---
title: "Marzyeh Ghassemi · Microsoft — author profile and papers"
description: "Marzyeh Ghassemi, Microsoft: 2 papers on Elamur Research (2020–2026), h-index 58 — affiliations, topics, co-authors and who cites them in…"
canonical: "https://research.elamur.ai/free/en/authors/marzyeh-ghassemi/"
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# Marzyeh Ghassemi

Marzyeh Ghassemi has 2 papers in our library, in 2020–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Kyunghyun Cho](https://md.research.elamur.ai/free/en/authors/kyunghyun-cho/), [Nathan Ng](https://md.research.elamur.ai/free/en/authors/nathan-ng/), [Shujian Zhang](https://md.research.elamur.ai/free/en/authors/shujian-zhang/).

2 papers in our library · 2020–2026

[OpenAlex](https://openalex.org/A5070063054) · [ORCID](https://orcid.org/0000-0001-6349-7251) · [Wikidata](https://www.wikidata.org/wiki/Q64949666) · [**h-index 58**](https://openalex.org/authors/A5070063054) · [335 works](https://openalex.org/works?filter=author.id:A5070063054) · [21,104 citations](https://openalex.org/works?filter=author.id:A5070063054&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/marzyeh-ghassemi/#papers) · [🔗 Cited 99 times in our library](https://md.research.elamur.ai/free/en/authors/marzyeh-ghassemi/cited-by/) · [9 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6027](https://md.research.elamur.ai/free/en/paper-stars/page/61/#star-6027)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Marzyeh+Ghassemi) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Marzyeh+Ghassemi) · [dblp](https://dblp.org/search?q=Marzyeh+Ghassemi) · [ACL Anthology](https://aclanthology.org/search/?q=Marzyeh+Ghassemi)

## Affiliations

[🎓**Massachusetts Institute of Technology** Cambridge · United States 2012–2026 · 176 papersEducation until 2017 · PhD, EECSEmployment*current*](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) · [🏢**Microsoft** Redmond · United States 2019–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏢**Microsoft Research** Cambridge · United Kingdom 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/microsoft-research-united-kingdom/) · [🔬**Vector Institute** Toronto · Canada 2018–2025 · 82 papersEmployment](https://md.research.elamur.ai/free/en/labs/vector-institute/) · [🎓**University of Toronto** Toronto · Canada 2018–2024 · 74 papersEmployment](https://md.research.elamur.ai/free/en/universities/university-of-toronto/) · [🔬**MIT Computer Science and Artificial Intelligence Laboratory** Cambridge · United States 2014–2025 · 20 papers](https://md.research.elamur.ai/free/en/labs/mit-computer-science-and-artificial-intelligence-laboratory/) · [🔬**Canadian Institute for Advanced Research** Toronto · Canada 2020–2025 · 16 papers](https://md.research.elamur.ai/free/en/labs/canadian-institute-for-advanced-research/) · [🏥**Unity Health Toronto** Toronto 2021–2022 · 6 papers](https://ror.org/012x5xb44) · [🏥**St. Michael's Hospital** Toronto · Canada 2021–2022 · 4 papers](https://ror.org/04skqfp25) · [🎓**University of Alberta** Edmonton · Canada 2021 · 4 papers](https://md.research.elamur.ai/free/en/universities/university-of-alberta/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 35 more institutions on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/marzyeh-ghassemi/year/2026/) · [**2020** 1 paper](https://md.research.elamur.ai/free/en/authors/marzyeh-ghassemi/year/2020/)

## Papers

The most cited first (OpenAlex and our library).

1. **[SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness](https://md.research.elamur.ai/free/en/papers/ng-2020-ssmba-self-supervised-manifold-based/)** *(2020 · 161 citations)* Classifiers and sequence models trained on one domain often perform poorly on out-of-domain (OOD) inputs. For images, simple transformations like rotation keep new examples realistic, but no comparable meaning-preserving operations exist for text. The authors propose SSMBA, a task-agnostic augmentation scheme based…
2. **[SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe](https://md.research.elamur.ai/free/en/papers/xiao-2026-sftmix-elevating-language-model-instruction/)** *(2026 · 3 citations)* Instruction tuning usually trains LLMs with plain next-token prediction (NTP). Most efforts to improve it focus on building cleaner SFT datasets, which often means filtering with proprietary LLMs or paying human annotators. SFTMix improves the training recipe itself and works on uncurated data.

## All works

11 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. **[A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data ↗](https://doi.org/10.1609/aaai.v29i1.9209) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Marzyeh Ghassemi et al.*2015 · 197 citations*
2. **[SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness](https://md.research.elamur.ai/free/en/papers/ng-2020-ssmba-self-supervised-manifold-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi*2020 · 161 citations*
3. **[Vision-Language Models Do Not Understand Negation ↗](https://doi.org/10.1109/cvpr52734.2025.02757) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Kumail Alhamoud et al.*2025 · 36 citations*
4. **[Predicting Out-of-Domain Generalization with Neighborhood Invariance ↗](https://arxiv.org/abs/2207.02093) arXiv (Cornell University) · no summary yet**Ng, Nathan et al.*2022 · 5 citations*
5. **[Towards Characterizing the High-dimensional Bias of Kernel-based Particle Inference Algorithms ↗](https://openalex.org/W3007177133) no summary yet**Jimmy Lei Ba et al.*2019 · 5 citations*
6. **[Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation ↗](https://arxiv.org/abs/1912.04370) arXiv:1912.04370 · no summary yet**Aparna Balagopalan et al.*2019 · 5 citations*
7. **[Redefining druggable targets with artificial intelligence ↗](https://doi.org/10.1038/s41587-025-02770-1) Nature Biotechnology · no summary yet**Karen Akinsanya et al.*2025 · 4 citations*
8. **[SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe](https://md.research.elamur.ai/free/en/papers/xiao-2026-sftmix-elevating-language-model-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Xiao, Shujian Zhang, Marzyeh Ghassemi, et al.*2026 · 3 citations*
9. **[Improving Black-box Robustness with In-Context Rewriting ↗](https://arxiv.org/abs/2402.08225) arXiv (Cornell University) · no summary yet**Kyle O'Brien et al.*2024 · 3 citations*
10. **[Hedging and Non-Affirmation: Quantifying LLM Alignment on Questions of Human Rights ↗](https://arxiv.org/abs/2502.19463) arXiv:2502.19463 · no summary yet**Rafiya Javed et al.*2025 · 2 citations*
11. **[Protecting patient privacy in clinical foundation models: Technical and legal perspectives ↗](https://arxiv.org/abs/2608.07705) arXiv:2608.07705 · no summary yet**Sana Tonekaboni et al.*2026*

## Co-authors here

4 co-authors with a page, the most papers together first.

- [Kyunghyun Cho](https://md.research.elamur.ai/free/en/authors/kyunghyun-cho/)
- [Nathan Ng](https://md.research.elamur.ai/free/en/authors/nathan-ng/)
- [Shujian Zhang](https://md.research.elamur.ai/free/en/authors/shujian-zhang/)
- [Wenxuan Zhou](https://md.research.elamur.ai/free/en/authors/wenxuan-zhou/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)
- [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2020](https://md.research.elamur.ai/free/en/venues/emnlp/2020/)
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
- Nature Biotechnology
- Proceedings of the AAAI Conference on Artificial Intelligence

## Cited by

Papers of our library cite their works 99 times (of the 149,439 papers whose bibliographies we read); [11 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/marzyeh-ghassemi/cited-by/).

Updated 31 October 2026
