Tieying Zhang
Pittsburgh, Pennsylvania, United States
Summary
🤩
RockstarTieying Zhang is a Research Director and systems-for-AI specialist with 11 years of experience building deployable, theory-grounded database and infrastructure solutions across academia and industry. After a postdoc at CMU focused on self-driving DBMS and AI-powered transaction scheduling, she contributed to production-grade systems such as Peloton, Apache Trafodion, PolarDB-X and DAS while serving research and leadership roles at Alibaba and ByteDance. Her work spans AI-for-systems (AI4DB, AI4storage, AI4OS, AI4Infra) and the reverse—systems that scale AI—combining rigorous research with pragmatic implementations. A program committee member for SIGMOD, ICDE and VLDB, she brings both publication-level rigor and product-minded engineering to large-scale distributed databases. Based in Sunnyvale, she is known for translating complex scheduling and many-core optimization research into real-world DBMS features.
11 years of coding experience
Github Skills (27)
rdbms10
database-management10
database10
domino9
dbms9
hbase8
transaction7
hashmap7
hash7
java6
transactional6
socket5
multithreading5
concurrent5
nanomsg4
Programming languages (4)
Github contributions (5)
Michael-Tieying-Zhang/peloton
Nov 2016 - Mar 2017
Contributions:5 PRs, 58 pushes, 4 branches in 3 months
management-systemdatabase-management-systemself-drivingdatabasedatabase-management
domino-succ/tpcc-hbase
Aug 2015 - Oct 2015
Contributions:4 PRs, 4 pushes, 1 comment in 2 months
benchmarkingrdbmstraditionalsqlruns
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