Shaofeng CAI
Scholar

Shaofeng CAI

Google Scholar ID: Nzr-hIoAAAAJ
National University of Singapore
Adaptive AIAIxDBTabular Data
Citations & Impact
All-time
Citations
1,205
 
H-index
16
 
i10-index
20
 
Publications
20
 
Co-authors
13
list available
Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • 1. [VLDB] HAKES: Scalable Vector Database for Embedding Search Service
  • 2. [ICML] In-Context Adaptation to Concept Drift for Learned Database Operations
  • 3. [ICML] NeuralCohort: Cohort-aware Neural Representation Learning for Healthcare Analytics
  • 4. [ICLR] Investigating Pattern Neurons in Urban Time Series Forecasting
  • 5. [SIGMOD] CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning
  • 6. [VLDB] Powering In-database Dynamic Model Slicing for Structured Data Analytics
  • 7. [CIDR] NeurDB: On the Design and Implementation of an AI-powered Autonomous Database
  • 8. [MM] Do LLMs Understand Visual Anomalies? Uncovering LLM Capabilities in Zero-shot Anomaly Detection
  • 9. [KDD] VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detection
  • 10. [Science China] NeurDB: An AI-powered Autonomous Data System
  • 11. [VLDB] Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems
  • 12. [VLDB] METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection
  • 13. [arXiv] Anytime Neural Architecture Search on Tabular Data
  • 14. [SIGMOD] Robust and Transferable Log-based Anomaly Detection
  • 15. [SIGMOD] Regularized Pairwise Relationship based Analytics for Structured Data
Research Experience
  • 1. Adaptive Neural Architectures and DL Techniques
  • 2. Anomaly/Fraud Detection & Data-Driven Healthcare Analytics
  • 3. Models, Techniques and Frameworks for Tabular Deep Learning
  • 4. AIxDB Techniques and Systems; In-database Analytics
Background
  • Senior Research Fellow in the Department of Computer Science, National University of Singapore. Mainly works on adaptive AI, focusing on adaptive neural architectures and deep learning techniques. Research extends to tabular deep learning, anomaly detection, and in-database analytics.