2026 David Sontag: 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	53	4711	4579	2187	2110	159	16804

Overview

David Sontag is affiliated with MIT in the United States and has a research profile spanning computer science and medicine. Their work integrates multiple disciplines with a strong emphasis on the intersection of artificial intelligence and healthcare.

The primary fields of study for David Sontag are:

Computer Science
Medicine

Their research delves into specialized subfields including:

Artificial Intelligence
Statistics and Probability
Molecular Biology
Rheumatology
Epidemiology

Key topics addressed in Sontag's publications include:

Machine Learning in Healthcare
Topic Modeling
Advanced Causal Inference Techniques
Machine Learning and Data Classification
Natural Language Processing Techniques
Systemic Lupus Erythematosus Research
Biomedical Text Mining and Ontologies

Frequent coauthors in Sontag's collaborations are:

Michael Oberst
Monica Agrawal
Zeshan Hussain
Hussein Mozannar
Hunter Lang

The venues where David Sontag most often publishes include:

arXiv (Cornell University)
bioRxiv (Cold Spring Harbor Laboratory)
Zenodo (CERN European Organization for Nuclear Research)
Proceedings of the AAAI Conference on Artificial Intelligence
Blood

Selected recent papers authored or coauthored by David Sontag include:

A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection, 2020, Science Translational Medicine
Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes, 2023, Annals of the Rheumatic Diseases
Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis, 2022, Nature Communications
The Potential For Bias In Machine Learning And Opportunities For Health Insurers To Address It, 2022, Health Affairs
TabLLM: Few-shot Classification of Tabular Data with Large Language Models, 2022, arXiv (Cornell University)

Best Publications

Recurrent Neural Networks for Multivariate Time Series with Missing Values.

Zhengping Che;Sanjay Purushotham;Kyunghyun Cho;David A. Sontag

2241
Citations
Character-aware neural language models

Yoon Kim;Yacine Jernite;David Sontag;Alexander M. Rush

1951
Citations
BLOG: Probabilistic Models with Unknown Objects

Brian Milch;Bhaskara Marthi;Stuart Russell;David Sontag

1161
Citations
Estimating individual treatment effect: generalization bounds and algorithms

Uri Shalit;Fredrik D. Johansson;David A. Sontag

627
Citations
A Practical Algorithm for Topic Modeling with Provable Guarantees

Sanjeev Arora;Rong Ge;Yonatan Halpern;David Mimno

474
Citations
Learning representations for counterfactual inference

Fredrik D. Johansson;Uri Shalit;David Sontag

466
Citations
Structured Inference Networks for Nonlinear State Space Models

Rahul G. Krishnan;Uri Shalit;David A. Sontag

449
Citations
Learning a Health Knowledge Graph from Electronic Medical Records.

Maya Rotmensch;Yoni Halpern;Abdulhakim Tlimat;Steven Horng

444
Citations
Causal Effect Inference with Deep Latent-Variable Models

Christos Louizos;Uri Shalit;Joris M. Mooij;David A. Sontag

424
Citations
Tightening LP relaxations for MAP using message passing

David Sontag;Talya Meltzer;Amir Globerson;Tommi Jaakkola

399
Citations
Guidelines for reinforcement learning in healthcare

Omer Gottesman;Fredrik Johansson;Matthieu Komorowski;Aldo Faisal

369
Citations
Large language models are few-shot clinical information extractors

Unknown

364
Citations
Learning Low-Dimensional Representations of Medical Concepts.

Youngduck Choi;Chill Yi-I Chiu;David A. Sontag

308
Citations
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning

Steven Horng;David A. Sontag;Yoni Halpern;Yacine Jernite

305
Citations
Unsupervised learning of disease progression models

Xiang Wang;David Sontag;Fei Wang

289
Citations
On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing

Alexander M Rush;David Sontag;Michael Collins;Tommi Jaakkola

269
Citations
Learning Bayesian Network Structure using LP Relaxations

Tommi S. Jaakkola;David Alexander Sontag;Amir Globerson;Marina Meila

268
Citations
Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

Narges Razavian;Saul Blecker;Ann Marie Schmidt;Aaron Smith-McLallen

253
Citations
Introduction to dual composition for inference

David Sontag;Amir Globerson;Amir Globerson;Amir Globerson;Tommi Jaakkola

251
Citations
Deep Kalman Filters.

Rahul G. Krishnan;Uri Shalit;David A. Sontag

246
Citations
Dual Decomposition for Parsing with Non-Projective Head Automata

Terry Koo;Alexander M. Rush;Michael Collins;Tommi Jaakkola

229
Citations

Frequent Co-Authors

Tommi S. Jaakkola MIT

Amir Globerson Tel Aviv University

Alexander M. Rush Cornell University

Adrian Weller University of Cambridge

Paul N. Bennett Microsoft (United States)

Ryen W. White Microsoft (United States)

Kevyn Collins-Thompson University of Michigan–Ann Arbor

John V. Guttag MIT

Rajesh Ranganath New York University

Ann Marie Schmidt New York University

External Links

Personal website of David Sontag Google Scholar page

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