2026 Dustin Tran: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Rising Stars	40	645	645	96	96	90	8582
Computer Science	40	9370	9100	3973	3809	83	6066

Research.com Recognitions

2025 - Research.com Rising Stars Award

Overview

Dustin Tran is affiliated with Google in the United States and has a research focus predominantly within computer science. Their work spans several subfields including artificial intelligence, computer vision and pattern recognition, control and systems engineering, computational mechanics, and emergency medicine.

The primary research topics addressed by Dustin Tran include adversarial robustness in machine learning, domain adaptation and few-shot learning, advanced neural network applications, anomaly detection techniques and applications, topic modeling, machine learning and data classification, and Gaussian processes and Bayesian inference.

Dustin Tran has authored numerous publications, with many appearing in the venue arXiv (Cornell University) where they have 23 documented papers. Other publication venues include the Annual Review of Statistics and Its Application, Annals of Vascular Surgery, and Entropy.

"Gemini: A Family of Highly Capable Multimodal Models" (2023) published in arXiv (Cornell University)
"Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" (2020) published in arXiv (Cornell University)
"BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning" (2020) published in arXiv (Cornell University)
"Scaling Vision Transformers to 22 Billion Parameters" (2023) published in arXiv (Cornell University)
"Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" (2020) published in arXiv (Cornell University)

Dustin Tran collaborates frequently with several coauthors including Balaji Lakshminarayanan, Jasper Snoek, Rodolphe Jenatton, Yeming Wen, and Michael W. Dusenberry, indicating a collaborative research approach within the machine learning community.

Best Publications

Automatic differentiation variational inference

Alp Kucukelbir;Dustin Tran;Rajesh Ranganath;Andrew Gelman

743
Citations
Edward: A library for probabilistic modeling, inference, and criticism

Dustin Tran;Alp Kucukelbir;Adji B. Dieng;Maja R. Rudolph

317
Citations
Scaling Vision Transformers to 22 Billion Parameters

Unknown

315
Citations
Hierarchical variational models

Rajesh Ranganath;Dustin Tran;David M. Blei

267
Citations
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

Yeming Wen;Paul Vicol;Jimmy Ba;Dustin Tran

233
Citations
Larger language models do in-context learning differently

Unknown

225
Citations
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning

Yeming Wen;Dustin Tran;Jimmy Ba

224
Citations
Image Transformer

Niki Parmar;Ashish Vaswani;Jakob Uszkoreit;Łukasz Kaiser

220
Citations
Mesh-TensorFlow: Deep Learning for Supercomputers

Noam Shazeer;Youlong Cheng;Niki J. Parmar;Dustin Tran

219
Citations
Deep Probabilistic Programming

Dustin Tran;Matthew D. Hoffman;Rif A. Saurous;Eugene Brevdo

193
Citations
TensorFlow Distributions

Joshua V. Dillon;Ian Langmore;Dustin Tran;Eugene Brevdo

192
Citations
Hierarchical Implicit Models and Likelihood-Free Variational Inference

Dustin Tran;Rajesh Ranganath;David M. Blei

176
Citations
Measuring Calibration in Deep Learning

Jeremy Nixon;Mike Dusenberry;Ghassen Jerfel;Timothy Nguyen

159
Citations
Variational Gaussian Process

Dustin Tran;Rajesh Ranganath;David M. Blei

154
Citations
Hyperparameter Ensembles for Robustness and Uncertainty Quantification

Florian Wenzel;Jasper Snoek;Dustin Tran;Rodolphe Jenatton

132
Citations
Analyzing the role of model uncertainty for electronic health records

Michael W. Dusenberry;Dustin Tran;Edward Choi;Jonas Kemp

126
Citations
Variational Inference via $\chi$ Upper Bound Minimization

Adji Bousso Dieng;Dustin Tran;Rajesh Ranganath;John W. Paisley

122
Citations
Plex: Towards Reliability using Pretrained Large Model Extensions

Unknown

117
Citations
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

Jeremiah Zhe Liu;Zi Lin;Shreyas Padhy;Dustin Tran

108
Citations
Training independent subnetworks for robust prediction

Marton Havasi;Rodolphe Jenatton;Stanislav Fort;Jeremiah Zhe Liu

98
Citations
The Variational Gaussian Process

Dustin Tran;Rajesh Ranganath;David M. Blei

94
Citations
Operator variational inference

Rajesh Ranganath;Jaan Altosaar;Dustin Tran;David M. Blei

92
Citations
Deep and Hierarchical Implicit Models.

Dustin Tran;Rajesh Ranganath;David M. Blei

81
Citations
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport

Dustin Tran;Ian Langmore;Josh Dillon;Matthew D. Hoffman

78
Citations

Frequent Co-Authors

David M. Blei Columbia University

Rajesh Ranganath New York University

Balaji Lakshminarayanan Google (United States)

Jasper Snoek Google (United States)

Aki Vehtari Aalto University

Edoardo M. Airoldi Temple University

Matthew D. Hoffman Google (United States)

Maria G. Castro University of Michigan–Ann Arbor

Pedro R. Lowenstein University of Michigan–Ann Arbor

Katherine A. Heller Google (United States)

External Links

Personal website of Dustin Tran Google Scholar page

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