J. Shane Culpepper

J. Shane Culpepper

RMIT University

H-index: 33

Oceania-Australia

About J. Shane Culpepper

J. Shane Culpepper, With an exceptional h-index of 33 and a recent h-index of 26 (since 2020), a distinguished researcher at RMIT University, specializes in the field of Information Retrieval, Search, Algorithms, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Enhancing Human Annotation: Leveraging Large Language Models and Efficient Batch Processing

Optimizing Data Acquisition to Enhance Machine Learning Performance

Advanced Dataset Discovery: When Multi-Query-Dataset Cardinality Estimation Matters

Facility relocation search for good: When facility exposure meets user convenience

Entropy-based query performance prediction for neural information retrieval systems

Updatable learned indexes meet disk-resident DBMS-From evaluations to design choices

A Simple Yet High-Performing On-disk Learned Index: Can We Have Our Cake and Eat it Too?

Representative Routes Discovery from Massive Trajectories

J. Shane Culpepper Information

University

Position

___

Citations(all)

3214

Citations(since 2020)

2082

Cited By

1921

hIndex(all)

33

hIndex(since 2020)

26

i10Index(all)

78

i10Index(since 2020)

57

Email

University Profile Page

RMIT University

Google Scholar

View Google Scholar Profile

J. Shane Culpepper Skills & Research Interests

Information Retrieval

Search

Algorithms

Machine Learning

Top articles of J. Shane Culpepper

Title

Journal

Author(s)

Publication Date

Enhancing Human Annotation: Leveraging Large Language Models and Efficient Batch Processing

Oleg Zendel

J. Shane Culpepper

Falk Scholer

Paul Thomas

2024

Optimizing Data Acquisition to Enhance Machine Learning Performance

Proceedings of the VLDB Endowment

Tingting Wang

Shixun Huang

Zhifeng Bao

J Shane Culpepper

Volkan Dedeoglu

...

2024/1/1

Advanced Dataset Discovery: When Multi-Query-Dataset Cardinality Estimation Matters

arXiv preprint arXiv:2401.00659

Tingting Wang

Shixun Huang

Zhifeng Bao

J Shane Culpepper

Reza Arablouei

...

2024/1/1

Facility relocation search for good: When facility exposure meets user convenience

Hui Luo

Zhifeng Bao

J Shane Culpepper

Mingzhao Li

Yanchang Zhao

2023/4/30

Entropy-based query performance prediction for neural information retrieval systems

Oleg Zendel

Binsheng Liu

J. Shane Culpepper

Falk Scholer

2023

Updatable learned indexes meet disk-resident DBMS-From evaluations to design choices

Proceedings of the ACM on Management of Data

Hai Lan

Zhifeng Bao

J Shane Culpepper

Renata Borovica-Gajic

2023/6/20

A Simple Yet High-Performing On-disk Learned Index: Can We Have Our Cake and Eat it Too?

arXiv preprint arXiv:2306.02604

Hai Lan

Zhifeng Bao

J Shane Culpepper

Renata Borovica-Gajic

Yu Dong

2023/6/5

Representative Routes Discovery from Massive Trajectories

Tingting Wang

Shixun Huang

Zhifeng Bao

J Shane Culpepper

Reza Arablouei

2022/8/14

Can Users Predict Relative Query Effectiveness?

Oleg Zendel

Melika P Ebrahim

J Shane Culpepper

Alistair Moffat

Falk Scholer

2022/7/6

sMARE: a new paradigm to evaluate and understand query performance prediction methods

Information Retrieval Journal

Guglielmo Faggioli

Oleg Zendel

J Shane Culpepper

Nicola Ferro

Falk Scholer

2022/6

Generalizing discriminative retrieval models using generative tasks

Binsheng Liu

Hamed Zamani

Xiaolu Lu

J Shane Culpepper

2021/4/19

Let trajectories speak out the traffic bottlenecks

ACM Transactions on Intelligent Systems and Technology (TIST)

Hui Luo

Zhifeng Bao

Gao Cong

J Shane Culpepper

Nguyen Lu Dang Khoa

2021/11/29

Bayesian system inference on shallow pools

Rodger Benham

Alistair Moffat

J Shane Culpepper

2021/3/28

Strong natural language query generation

Information Retrieval Journal

Binsheng Liu

Xiaolu Lu

J Shane Culpepper

2021/10

An enhanced evaluation framework for query performance prediction

Guglielmo Faggioli

Oleg Zendel

J.Shane Culpepper

Nicola Ferro

Falk Scholer

2021

Topic difficulty: Collection and query formulation effects

ACM Transactions on Information Systems (TOIS)

J Shane Culpepper

Guglielmo Faggioli

Nicola Ferro

Oren Kurland

2021/9/7

Different keystrokes for different folks: visualizing crowdworker querying behavior

Rodger Benham

Joel Mackenzie

J Shane Culpepper

Alistair Moffat

2021/3/14

Do Hard Topics Exist? A Statistical Analysis.

J Shane Culpepper

Guglielmo Faggioli

Nicola Ferro

Oren Kurland

2021/9

A survey on trajectory data management, analytics, and learning

Sheng Wang

Zhifeng Bao

J Shane Culpepper

Gao Cong

2021/3/5

Is query performance prediction with multiple query variations harder than topic performance prediction?

Oleg Zendel

J Shane Culpepper

Falk Scholer

2021/7/11

See List of Professors in J. Shane Culpepper University(RMIT University)

Co-Authors

H-index: 120
W. Bruce Croft

W. Bruce Croft

University of Massachusetts Amherst

H-index: 92
Jimmy Lin

Jimmy Lin

University of Waterloo

H-index: 70
Gao Cong

Gao Cong

Nanyang Technological University

H-index: 63
Timos Sellis

Timos Sellis

Swinburne University of Technology

H-index: 58
Mark Sanderson

Mark Sanderson

RMIT University

H-index: 50
Charles L. A. Clarke

Charles L. A. Clarke

University of Waterloo

academic-engine