ProfessorsProfessors of Johns Hopkins UniversityCarlos Alejandro Aguirre

Carlos Alejandro Aguirre

Johns Hopkins University

H-index: 8

North America-United States

About Carlos Alejandro Aguirre

Carlos Alejandro Aguirre, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Johns Hopkins University, specializes in the field of Natural Language Processing.

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

Severe Symptoms and Suicidal Ideation in People Without a Psychiatric Diagnosis: Findings From an Online Cohort Study

Selecting shots for demographic fairness in few-shot learning with large language models

Crowdsourcing Thumbnail Captions: Data Collection and Validation

Generalizing Fairness using Multi-Task Learning without Demographic Information

Bernice: A multilingual pre-trained encoder for Twitter

Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics

Crowdsourcing thumbnail captions via time-constrained methods

Qualitative analysis of depression models by demographics

Carlos Alejandro Aguirre Information

University	Johns Hopkins University
Position	___
Citations(all)	262
Citations(since 2020)	260
Cited By	37
hIndex(all)	8
hIndex(since 2020)	8
i10Index(all)	7
i10Index(since 2020)	7
Email	Access Email
University Profile Page	Johns Hopkins University
Google Scholar	View Google Scholar Profile

Carlos Alejandro Aguirre Skills & Research Interests

Natural Language Processing

Top articles of Carlos Alejandro Aguirre

Title	Journal	Author(s)	Publication Date
Severe Symptoms and Suicidal Ideation in People Without a Psychiatric Diagnosis: Findings From an Online Cohort Study		Colin Frazier Philip Resnik Carol Espy-Wilson Carlos Alejandro Aguirre Deanna L Kelly	2023/4/20
Selecting shots for demographic fairness in few-shot learning with large language models	arXiv preprint arXiv:2311.08472	Carlos Aguirre Kuleen Sasse Isabel Cachola Mark Dredze	2023/11/14
Crowdsourcing Thumbnail Captions: Data Collection and Validation	ACM Transactions on Interactive Intelligent Systems	Carlos Aguirre Shiye Cao Amama Mahmood Chien-Ming Huang	2023/9/11
Generalizing Fairness using Multi-Task Learning without Demographic Information	arXiv preprint arXiv:2305.12671	Carlos Aguirre Mark Dredze	2023/5/22
Bernice: A multilingual pre-trained encoder for Twitter		Alexandra DeLucia Shijie Wu Aaron Mueller Carlos Aguirre Philip Resnik ...	2022/12
Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics	arXiv preprint arXiv:2211.07932	Carlos Aguirre Mark Dredze Philip Resnik	2022/11/15
Crowdsourcing thumbnail captions via time-constrained methods		Carlos A Aguirre Amama Mahmood Chien-Ming Huang	2022/3/22
Qualitative analysis of depression models by demographics		Carlos Aguirre Mark Dredze	2021/6
Gender and racial fairness in depression research using social media		Carlos Aguirre Keith Harrigian Mark Dredze	2021/3/18
Towards understanding the role of gender in deploying social media-based mental health surveillance models		Eli Sherman Keith Harrigian Carlos Aguirre Mark Dredze	2021/6
On the state of social media data for mental health research		Keith Harrigian Carlos Aguirre Mark Dredze	2020/11/10
Do models of mental health based on social media data generalize?		Keith Harrigian Carlos Aguirre Mark Dredze	2020/11