Serena Booth

Serena Booth

Massachusetts Institute of Technology

H-index: 11

North America-United States

About Serena Booth

Serena Booth, With an exceptional h-index of 11 and a recent h-index of 11 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of Human-AI interaction, Reward Function Design, RLHF, Human-Robot interaction, Explainable AI.

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

Learning optimal advantage from preferences and mistaking it for reward

Building Blocks for Human-AI Alignment: Specify, Inspect, Model, and Revise

Quality-Diversity Generative Sampling for Learning with Synthetic Data

Varying How We Teach: Adding Contrast Helps Humans Learn about Robot Motions

The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications

Variable autonomy for human-robot teaming (vat)

Aligning Robot Behaviors with Human Intents by Exposing Learned Behaviors and Resolving Misspecifications

Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning

Serena Booth Information

University

Position

___

Citations(all)

455

Citations(since 2020)

438

Cited By

57

hIndex(all)

11

hIndex(since 2020)

11

i10Index(all)

11

i10Index(since 2020)

11

Email

University Profile Page

Massachusetts Institute of Technology

Google Scholar

View Google Scholar Profile

Serena Booth Skills & Research Interests

Human-AI interaction

Reward Function Design

RLHF

Human-Robot interaction

Explainable AI

Top articles of Serena Booth

Title

Journal

Author(s)

Publication Date

Learning optimal advantage from preferences and mistaking it for reward

Proceedings of the AAAI Conference on Artificial Intelligence

W Bradley Knox

Stephane Hatgis-Kessell

Sigurdur Orn Adalgeirsson

Serena Booth

Anca Dragan

...

2024/3/24

Building Blocks for Human-AI Alignment: Specify, Inspect, Model, and Revise

Serena Lynn Booth

2024

Quality-Diversity Generative Sampling for Learning with Synthetic Data

AAAI Conference on Artificial Intelligence

Allen Chang

Matthew C. Fontaine

Serena Booth

Maja J. Matarić

Stefanos Nikolaidis

2024

Varying How We Teach: Adding Contrast Helps Humans Learn about Robot Motions

HRI Human-Interactive Robot Learning Workshop

Tiffany Horter

Elena Glassman

Julie Shah

Serena Booth

2023

The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications

Proceedings of the AAAI Conference on Artificial Intelligence

Serena Booth

W Bradley Knox

Julie Shah

Scott Niekum

Peter Stone

...

2023/6/26

Variable autonomy for human-robot teaming (vat)

Manolis Chiou

Serena Booth

Bruno Lacerda

Andreas Theodorou

Simon Rothfuß

2023/3/13

Aligning Robot Behaviors with Human Intents by Exposing Learned Behaviors and Resolving Misspecifications

HRI Pioneers

Serena Booth

2023

Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning

Serena Booth

Sanjana Sharma

Sarah Chung

Julie Shah

Elena L Glassman

2022/3/7

Do Feature Attribution Methods Correctly Attribute Features?

Proceedings of the AAAI Conference on Artificial Intelligence

Yilun Zhou

Serena Booth

Marco Tulio Ribeiro

Julie Shah

2022/6/28

Models of human preference for learning reward functions

W. Bradley Knox

Stephane Hatgis-Kessell

Serena Booth

Scott Niekum

Peter Stone

...

2022

The irrationality of neural rationale models

arXiv preprint arXiv:2110.07550

Yiming Zheng

Serena Booth

Julie Shah

Yilun Zhou

2021/10/14

IEEE P7001: A proposed standard on transparency

Frontiers in Robotics and AI

Alan FT Winfield

Serena Booth

Louise A Dennis

Takashi Egawa

Helen Hastie

...

2021/7/26

Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development

Aspen Hopkins*

Serena Booth*

2021/5

Bayes-TrEx: A Bayesian Sampling Approach to Model Transparency by Example

Serena Booth

Yilun Zhou

Ankit Shah

Julie Shah

2021

RoCUS: Robot Controller Understanding via Sampling

Yilun Zhou

Serena Booth

Nadia Figueroa

Julie Shah

2022/1/11

Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI)

arXiv preprint arXiv:2202.11249

Michael Walker

Thao Phung

Tathagata Chakraborti

Tom Williams

Daniel Szafir

2022/2/23

Explainable AI foundations to support human-robot teaching and learning

Serena Lynn Booth

2020

See List of Professors in Serena Booth University(Massachusetts Institute of Technology)

Co-Authors

H-index: 91
Hanspeter Pfister

Hanspeter Pfister

Harvard University

H-index: 54
Krzysztof Gajos

Krzysztof Gajos

Harvard University

H-index: 53
Radhika Nagpal

Radhika Nagpal

Harvard University

H-index: 47
Julie Shah

Julie Shah

Massachusetts Institute of Technology

H-index: 29
James Tompkin

James Tompkin

Brown University

H-index: 24
Christian Muise

Christian Muise

Queen's University

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