Devavrat Shah

About Devavrat Shah

Devavrat Shah, With an exceptional h-index of 64 and a recent h-index of 35 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of statistical inference, networks, algorithms, communications.

His recent articles reflect a diverse array of research interests and contributions to the field:

Advancing Equality: Harnessing Generative AI to Combat Systemic Racism

Gradient-based empirical risk minimization using local polynomial regression

Unifying epidemic models with mixtures

A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems

Auditing for Human Expertise

SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise

Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction

Impact of therapy sequence on survival outcomes among patients with relapsed or refractory mature T and NK cell neoplasms: a global retrospective cohort study

Devavrat Shah Information

University

Position

___

Citations(all)

21293

Citations(since 2020)

6728

Cited By

17620

hIndex(all)

64

hIndex(since 2020)

35

i10Index(all)

193

i10Index(since 2020)

103

Email

University Profile Page

Google Scholar

Devavrat Shah Skills & Research Interests

statistical inference

networks

algorithms

communications

Top articles of Devavrat Shah

Advancing Equality: Harnessing Generative AI to Combat Systemic Racism

2024/3/27

Gradient-based empirical risk minimization using local polynomial regression

Stochastic Systems

2024/3/26

Ali Jadbabaie
Ali Jadbabaie

H-Index: 47

Devavrat Shah
Devavrat Shah

H-Index: 39

Unifying epidemic models with mixtures

IEEE Transactions on Signal and Information Processing over Networks

2024/3/11

A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems

arXiv preprint arXiv:2402.14959

2024/2/22

Auditing for Human Expertise

Advances in Neural Information Processing Systems

2024/2/13

SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise

Advances in Neural Information Processing Systems

2024/2/13

Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction

arXiv preprint arXiv:2402.00793

2024/2/1

Manish Raghavan
Manish Raghavan

H-Index: 11

Devavrat Shah
Devavrat Shah

H-Index: 39

Impact of therapy sequence on survival outcomes among patients with relapsed or refractory mature T and NK cell neoplasms: a global retrospective cohort study

Blood

2023/11/28

Novel Causal Inference Method Estimates Treatment Effects of Contemporary Drugs in a Global Cohort of Patients with Relapsed and Refractory Mature T-Cell and NK-Cell Neoplasms

Blood

2023/11/28

Predicting Ground Reaction Force from Inertial Sensors

arXiv preprint arXiv:2311.02287

2023/11/4

System and Method for Joining Datasets

2023/10/12

Model agnostic time series analysis via matrix estimation

2023/10/3

Federated optimization of smooth loss functions

IEEE Transactions on Information Theory

2023/9/19

Ali Jadbabaie
Ali Jadbabaie

H-Index: 47

Devavrat Shah
Devavrat Shah

H-Index: 39

Low-Rank Gradient Descent

IEEE Open Journal of Control Systems

2023/9/13

On Computationally Efficient Learning of Exponential Family Distributions

arXiv preprint arXiv:2309.06413

2023/9/12

Abhin Shah
Abhin Shah

H-Index: 1

Devavrat Shah
Devavrat Shah

H-Index: 39

Causal matrix completion

2023/7/12

Matrix estimation for individual fairness

2023/7/3

Counterfactual identifiability of bijective causal models

2023/7/3

Mohammad Alizadeh
Mohammad Alizadeh

H-Index: 2

Devavrat Shah
Devavrat Shah

H-Index: 39

Exploiting Observation Bias to Improve Matrix Completion

arXiv preprint arXiv:2306.04775

2023/6/7

Yassir Jedra
Yassir Jedra

H-Index: 4

Devavrat Shah
Devavrat Shah

H-Index: 39

A User-Driven Framework for Regulating and Auditing Social Media

arXiv preprint arXiv:2304.10525

2023/4/20

Devavrat Shah
Devavrat Shah

H-Index: 39

See List of Professors in Devavrat Shah University(Massachusetts Institute of Technology)

Co-Authors

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