Maryam Habibi

About Maryam Habibi

Maryam Habibi, With an exceptional h-index of 12 and a recent h-index of 8 (since 2020), a distinguished researcher at Humboldt-Universität zu Berlin, specializes in the field of natural language processing (NLP), text mining, information retrieval, machine learning, deep.

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

HunFlair: an easy-to-use tool for state-of-the-art biomedical named entity recognition (vol 37, pg 2792, 2021)

Annotation and initial evaluation of a large annotated German oncological corpus

TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity

DeepTable: A Permutation Invariant Neural Network for Table Orientation Classification

PatSeg: a Sequential Patent Segmentation Approach

HUNER: improving biomedical NER with pretraining

Maryam Habibi Information

University

Position

___

Citations(all)

1087

Citations(since 2020)

830

Cited By

597

hIndex(all)

12

hIndex(since 2020)

8

i10Index(all)

13

i10Index(since 2020)

7

Email

University Profile Page

Google Scholar

Maryam Habibi Skills & Research Interests

natural language processing (NLP)

text mining

information retrieval

machine learning

deep

Top articles of Maryam Habibi

HunFlair: an easy-to-use tool for state-of-the-art biomedical named entity recognition (vol 37, pg 2792, 2021)

BIOINFORMATICS

2023/11/1

Annotation and initial evaluation of a large annotated German oncological corpus

JAMIA open

2021/4/1

TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity

2020/12/10

DeepTable: A Permutation Invariant Neural Network for Table Orientation Classification

Data Mining and Knowledge Discovery

2020/11

PatSeg: a Sequential Patent Segmentation Approach

Big Data Research

2020/3/1

HUNER: improving biomedical NER with pretraining

Bioinformatics

2020/1/1

See List of Professors in Maryam Habibi University(Humboldt-Universität zu Berlin)

Co-Authors

academic-engine