# Hong W.

> Software Engineer at Meta

Location: Sunnyvale, California, United States
Profile: https://flows.cv/hongw

## Work Experience
### Staff Software Engineer @ Meta
Jan 2024 – Present | Menlo Park, CA
Meta’s GPU-native retrieval and ranking stack

### Apache HAWQ PMC Member &  Committer @ The Apache Software Foundation
Jan 2016 – Present

### Staff Software Engineer @ Alibaba Group
Jan 2018 – Jan 2024 | Sunnyvale, California
Database and Storage Lab in Alibaba DAMO Academy. Focus on Database Performance Optimization, Database Tuning and Database Diagnose boosted by AI models. Check out part of my published work:

- An Efficient Transfer Learning Based Configuration Adviser for Database Tuning (VLDB 2024)
- A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning (SIGMOD 2023)
- Towards Dynamic and Safe Configuration Tuning for Cloud Databases (SIGMOD 2022)
- ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases (SIGMOD 2021)
- Leaper: A Learned Prefetcher for Cache Invalidation in LSM-tree based Storage Engines (VLDB 2020)

### Engineering Manager(Founding Engineer) @ Petuum, Inc.
Jan 2016 – Jan 2018 | Pittsburgh
Petuum is one of the top startups in the first wave of AI. I led a team building a AI product on the cloud called Symphony. The backend is our in-house developed distributed training/inference infra, leveraging parameter servers, SSP and clippers. I was also contributing to the distributed training forked from TensorFlow v0.8, Serving, DyNet framework(which is earlier than PyTorch).

### Senior Member of Technical Staff @ Pivotal Software, Inc.
Jan 2015 – Jan 2016
DB kernel developer, worked on the Open-Source Apache project HAWQ: distributed SQL Engine on Hadoop.
- Design and implement the HAWQ register feature
- Design and implement external ORC format support, FDW feature for HAWQ
- Implement the new feature test framework for HAWQ
- Top #3 committer

### Senior Algorithm Engineer @ Douban
Jan 2013 – Jan 2015 | Beijing City, China
- Build distributed Machine Learning libraries.
- Develop computational infrastructure and tools.
- Optimize recommendation systems and machine learning applications.

Owner of the Paracel project, which is a framework for distributed machine learning (Flexible user-defined function in server end, Highly scalable).

Owner of the Plato project, which is a Real-time Recommendation System based on Factor Model
- Design a 3-layer(Online/Nearline/Offline) backends system
- Implement variant of Balltree(dot product supported) for online retrieval
- Real-time training model, improve completion rate of douban.fm by 5%-8%

### Algorithm Engineer Intern @ Douban
Jan 2012 – Jan 2012 | Beijing City, China
Research and implement parallel SVD algorithm

### System Engineer Intern @ Yahoo! Inc.
Jan 2012 – Jan 2012


## Education
### Computer Science
Tsinghua University


## Contact & Social
- LinkedIn: https://linkedin.com/in/hongwu-xunzhang
- Portfolio: http://xunzhangthu.org

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Source: https://flows.cv/hongw
JSON Resume: https://flows.cv/hongw/resume.json
Last updated: 2026-04-12