Michael Steinbach

Michael Steinbach

University of Minnesota-Twin Cities

H-index: 50

North America-United States

About Michael Steinbach

Michael Steinbach, With an exceptional h-index of 50 and a recent h-index of 29 (since 2020), a distinguished researcher at University of Minnesota-Twin Cities, specializes in the field of Data mining, machine learning, statistics, and bioinformatics.

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

Towards Entity-Aware Conditional Variational Inference for Heterogeneous Time-Series Prediction: An application to Hydrology

Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management

Mini-Batch Learning Strategies for modeling long term temporal dependencies: a study in environmental applications

Causal Structure Learning from Imperfect Longitudinal Data in Healthcare

Strategies for building robust prediction models using data unavailable at prediction time

Integrating scientific knowledge with machine learning for engineering and environmental systems

Realization of causal representation learning to adjust confounding bias in latent space

Physics-guided recurrent neural networks for predicting lake water temperature

Michael Steinbach Information

University

Position

___

Citations(all)

40286

Citations(since 2020)

14782

Cited By

31172

hIndex(all)

50

hIndex(since 2020)

29

i10Index(all)

121

i10Index(since 2020)

59

Email

University Profile Page

University of Minnesota-Twin Cities

Google Scholar

View Google Scholar Profile

Michael Steinbach Skills & Research Interests

Data mining

machine learning

statistics

and bioinformatics

Top articles of Michael Steinbach

Title

Journal

Author(s)

Publication Date

Towards Entity-Aware Conditional Variational Inference for Heterogeneous Time-Series Prediction: An application to Hydrology

Rahul Ghosh

Arvind Renganathan

Wallace McAliley

Michael Steinbach

Christopher Duffy

...

2024

Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management

Somya Sharma Chatterjee

Kelly Lindsay

Neel Chatterjee

Rohan Patil

Ilkay Altintas De Callafon

...

2024

Mini-Batch Learning Strategies for modeling long term temporal dependencies: a study in environmental applications

Shaoming Xu

Ankush Khandelwal

Xiang Li

Xiaowei Jia

Licheng Liu

...

2023

Causal Structure Learning from Imperfect Longitudinal Data in Healthcare

Haoyu Yang

Roshan Tourani

Jia Li

Pedro Caraballo

Michael Steinbach

...

2023/6/26

Strategies for building robust prediction models using data unavailable at prediction time

Journal of the American Medical Informatics Association

Haoyu Yang

Roshan Tourani

Ying Zhu

Vipin Kumar

Genevieve B Melton

...

2022/1/1

Integrating scientific knowledge with machine learning for engineering and environmental systems

ACM Computing Surveys

Jared Willard

Xiaowei Jia

Shaoming Xu

Michael Steinbach

Vipin Kumar

2022/1

Realization of causal representation learning to adjust confounding bias in latent space

arXiv preprint arXiv:2211.08573

Jia Li

Xiang Li

Xiaowei Jia

Michael Steinbach

Vipin Kumar

2022/11/15

Physics-guided recurrent neural networks for predicting lake water temperature

Xiaowei Jia

Jared D Willard

Anuj Karpatne

Jordan S Read

Jacob A Zwart

...

2022/8/15

Regionalization in a global hydrologic deep learning model: from physical descriptors to random vectors

Water Resources Research

Xiang Li

Ankush Khandelwal

Xiaowei Jia

Kelly Cutler

Rahul Ghosh

...

2022/8

Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles

ACM/IMS Transactions on Data Science

Xiaowei Jia

Jared Willard

Anuj Karpatne

Jordan S Read

Jacob A Zwart

...

2021/5/17

Effectiveness of Basin Aware Modulation in a Global Hydrologic Deep Learning Model: from Physical Descriptors to Random Vectors

AGU Fall Meeting Abstracts

Xiang Li

Ankush Khandelwal

Rahul Ghosh

Arvind Renganathan

John Nieber

...

2021/12

Source Aware Modulation for leveraging limited data from heterogeneous sources

Xiang Li

Ankush Khandelwal

Rahul Ghosh

Arvind Renganathan

Jared Willard

...

2021

Are Long short-term memory (LSTM) model simulations of watershed discharge improved when water storage is included as input? The Case Study at Rum River Watershed, MN

AGU Fall Meeting Abstracts

Pai-Feng Teng

John Nieber

Xiang Li

Charles Regan

Christopher Duffy

...

2021/12

Physics-guided recurrent graph model for predicting flow and temperature in river networks

Xiaowei Jia

Jacob Zwart

Jeffrey Sadler

Alison Appling

Samantha Oliver

...

2021

Artificial intelligence for modeling complex systems: taming the complexity of expert models to improve decision making

ACM Transactions on Interactive Intelligent Systems

Yolanda Gil

Daniel Garijo

Deborah Khider

Craig A Knoblock

Varun Ratnakar

...

2021/7/21

Association of BMI, comorbidities and all-cause mortality by using a baseline mortality risk model

PloS one

Jia Li

Gyorgy Simon

M Regina Castro

Vipin Kumar

Michael S Steinbach

...

2021/7/9

A computational method for learning disease trajectories from partially observable EHR data

IEEE journal of biomedical and health informatics

Wonsuk Oh

Michael S Steinbach

M Regina Castro

Kevin A Peterson

Vipin Kumar

...

2021/6/15

Integrating physics-based modeling with machine learning: A survey

Applied Energy

Hao Tu

Scott Moura

Yebin Wang

Huazhen Fang

2023/1/1

Incorporating Causal Effects into Deep Learning Predictions on EHR Data

arXiv preprint arXiv:2011.05466

Jia Li

Haoyu Yang

Xiaowei Jia

Vipin Kumar

Michael Steinbach

...

2020/11/11

Teaching deep learning causal effects improves predictive performance

Scanning Electron Microsc Meet at

Jia Li

Xiaowei Jia

Haoyu Yang

Vipin Kumar

Michael Steinbach

...

2020/11/10

See List of Professors in Michael Steinbach University(University of Minnesota-Twin Cities)