Kevin Seppi

Kevin Seppi

Brigham Young University

H-index: 34

North America-United States

About Kevin Seppi

Kevin Seppi, With an exceptional h-index of 34 and a recent h-index of 19 (since 2020), a distinguished researcher at Brigham Young University, specializes in the field of Human Computer Interaction, Natural Language Processing, Machine Learning, Graphical Models, and Optimization.

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

Understanding the Roles of Video and Sensor Data in the Annotation of Human Activities

Dispensing with humans in human-computer interaction research

When to use multi-task learning vs intermediate fine-tuning for pre-trained encoder transfer learning

Metalearning using structure-rich pipeline representations for improved AutoML

Exploring the Relationship Between Algorithm Performance, Vocabulary, and Run-Time in Text Classification

The rJokes dataset: a large scale humor collection

Digging into user control: perceptions of adherence and instability in transparent models

Can humor prediction datasets be used for humor generation? humorous headline generation via style transfer

Kevin Seppi Information

University

Position

Professor of Computer Science

Citations(all)

3671

Citations(since 2020)

1217

Cited By

2968

hIndex(all)

34

hIndex(since 2020)

19

i10Index(all)

72

i10Index(since 2020)

33

Email

University Profile Page

Brigham Young University

Google Scholar

View Google Scholar Profile

Kevin Seppi Skills & Research Interests

Human Computer Interaction

Natural Language Processing

Machine Learning

Graphical Models

and Optimization

Top articles of Kevin Seppi

Title

Journal

Author(s)

Publication Date

Understanding the Roles of Video and Sensor Data in the Annotation of Human Activities

International Journal of Human–Computer Interaction

Michael Jones

Courtni Byun

Naomi Johnson

Kevin Seppi

2022/8/1

Dispensing with humans in human-computer interaction research

Courtni Byun

Piper Vasicek

Kevin Seppi

2023/4/19

When to use multi-task learning vs intermediate fine-tuning for pre-trained encoder transfer learning

arXiv preprint arXiv:2205.08124

Orion Weller

Kevin Seppi

Matt Gardner

2022/5/17

Metalearning using structure-rich pipeline representations for improved AutoML

International Journal of Data Analysis Techniques and Strategies

Brandon Schoenfeld

Kevin Seppi

Christophe Giraud-Carrier

2022

Exploring the Relationship Between Algorithm Performance, Vocabulary, and Run-Time in Text Classification

arXiv preprint arXiv:2104.03848

Wilson Fearn

Orion Weller

Kevin Seppi

2021/4/8

The rJokes dataset: a large scale humor collection

Orion Weller

Kevin Seppi

2020/5

Digging into user control: perceptions of adherence and instability in transparent models

Alison Smith-Renner

Varun Kumar

Jordan Boyd-Graber

Kevin Seppi

Leah Findlater

2020/3/17

Can humor prediction datasets be used for humor generation? humorous headline generation via style transfer

Orion Weller

Nancy Fulda

Kevin Seppi

2020/7

You don’t have time to read this: An exploration of document reading time prediction

Orion Weller

Jordan Hildebrandt

Ilya Reznik

Christopher Challis

E Shannon Tass

...

2020/7

See List of Professors in Kevin Seppi University(Brigham Young University)

Co-Authors

H-index: 50
Jordan Boyd-Graber

Jordan Boyd-Graber

University of Maryland, Baltimore

H-index: 49
Michael A. Goodrich

Michael A. Goodrich

Brigham Young University

H-index: 46
Leah Findlater

Leah Findlater

University of Washington

H-index: 38
Tony Martinez

Tony Martinez

Brigham Young University

H-index: 29
David Wingate

David Wingate

Brigham Young University

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