Sahand Negahban

Sahand Negahban

Yale University

H-index: 21

North America-United States

About Sahand Negahban

Sahand Negahban, With an exceptional h-index of 21 and a recent h-index of 19 (since 2020), a distinguished researcher at Yale University, specializes in the field of Machine Learning, Compressed Sensing, Signal Processing.

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

Rescuing missing data in connectome-based predictive modeling

Geon3D: Benchmarking 3D Shape Bias towards Building Robust Machine Vision

A dynamic model to estimate evolving risk of major bleeding after percutaneous coronary intervention

Distributed machine learning with sparse heterogeneous data

Network propagation-based prioritization of long tail genes in 17 cancer types

Exploiting 3D Shape Bias towards Robust Vision

Geon3D: Exploiting 3D Shape Bias towards Building Robust Machine Vision

Feature selection using stochastic gates

Sahand Negahban Information

University

Position

Associate Professor

Citations(all)

5911

Citations(since 2020)

3300

Cited By

4268

hIndex(all)

21

hIndex(since 2020)

19

i10Index(all)

25

i10Index(since 2020)

21

Email

University Profile Page

Yale University

Google Scholar

View Google Scholar Profile

Sahand Negahban Skills & Research Interests

Machine Learning

Compressed Sensing

Signal Processing

Top articles of Sahand Negahban

Title

Journal

Author(s)

Publication Date

Rescuing missing data in connectome-based predictive modeling

Imaging Neuroscience

Qinghao Liang

Rongtao Jiang

Brendan D Adkinson

Matthew Rosenblatt

Saloni Mehta

...

2024/2/2

Geon3D: Benchmarking 3D Shape Bias towards Building Robust Machine Vision

Yutaro Yamada

Yuval Kluger

Sahand Negahban

Ilker Yildirim

2023/5/24

A dynamic model to estimate evolving risk of major bleeding after percutaneous coronary intervention

medRxiv

Nathan C Hurley

Nihar Desai

Sanket S Dhruva

Rohan Khera

Wade Schulz

...

2021/12/17

Distributed machine learning with sparse heterogeneous data

Advances in Neural Information Processing Systems

Dominic Richards

Sahand Negahban

Patrick Rebeschini

2021/12/6

Network propagation-based prioritization of long tail genes in 17 cancer types

Genome Biology

Hussein Mohsen

Vignesh Gunasekharan

Tao Qing

Montrell Seay

Yulia Surovtseva

...

2021/12

Exploiting 3D Shape Bias towards Robust Vision

Yutaro Yamada

Yuval Kluger

Sahand Negahban

Ilker Yildirim

2021/10/12

Geon3D: Exploiting 3D Shape Bias towards Building Robust Machine Vision

Yutaro Yamada

Yuval Kluger

Sahand Negahban

Ilker Yildirim

2021/10/6

Feature selection using stochastic gates

Yutaro Yamada

Ofir Lindenbaum

Sahand Negahban

Yuval Kluger

2020/11/21

Tree-projected gradient descent for estimating gradient-sparse parameters on graphs

Sheng Xu

Zhou Fan

Sahand Negahban

2020/7/15

Weight-based Neural Network Interpretability using Activation Tuning and Personalized Products

Machine Learning for Computational Biology Workshop (MLCB’20)

Hussein Mohsen

Jonathan Warrell

Martin Renqiang Min

Sahand Negahban

Mark Gerstein

2020

See List of Professors in Sahand Negahban University(Yale University)