8 citations · 14 across the 13 of their papers we have counts for
13 papers
iFVS: Towards Instance-Optimized Filtered Vector Search
Abdullah Al-Mamun, Yeasir Rayhan, Walid G. Aref
Filtered vector search (FVS) is increasingly important in modern AI + DB systems, where vector similarity search is combined with relational predicates. Quantization plays a vital…
Virtual-Memory Assisted Buffer Management In Tiered Memory
Yeasir Rayhan, Walid G. Aref
Tiered memory architectures have gained significant traction in the database community in recent years. In these architectures, the on-chip DRAM of the host processor is typically…
Gen-DBA: Generative Database Agents
Yeasir Rayhan, Walid G. Aref
Leveraging Machine Learning to optimize database systems, referred to as Machine Learning for Databases (ML4DB, for short), dates back to the early 1990s, spanning indexing techniq…
An Empirical Survey and Benchmark of Learned Distance Indexes for Road Networks
Gautam Choudhary, Libin Zhou, Yeasir Rayhan +1
The calculation of shortest-path distances in road networks is a core operation in navigation systems, location-based services, and spatial analytics. Although classical algorithms…
Lightning Prediction under Uncertainty: DeepLight with Hazy Loss
Md Sultanul Arifin, Abu Nowshed Sakib, Yeasir Rayhan +1
Lightning, a common feature of severe meteorological conditions, poses significant risks, from direct human injuries to substantial economic losses. These risks are further exacerb…
Exploring Next Token Prediction For Optimizing Databases
Yeasir Rayhan, Walid G. Aref
The Next Token Prediction paradigm (NTP, for short) lies at the forefront of modern large foundational models that are pre-trained on diverse and large datasets. These models gener…
Revisiting Page Migration for Main-Memory Database Systems
Yeasir Rayhan, Walid G. Aref
Modern hardware architectures, e.g., NUMA servers, chiplet processors, tiered and disaggregated memory systems have significantly improved the performance of Main-Memory Databases,…
P-MOSS: Scheduling Main-Memory Indexes Over NUMA Servers Using Next Token Prediction
Yeasir Rayhan, Walid G. Aref
Ever since the Dennard scaling broke down in the early 2000s and the frequency of the CPUs stalled, vendors have started to increase the core count in each CPU chip at the expense…
Deep Learning Based Crime Prediction Models: Experiments and Analysis
Rittik Basak Utsha, Muhtasim Noor Alif, Yeasir Rayhan +2
Crime prediction is a widely studied research problem due to its importance in ensuring safety of city dwellers. Starting from statistical and classical machine learning based crim…
GTX: A Write-Optimized Latch-free Graph Data System with Transactional Support -- Extended Version
Libin Zhou, Lu Xing, Yeasir Rayhan +1
This paper introduces GTX, a standalone main-memory write-optimized graph data system that specializes in structural and graph property updates while enabling concurrent reads and…
SIMD-ified R-tree Query Processing and Optimization
Yeasir Rayhan, Walid G. Aref
The introduction of Single Instruction Multiple Data (SIMD) instructions in mainstream CPUs has enabled modern database engines to leverage data parallelism by performing more comp…
ILX: Intelligent "Location+X" Data Systems (Vision Paper)
Walid G. Aref, Ahmed M. Aly, Anas Daghistani +3
Due to the ubiquity of mobile phones and location-detection devices, location data is being generated in very large volumes. Queries and operations that are performed on location d…
AIST: An Interpretable Attention-based Deep Learning Model for Crime Prediction
Yeasir Rayhan, Tanzima Hashem
Accuracy and interpretability are two essential properties for a crime prediction model. Because of the adverse effects that the crimes can have on human life, economy and safety,…