World's Best Scientists 2026 revealed!
Gholamreza Haffari

Gholamreza Haffari

D-Index & Metrics

Computer Science

D-Index
37
Citations
5584
World Ranking
10790
National Ranking
327

Overview

Gholamreza Haffari is affiliated with Monash University in Australia and has contributed extensively to the field of computer science, with a particular focus on artificial intelligence. Their body of work spans multiple subfields, including artificial intelligence, computer vision and pattern recognition, signal processing, molecular biology, and information systems.

The primary area of research comprises core topics such as topic modeling, natural language processing techniques, multimodal machine learning applications, speech recognition and synthesis, domain adaptation and few-shot learning, speech and dialogue systems, and text readability and simplification.

Frequent collaborators include Lizhen Qu, Yuan-Fang Li, Thuy-Trang Vu, Ehsan Shareghi, and Zhuang Li. This network of coauthors indicates a collaborative approach to research across various projects and disciplines.

The scientist's research has been published in notable venues, with a strong presence on arXiv (Cornell University), where they have 121 publications. Other significant publication venues include the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Transactions of the Association for Computational Linguistics, ACM Computing Surveys, and SN Computer Science.

The following recent papers illustrate the diversity and scope of their research:

  • A Survey on Document-level Neural Machine Translation, 2021, ACM Computing Surveys
  • Curriculum-Meta Learning for Order-Robust Continual Relation Extraction, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Learning Object-Language Alignments for Open-Vocabulary Object Detection, 2022, arXiv (Cornell University)
  • Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning, 2023, arXiv (Cornell University)
  • Generate, Annotate, and Learn: NLP with Synthetic Text, 2022, Transactions of the Association for Computational Linguistics

Best Publications

  • Graph-to-Sequence Learning using Gated Graph Neural Networks

    Daniel Beck;Gholamreza Haffari;Trevor Cohn

  • DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.

    Ali Bashashati;Gholamreza Haffari;Gholamreza Haffari;Jiarui Ding;Jiarui Ding;Gavin Ha;Gavin Ha

  • Iterative Back-Translation for Neural Machine Translation

    Vu Cong Duy Hoang;Philipp Koehn;Gholamreza Haffari;Trevor Cohn

  • Document Context Neural Machine Translation with Memory Networks

    Sameen Maruf;Gholamreza Haffari

  • Feature-based classifiers for somatic mutation detection in tumour–normal paired sequencing data

    Jiarui Ding;Ali Bashashati;Andrew Roth;Arusha Oloumi

  • Incorporating Structural Alignment Biases into an Attentional Neural Translation Model

    Trevor Cohn;Cong Duy Vu Hoang;Ekaterina Vymolova;Kaisheng Yao

  • Selective Attention for Context-aware Neural Machine Translation.

    Sameen Maruf;André F. T. Martins;Gholamreza Haffari

  • PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.

    Jiangning Song;Fuyi Li;Andre Leier;Tatiana Marquez-Lago

  • A Latent Variable Recurrent Neural Network for Discourse-Driven Language Models

    Yangfeng Ji;Gholamreza Haffari;Jacob Eisenstein

  • PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

    Jiangning Song;Fuyi Li;Kazuhiro Takemoto;Gholamreza Haffari

  • Transductive learning for statistical machine translation

    Nicola Ueffing;Gholamreza Haffari;Anoop Sarkar

  • Active Learning for Statistical Phrase-based Machine Translation

    Gholamreza Haffari;Maxim Roy;Anoop Sarkar

  • A Survey on Document-level Neural Machine Translation: Methods and Evaluation

    Sameen Maruf;Fahimeh Saleh;Gholamreza Haffari

  • Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods.

    Fuyi Li;Yanan Wang;Yanan Wang;Chen Li;Chen Li;Tatiana T Marquez-Lago

  • Proceedings of the Australasian Language Technology Association Workshop 2017

    Jojo Sze-Meng Wong;Gholamreza Haffari

  • Continual Learning for Large Language Models: A Survey

    Unknown

  • Reasoning like human: hierarchical reinforcement learning for knowledge graph reasoning

    Guojia Wan;Shirui Pan;Chen Gong;Chen Gong;Chuan Zhou

  • A Latent Variable Recurrent Neural Network for Discourse Relation Language Models

    Yangfeng Ji;Gholamreza Haffari;Jacob Eisenstein

  • Learning how to actively learn: a deep imitation learning approach

    Ming Liu;Wray L. Buntine;Gholamreza Haffari

  • Semi-supervised model adaptation for statistical machine translation

    Nicola Ueffing;Gholamreza Haffari;Anoop Sarkar

  • Analysis of semi-supervised learning with the Yarowsky algorithm

    GholamReza Haffari;Anoop Sarkar

  • HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology.

    Raunak Shrestha;Raunak Shrestha;Ermin Hodzic;Thomas Michael Sauerwald;Phuong Dao

  • Learning Object-Language Alignments for Open-Vocabulary Object Detection

    Unknown

  • Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation

    Poorya Zaremoodi;Wray L. Buntine;Gholamreza Haffari

Frequent Co-Authors

Trevor Cohn
Trevor Cohn University of Melbourne
Wray Buntine
Wray Buntine VinUniversity
Pushpak Bhattacharyya
Pushpak Bhattacharyya Indian Institute of Technology Patna
Kai Ming Ting
Kai Ming Ting Nanjing University
Samuel Aparicio
Samuel Aparicio University of British Columbia
Mohammad Norouzi
Mohammad Norouzi Google (United States)
Sohrab P. Shah
Sohrab P. Shah Memorial Sloan Kettering Cancer Center
Kuo-Chen Chou
Kuo-Chen Chou The Gordon Life Science Institute
Gavin Ha
Gavin Ha Fred Hutchinson Cancer Research Center
Dinh Phung
Dinh Phung Monash University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens doors to a variety of online degree programs and specialized career paths. For students seeking a flexible and streamlined journey, a fast track computer science degree can allow quicker entry into the workforce—ideal for career changers or those balancing work commitments.

Your interests may extend to engineering fields that intersect with computer science. An environmental engineering degrees online program is excellent for those passionate about technology-driven solutions to sustainability challenges.

If you are keen on machinery and design, consider an online degree for mechanical engineering, which can prepare you for roles in robotics, manufacturing, or automotive industries.

Alternatively, a strong foundation in science can be built with online physics degrees, offering pathways to research, data analysis, and innovation in tech fields.

These diverse online programs support flexible learning and represent possible next steps for aspiring computer scientists seeking broader expertise or interdisciplinary careers.

Best Scientists Citing Gholamreza Haffari

Trending Scientists

Recently Published Articles