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ORCIDMeghna Babbar-Sebens
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2020 – today
- 2024
[c19]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Meghna Babbar-Sebens:
Causal Inference to Enhance AI Trustworthiness in Environmental Decision-Making. AINA (4) 2024: 214-225- 2022
- [c18]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Mimoza Durresi, Meghna Babbar-Sebens:
Trustworthy Fairness Metric Applied to AI-Based Decisions in Food-Energy-Water. AINA (2) 2022: 433-445 - 2021
- [j6]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera
, Arjan Durresi, Meghna Babbar-Sebens, Jenna H. Tilt:
A Trustworthy Human-Machine framework for collective decision making in Food-Energy-Water management: The role of trust sensitivity. Knowl. Based Syst. 213: 106683 (2021) - [c17]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Mimoza Durresi, Meghna Babbar-Sebens:
Trustworthy Acceptance: A New Metric for Trustworthy Artificial Intelligence Used in Decision Making in Food-Energy-Water Sectors. AINA (1) 2021: 208-219 - 2020
- [c16]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Meghna Babbar-Sebens:
Trust-Based Decision Making for Food-Energy-Water Actors. AINA 2020: 591-602 - [c15]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Meghna Babbar-Sebens, Jenna H. Tilt:
Control Theoretical Modeling of Trust-Based Decision Making in Food-Energy-Water Management. CISIS 2020: 97-107 - [c14]Meghna Babbar-Sebens, Kenneth R. Cannady-Shultz, Snehasis Mukhopadhyay:
Interactive Watershed Optimization in the Presence of Spatially-varying and Uncertain Stakeholder Preferences. ICHMS 2020: 1-6
2010 – 2019
- 2019
- [j5]Thanh Nguyen, Snehasis Mukhopadhyay, Meghna Babbar-Sebens:
Why the 'selfish' optimizing agents could solve the decentralized reinforcement learning problems. AI Commun. 32(2): 143-159 (2019) - [j4]Jennifer M. Badham, Sondoss El Sawah, Joseph H. A. Guillaume, Serena H. Hamilton, Randall J. Hunt, Anthony J. Jakeman, Suzanne A. Pierce, Valerie O. Snow, Meghna Babbar-Sebens, Baihua Fu, Patricia Gober, Mary C. Hill, Takuya Iwanaga, Daniel P. Loucks, Wendy S. Merritt, Scott D. Peckham, Amy K. Richmond, Fateme Zare, Gabriele Bammer:
Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities. Environ. Model. Softw. 116: 40-56 (2019) - [c13]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Meghna Babbar-Sebens:
Decision Support System Using Trust Planning Among Food-Energy-Water Actors. AINA 2019: 1169-1180 - [c12]Suleyman Uslu, Davinder Kaur, Samuel J. Rivera, Arjan Durresi, Meghna Babbar-Sebens:
Trust-Based Game-Theoretical Decision Making for Food-Energy-Water Management. BWCCA 2019: 125-136 - [c11]Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay:
Non-Stationary Reinforcement-Learning Based Dimensionality Reduction for Multi-objective Optimization of Wetland Design. ICRAI 2019: 82-86 - [c10]Meghna Babbar-Sebens, Samuel J. Rivera, Eroma Abeysinghe, Suresh Marru, Marlon E. Pierce, Eric Coulter, Majid Farahani, Dimuthu Wannipurage, Marcus Christie:
InterACTWEL Science Gateway for Adaptation Planning in Food-Energy-Water Sectors of Local Communities. PEARC 2019: 110:1-110:4 - 2018
- [c9]Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay:
Uncertainty-Based Deep Learning Networks for Limited Data Wetland User Models. AIVR 2018: 19-26 - [c8]Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay:
Machine Learning with Small Data for User Modeling of Watershed Stakeholders Engaged in Interactive Optimization. CSAI/ICIMT 2018: 22-27 - 2016
- [c7]Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay:
Fuzzy and deep learning approaches for user modeling in wetland design. SMC 2016: 2133-2138 - 2015
- [j3]Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Vidya Bhushan Singh, Adriana Debora Piemonti:
A web-based software tool for participatory optimization of conservation practices in watersheds. Environ. Model. Softw. 69: 111-127 (2015) - 2014
- [c6]Snehasis Mukhopadhyay, Vidya Bhushan Singh, Meghna Babbar-Sebens:
User modeling with limited data: Application to stakeholder-driven watershed design. SMC 2014: 3855-3860 - 2013
- [c5]Vidya Bhushan Singh, Snehasis Mukhopadhyay, Meghna Babbar-Sebens:
User Modelling for Interactive Optimization Using Neural Network. SMC 2013: 3288-3293 - 2012
- [j2]Meghna Babbar-Sebens, Barbara S. Minsker:
Interactive Genetic Algorithm with Mixed Initiative Interaction for multi-criteria ground water monitoring design. Appl. Soft Comput. 12(1): 182-195 (2012) - [c4]Vidya Bhushan Singh, Snehasis Mukhopadhyay, Meghna Babbar-Sebens:
Decentralized pursuit learning automata in batch mode. SCIS&ISIS 2012: 1567-1572 - 2011
- [c3]Omkar J. Tilak, Meghna Babbar-Sebens, Snehasis Mukhopadhyay:
Decentralized and partially decentralized reinforcement learning for designing a distributed wetland system in watersheds. SMC 2011: 271-276 - 2010
- [j1]Meghna Babbar-Sebens, Barbara S. Minsker:
A Case-Based Micro Interactive Genetic Algorithm (CBMIGA) for interactive learning and search: Methodology and application to groundwater monitoring design. Environ. Model. Softw. 25(10): 1176-1187 (2010)
2000 – 2009
- 2009
- [c2]Meghna Babbar-Sebens, Snehasis Mukhopadhyay:
Reinforcement Learning for Human-Machine Collaborative Optimization: Application in Ground Water Monitoring. SMC 2009: 3563-3568 - 2002
- [c1]Meghna Babbar, Barbara S. Minsker:
A Multiscale Master-Slave Parallel Genetic Algorithm with Application to Groundwater Remediation Design. GECCO Late Breaking Papers 2002: 9-16
Coauthor Index
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