I am currently a computer science PhD working with Prof. Pandey Prashant at Northeastern University DATA Lab. I focus on building high-efficiency systems for data at scale.
Projects
-
GPU Accelerated Approximate Nearest Neighbor Search
In this project, we built a library providing an updatable index for approximate nearest neighbor search on GPU. Our goal is to efficiently scale its construction and querying beyond GPU memory, handling vector search at billion scale.
-
Adaptive Streaming System
Mechanisms and policies for efficiently scaling streaming workloads at runtime.
Publications
-
The Dangerous Impact of Solver Imprecision on Data Management Techniques (and How to Avoid It)
Zixuan Chen, Zikun Wang, Panagiotis Manolios, Mirek RiedewaldInternational Conference on Extending Database Technology (EDBT) 2027
-
[Workshop] Directional Beam Search: I/O-Efficient ANNS on GPU
Zikun Wang, Hunter McCoy, Prashant PandeyThe 2nd Workshop on Vector Databases (VecDB) 2026
-
GPU-Accelerated ANNS: Quantized for Speed, Built for Change
Hunter McCoy, Zikun Wang, Prashant PandeyInternational Conference on Very Large Data Bases (VLDB) 2026
-
CAPSys: Contention-aware task placement for data stream processing
Yuanli Wang, Lei Huang, Zikun Wang, Vasiliki Kalavri, Ibrahim MattaEuropean Conference on Computer Systems (EuroSys) 2025
Posters
- Zero-downtime reconfiguration mechanisms for dynamic data stream processing at Boston University's North East Database Day 2025. Jan 9, 2025.
- Effective Workload Scaling in Streaming System at Boston University's The 27th Annual Undergraduate Research Symposium. Oct 18, 2024.
- A Computational Platform for Visuospatial Assessment at Neuroscience of the Everyday World Conference 2024. Aug 9, 2024.
- Automatic Task Placement Decisions for High-throughput and Resource-efficient Data Stream Processing at North East Database Day 2024. May 23, 2024.
Teaching Roles
- Teaching Assistant, GRS CS 630 Graduate algorithm, Boston University, Fall 2024.
- Grader, CAS CS 320 Programming Language, Boston University, Fall 2022.
My Academic Friends
