--- title: "AmirAli Bagher Zadeh — author profile and papers" description: "AmirAli Bagher Zadeh, Carnegie Mellon University: 3 papers on Elamur Research (2018–2020), h-index 7 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/amirali-bagher-zadeh/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/amirali-bagher-zadeh/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / AmirAli Bagher Zadeh # AmirAli Bagher Zadeh AmirAli Bagher Zadeh works on multimodal language, meaning the way spoken words, tone of voice and facial expression carry meaning together, and on how machine learning models can combine these channels. The papers here, from 2018 to 2020, cover sentiment and emotion in video, the design of fusion methods that merge language, acoustic and visual representations, and the computational cost of such methods as more modalities are added. The most cited of them, [Multimodal Language Analysis in the Wild](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/) (2018), introduced CMU-MOSEI. It is a large corpus of single-speaker YouTube monologues labelled for sentiment and emotion, with hand-written transcripts aligned to the audio at the phoneme level. The same paper presented the Dynamic Fusion Graph, a fusion module that models interactions among one, two and three modalities. [Efficient Low-rank Multimodal Fusion](https://md.research.elamur.ai/free/en/papers/liu-2018-efficient-low-rank-multimodal-fusion/) (2018) tackled the exponential growth of tensor-based fusion. It factors the fusion weights into low-rank, modality-specific parts, so the joint output can be computed directly from the unimodal vectors. The newest paper, [Integrating Multimodal Information in Large Pretrained Transformers](https://md.research.elamur.ai/free/en/papers/rahman-2020-integrating-multimodal-information-large-pretrained/) (2020), turns to text-only pretrained models such as BERT and XLNet. It adds the Multimodal Adaptation Gate, a small component that uses aligned acoustic and visual cues to displace each word's representation inside the model. The base architecture stays intact, and the combined system is fine-tuned end to end. Bagher Zadeh's papers list [Carnegie Mellon University](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) in Pittsburgh as the affiliation from 2018 to 2020. The most frequent co-author is [Louis-Philippe Morency](https://md.research.elamur.ai/free/en/authors/louis-philippe-morency/), on three of the papers, followed by [Paul Pu Liang](https://md.research.elamur.ai/free/en/authors/paul-pu-liang/) on two. The work sits mainly under [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/), with further papers in [Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) and [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/). AmirAli Bagher Zadeh has 3 papers in our library, in 2018–2020, most of them on [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/), [Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Louis-Philippe Morency](https://md.research.elamur.ai/free/en/authors/louis-philippe-morency/), [Paul Pu Liang](https://md.research.elamur.ai/free/en/authors/paul-pu-liang/), [Ehsan Hoque](https://md.research.elamur.ai/free/en/authors/ehsan-hoque/). 3 papers in our library · 2018–2020 [OpenAlex](https://openalex.org/A5071618613) · [**h-index 7**](https://openalex.org/authors/A5071618613) · [8 works](https://openalex.org/works?filter=author.id:A5071618613) · [3,529 citations](https://openalex.org/works?filter=author.id:A5071618613&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/amirali-bagher-zadeh/#papers) · [🔗 311 citations in our library](https://md.research.elamur.ai/free/en/authors/amirali-bagher-zadeh/cited-by/) · [⭐ Paper Star rank #748](https://md.research.elamur.ai/free/en/paper-stars/page/8/#star-748) 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=AmirAli+Bagher+Zadeh) · [Semantic Scholar](https://www.semanticscholar.org/search?q=AmirAli+Bagher+Zadeh) · [dblp](https://dblp.org/search?q=AmirAli+Bagher+Zadeh) · [ACL Anthology](https://aclanthology.org/search/?q=AmirAli+Bagher+Zadeh) ## Affiliations [🎓**Carnegie Mellon University** Pittsburgh · United States 2018–2020 · 5 papers*current*](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed. ## Topics [Vision & language (3)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Sentiment & emotion (1)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Efficient models & compression (1)](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2020** 1 paper](https://md.research.elamur.ai/free/en/papers/rahman-2020-integrating-multimodal-information-large-pretrained/) ### 2010s [**2018** 2 papers](https://md.research.elamur.ai/free/en/authors/amirali-bagher-zadeh/year/2018/) ## Papers The most cited first (OpenAlex and our library). 1. **[Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/)** *(2018 · 1,506 citations)* Studying how people combine words, facial expressions and voice requires large, varied multimodal data, but earlier corpora were small and covered few speakers, topics and label types. 2. **[Efficient Low-rank Multimodal Fusion With Modality-Specific Factors](https://md.research.elamur.ai/free/en/papers/liu-2018-efficient-low-rank-multimodal-fusion/)** *(2018 · 1,174 citations)* The paper tackles a scaling problem in multimodal fusion, which merges per-modality representations (language, audio, visual) into one joint vector. 3. **[Integrating Multimodal Information in Large Pretrained Transformers](https://md.research.elamur.ai/free/en/papers/rahman-2020-integrating-multimodal-information-large-pretrained/)** *(2020 · 742 citations)* Pretrained Transformers such as BERT and XLNet accept only text. Applying them to multimodal language, where spoken words come with voice and facial cues, has therefore meant one of two compromises: discarding the nonverbal signals, or using the models only to produce word features for a separate fusion network. The… ## Co-authors here 7 co-authors with a page, the most papers together first. - [Louis-Philippe Morency](https://md.research.elamur.ai/free/en/authors/louis-philippe-morency/) ×3 - [Paul Pu Liang](https://md.research.elamur.ai/free/en/authors/paul-pu-liang/) ×2 - [Ehsan Hoque](https://md.research.elamur.ai/free/en/authors/ehsan-hoque/) - [Erik Cambria](https://md.research.elamur.ai/free/en/authors/erik-cambria/) - [Soujanya Poria](https://md.research.elamur.ai/free/en/authors/soujanya-poria/) - [Ying Shen](https://md.research.elamur.ai/free/en/authors/ying-shen/) - [Zhun Liu](https://md.research.elamur.ai/free/en/authors/zhun-liu/) ## Cited by Papers of our library cite their works 311 times (of the 140,884 papers whose bibliographies we read); [8 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/amirali-bagher-zadeh/cited-by/).