Profile

Sudha Ram

Professor, Computer Science | Professor, Management Information Systems | Professor, Remote Sensing / Spatial Analysis - GIDP | Professor, BIO5 Institute | Member of the Graduate Faculty

Management Information Systems

Collaboration(40)

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Grants(8)

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Publications(172)

Recent

A Reduced Modeling Approach for Making Predictions with Incomplete Data Having Blockwise Missing Patterns

2024

predictive modeling, data imputation, machine learning

A Human-in-the-LooSegmented Mixed-Effects Modeling Method for Analyzing Wearables Data

2023

wearable technology, mixed-effects modeling, human activity analysis, data analysis, health monitoring

Discovery of associative patterns between workplace sound level and physiological wellbeing using wearable devices and empirical Bayes modeling

2023

physiological wellbeing, workplace environment, wearable devices, associative patterns, empirical bayes modeling

Rewarded Advertising and Mobile User Engagement: A Large-Scale Field Experiment

2022

advertising, mobile, user engagement, field experiment, rewarded

ROLEX: A Novel Method for Interpretable Machine Learning Using Robust Local Explanations

2022

machine learning, interpretability, local explanations, novel method, robustness

Toward NEPA Performance: A framework for assessing EIAs

2022

environmental impact assessment, framework, performance assessment, nepa compliance, environmental policy

Health care Predictive Analytics for Short Term Multiple Disease Prediction in Critical Care Overall Best Paper award)

2021

healthcare, predictive analytics, disease prediction, critical care, data science

Intention-based DeeLearning Approach for Detecting Online Fake News BEst Paper of ICIS Award)

2021

fake news detection, deep learning, online misinformation, information credibility, intent analysis

Focusing on High Impact Programmatic Research in Information Systems, Not Theory, to Address Grand Challenges

2021

programmatic research, information systems, grand challenges, high impact, practical solutions

Fool Me Twice, Shame on Me: Structural Balance Theory Based DeeLearning Model for Identifying False Information

2021

deelearning models, false information, structural balance theory, identifying, deception detection

Profile

Sudha Ram

Collaboration(40)

Hao Zhang

Marc Miller

Nirav Merchant

Esther Sternberg

Karletta Chief

Grants(8)

Publications(172)

A Reduced Modeling Approach for Making Predictions with Incomplete Data Having Blockwise Missing Patterns

A Human-in-the-LooSegmented Mixed-Effects Modeling Method for Analyzing Wearables Data

Discovery of associative patterns between workplace sound level and physiological wellbeing using wearable devices and empirical Bayes modeling

Rewarded Advertising and Mobile User Engagement: A Large-Scale Field Experiment

ROLEX: A Novel Method for Interpretable Machine Learning Using Robust Local Explanations

Toward NEPA Performance: A framework for assessing EIAs

Health care Predictive Analytics for Short Term Multiple Disease Prediction in Critical Care Overall Best Paper award)

Intention-based DeeLearning Approach for Detecting Online Fake News BEst Paper of ICIS Award)

Focusing on High Impact Programmatic Research in Information Systems, Not Theory, to Address Grand Challenges

Fool Me Twice, Shame on Me: Structural Balance Theory Based DeeLearning Model for Identifying False Information