Hongbin Zhong(钟宏斌)CS PhD Student
Georgia Institute of Technology
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Biography
I am a first-year PhD student in Computer Science at Georgia Tech, fortunate to be advised by the kind and supportive Prof. Kexin Rong.
I also closely collaborate with Prof. Ada Gavrilovska, Prof. Steve Mussmann from Gatech, as well as Dr. Nina Narodytska and Dr. Adriana Szekeres from VMware Research.
Previously, I was a research intern at Columbia University, working with Prof. Eugene Wu, where I contributed to the publication of multiple DB top-tier conference papers.
Additionally, I have extensive industry engineering experience, which you can learn more about on my LinkedIn.
Overall, my current research focuses on developing efficient and secure solutions at the intersection of machine learning and computer systems. Specifically, I am interested in systems that aim to maximize efficiency under security constraints in LLM-based applications, including but not limited to:
- Efficient and secure vector search in RAG/agentic systems
- Reliable and scalable LLM agent systems with built-in safety and robustness
- Secure and efficient LLM deployment across diverse platforms and environments
I'm always looking for industrial collaborators, please feel free to contact me if you're interested.
News
- [05/2025] I will be joining Microsoft Research as a summer intern — looking forward to seeing you in Seattle!
- [08/2024] I will begin my PhD at Georgia Tech in Atlanta — excited for the journey ahead!
Under Review
HoneyBee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning
Hongbin Zhong*, Matthew Lentz, Nina Narodytska, Adriana Szekeres, Kexin Rong
arxiv 2025
[paper]
Selected Publications
Fast Hypothetical Updates Evaluation
Haneen Mohammed*, Alexander Yao*, Charlie Summers*, Hongbin Zhong, Gromit Yeuk-Yin Chan, Sub- rata Mitra, Lampros Flokas, Eugene Wu
SIGMOD 2025 DEMO
FaDE: More Than a Million What-ifs Per Second
Haneen Mohammed*, Alexander Yao*, Charlie Summers*, Hongbin Zhong, Gromit Yeuk-Yin Chan, Sub- rata Mitra, Lampros Flokas, Eugene Wu
VLDB 2025
[code]
Accelerating Deletion Interventions on OLAP Workload
Haneen Mohammed, Alexander Yao, Lampros Flokas,Hongbin Zhong, Charlie Summers, Eugene Wu
ICDE 2024
PECJ: Stream Window Join on Disorder Data Streams with Proactive Error Compensation
Xianzhi Zeng*, Shuhao Zhang, Hongbin Zhong, Hao Zhang, Mian Lu, Zhao Zheng, Yuqiang Chen
SIGMOD 2024
Research experience
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Microsoft Research May. 2025 - Aug. 2025, Redmond, Seattle, US |
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Columbia University Jul. 2023 - Dec. 2023, New York, US closely worked with Eugene Wu Topic: Query Explanation (Answering "Why" Made Fast) |
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Rutgers University Jun. 2023 - Sep. 2023 closely worked with Dong Deng Topic: Find similar data text segment between some documents |
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Nanyang Technological University Jan. 2023 - Jul. 2023 Topic: Stream Window Join on Disorder Data Streams |
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Engineering experience
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InfiniFlow Apr. 2024 - Jun. 2024 Vector Databases Contributor Shanghai, China |
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4paradigm Feb. 2024 - Jun. 2024 Part-time Full-stack Engineer Intern |
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Meituan Apr. 2022 - Sep. 2022 Backend Engineer Intern Beijing, China |
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