David Walter Wanik
Asst Prof In Res & Director/Operations and Info Management

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Scholarly Contributions

49 Scholarly Contributions

24
Journal Articles
22
Poster/Presentations
2
Conference Proceedings
1
Patent and Intellectual Property
Integration of early warning systems to enhance emergency response to severe weather events
2016
David Wanik
Research Type: Poster/Presentation

LiDAR Modelling of Tree Threats to Power Lines
2016
David Wanik
Research Type: Poster/Presentation

Linking multi-media modeling with machine learning to assess and predict lake chlorophyll a concentrations
2021
Marina Astitha, Epapante Vlahos, Christina Chang
Research Type: Journal Article

Machine learning using combined structural and chemical descriptors for prediction of methane adsorption performance of metal organic frameworks (MOFs)
2017
Steven L Suib, Ranjan Srivastava, David Wanik, Maryam Pardakhti, Ehsan Moharreri
Research Type: Journal Article

NH13D-1970 Evaluation of power outages in Connecticut during hypothetical future Hurricane Sandy scenarios
2015
Brian Hartman, Emmanouil N Anagnostou, David Wanik, Marina Astitha
Research Type: Poster/Presentation

Nonparametric Tree-Based Predictive Modeling of Storm Outages on an Electric Distribution Network
2017
Maria E. Frediani, Marina Astitha, Emmanouil N Anagnostou, Brian Hartman, David Wanik, Jichao He
Research Type: Journal Article

On the Sensitivity of a Machine Learning-Based Model to Predict Chlorophyll- Using Multi-Media Modeling Environmental Predictors
2020
Valerie Garcia, Chunling Tang, Epapante Vlahos, Christina Feng Chang, Jesse Bash, David Wanik, Marina Astitha
Research Type: Poster/Presentation

Predicting County-Level Population From VIIRS Nighttime Light Imagery With Deep Learning
2024
David Wanik, Vineela Datla, Viswadeep Lebakula, Arthur G. Cosby
Research Type: Journal Article

Predicting County-Level Population from VIIRS Nighttime Light Imagery with Deep Learning
Vineela Datla, Viswadeep Lebakula, David Wanik, Arthur Cosby
Research Type: Journal Article

Predicting Energy Demand Using Machine Learning: Exploring Temporal and Weather-Related Patterns, Variations, and Impacts
2024
Diego Cerrai, Kingsley Udeh, David Wanik, Buket Sahin
Research Type: Journal Article

Predicting Storm Outages Through New Representations of Weather and Vegetation
2019
Emmanouil N Anagnostou, Jaemo Yang, Md Abul Bhuiyan, Diego Cerrai, Xinxuan Zhang, David Wanik, Maria E.B. Frediani
Research Type: Journal Article

Probabilistic Storm and Electric Utility Customer Outage Prediction
Kingsley Udeh, Diego Cerrai, Derek C Aguiar, Emmanouil N Anagnostou, David Wanik
Research Type: Journal Article

Quantifying uncertainty in machine learning-based power outage prediction model training: A tool for sustainable storm restoration
2020
Emmanouil N Anagnostou, David Wanik, Feifei Yang, Diego Cerrai, Md Abdul Ehsan Bhuiyan
Research Type: Journal Article

Storm outage modeling for an electric distribution network in Northeastern USA
2015
M. E.B. Frediani, Brian Hartman, David Wanik, Marina Astitha, Emmanouil N Anagnostou
Research Type: Journal Article

Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas
2017
Miguel Roman, Robert Griffin, Tony Cole, Andrew Molthan, David Wanik
Research Type: Journal Article

Systems and Methods for Outage Prediction
2021
Emmanouil N. Anagnostou
Research Type: Patent and Intellectual Property

The Economic case for predicting Storm damages at Electric Distribution Utilities
2017
David Wanik
Research Type: Poster/Presentation

Time Series Modeling of Storm Outages with Weather Mesonet Data for Emergency Preparedness and Response
David Wanik, Nick Bassill, Kingsley Udeh, Emmanouil N Anagnostou
Research Type: Conference Proceedings

Updates on Using Multi-media Modeling to Investigate Conditions Leading to Harmful Algal Blooms
2018
Valerie Garcia, Christina Feng Chang, David Wanik, Marina Astitha, Epapante Vlahos, Ellen Cooter
Research Type: Poster/Presentation

Updates on the Assessment of Environmental Variables Affecting Chlorophyll-a through Multi-media Modeling and Machine Learning: a Lake Erie Case Study
2020
Valerie Garcia, Epapante Vlahos, David Wanik, Christina Feng Chang, Jesse Bash, Marina Astitha, Chunling Tang
Research Type: Poster/Presentation