2026 Jacob Andreas: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	41	8771	8521	3750	3601	105	7925

Overview

Jacob Andreas is a researcher affiliated with MIT in the United States, primarily working in the field of Computer Science. Their research spans several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Ecology, and Developmental Biology.

Their work covers a wide range of topics with notable focus areas such as:

Topic Modeling
Natural Language Processing Techniques
Multimodal Machine Learning Applications
Explainable Artificial Intelligence (XAI)
Speech and dialogue systems
Software Engineering Research
Marine animal studies overview

Jacob Andreas has contributed extensively to scientific literature, especially through publications in well-known venues including:

arXiv (Cornell University)
bioRxiv (Cold Spring Harbor Laboratory)
Zenodo (CERN European Organization for Nuclear Research)
iScience
Nature Communications

The following is a selection of recent papers authored or coauthored by Jacob Andreas:

"What learning algorithm is in-context learning? Investigations with linear models" (2022), arXiv (Cornell University)
"Pre-Trained Language Models for Interactive Decision-Making" (2022), arXiv (Cornell University)
"Compositional Explanations of Neurons" (2020), arXiv (Cornell University)
"Toward understanding the communication in sperm whales" (2022), iScience
"A Benchmark for Systematic Generalization in Grounded Language Understanding" (2020), arXiv (Cornell University)

Frequent collaborators include:

Antonio Torralba
Pratyusha Sharma
Ekin Akyürek
Belinda Z. Li
Joshua B. Tenenbaum

Jacob Andreas' publication record reflects a focus on theoretical and applied aspects of artificial intelligence, with an emphasis on language understanding, interactive decision-making models, and explanations of neural representations. Some of their investigations extend into multidisciplinary areas such as marine animal communication, indicating engagement with ecological and biological data analysis methodologies.

The combination of topics and publication venues illustrates a career actively contributing to both the advancement of fundamental AI research and its applications across diverse domains.

Best Publications

Neural Module Networks

Jacob Andreas;Marcus Rohrbach;Trevor Darrell;Dan Klein

1129
Citations
Learning to Reason: End-to-End Module Networks for Visual Question Answering

Ronghang Hu;Jacob Andreas;Marcus Rohrbach;Trevor Darrell

598
Citations
Learning to Compose Neural Networks for Question Answering

Jacob Andreas;Marcus Rohrbach;Trevor Darrell;Dan Klein

566
Citations
Modeling Relationships in Referential Expressions with Compositional Modular Networks

Ronghang Hu;Marcus Rohrbach;Jacob Andreas;Trevor Darrell

421
Citations
Speaker-Follower Models for Vision-and-Language Navigation

Daniel Fried;Ronghang Hu;Volkan Cirik;Anna Rohrbach

341
Citations
Modular multitask reinforcement learning with policy sketches

Jacob Andreas;Dan Klein;Sergey Levine

322
Citations
Experience Grounds Language

Yonatan Bisk;Ari Holtzman;Jesse Thomason;Jacob Andreas

261
Citations
What learning algorithm is in-context learning? Investigations with linear models

Unknown

252
Citations
Deep Compositional Question Answering with Neural Module Networks

Jacob Andreas;Marcus Rohrbach;Trevor Darrell;Dan Klein

239
Citations
Good-Enough Compositional Data Augmentation

Jacob Andreas

239
Citations
A Minimal Span-Based Neural Constituency Parser

Mitchell Stern;Jacob Andreas;Dan Klein

219
Citations
Explainable Neural Computation via Stack Neural Module Networks

Ronghang Hu;Jacob Andreas;Trevor Darrell;Kate Saenko

191
Citations
A Survey of Reinforcement Learning Informed by Natural Language

Jelena Luketina;Nantas Nardelli;Nantas Nardelli;Gregory Farquhar;Gregory Farquhar;Jakob N. Foerster

180
Citations
Reasoning About Pragmatics with Neural Listeners and Speakers

Jacob Andreas;Dan Klein

153
Citations
Semantics-Based Machine Translation with Hyperedge Replacement Grammars

Bevan Jones;Jacob Andreas;Daniel Bauer;Karl Moritz Hermann

146
Citations
Learning with Latent Language

Jacob Andreas;Dan Klein;Sergey Levine

98
Citations
Parsing Graphs with Hyperedge Replacement Grammars

David Chiang;Jacob Andreas;Daniel Bauer;Karl Moritz Hermann

98
Citations
Semantic Parsing as Machine Translation

Jacob Andreas;Andreas Vlachos;Stephen Clark

97
Citations
Unified Pragmatic Models for Generating and Following Instructions

Daniel Fried;Jacob Andreas;Dan Klein

94
Citations
Task-Oriented Dialogue as Dataflow Synthesis

Jacob Andreas;John Bufe;David Burkett;Charles Chen

87
Citations
Compositional Explanations of Neurons

Jesse Mu;Jacob Andreas

70
Citations
Implicit Representations of Meaning in Neural Language Models

Belinda Z. Li;Maxwell Nye;Jacob Andreas

65
Citations
Task-Oriented Dialogue as Dataflow Synthesis

Semantic Machines;Jacob Andreas;John Bufe;David Burkett

10
Citations

Frequent Co-Authors

Daniel Klein University of California, Berkeley

Trevor Darrell University of California, Berkeley

Kate Saenko Boston University

Marcus Rohrbach Facebook (United States)

Sergey Levine University of California, Berkeley

Taylor Berg-Kirkpatrick University of California, San Diego

Antonio Torralba MIT

Kathleen R. McKeown Columbia University

Yu Su The Ohio State University

Tim Rocktäschel University College London

External Links

Personal website of Jacob Andreas

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

Related Online Degrees & Career Pathways

If you’re interested in studying Computer Science in the USA, exploring related online degrees can open up a variety of career opportunities. Fields like engineering, data analysis, and physics all offer in-demand roles for tech-savvy graduates.

For those fascinated by the physical sciences, pursuing a bachelor of science in physics online can provide a strong foundation in problem-solving and critical thinking, applicable in both research and industry settings.

The tech world’s growing demand for data-driven solutions also makes a data science degree highly attractive. With the flexibility of online study, you can prepare for well-paying tech careers while balancing other commitments.

Engineering is another popular pathway, and there are several accredited online electrical engineering programs available. These programs teach you to design and maintain high-tech systems, offering excellent job prospects in today’s digital economy.

For quicker entry into the workforce, consider certificate programs that pay well. Certifications in areas like programming, IT, or cybersecurity can boost your résumé and fast-track your tech career.