xiaohongshu
Scan to follow my notes on AI and everyday life.