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Rahman, Aowabin
35  Ergebnisse:
Personensuche X
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1

A Computational Framework for Control Co-Design of Resilien..:

Ramachandran, Thiagarajan ; Vasisht, Soumya ; Rahman, Aowabin..
IEEE Transactions on Control Systems Technology.  32 (2024)  3 - p. 793-804 , 2024
Link: https://doi.org/10.1109/..
 
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2

Collaboration and Negotiation:

, In: Advances in Information Security; Autonomous Intelligent Cyber Defense Agent (AICA),
Chatterjee, Samrat ; Bhattacharya, Arnab ; Dutta, Ashutosh... - p. 229-251 , 2023
Link: https://doi.org/10.1007/..
 
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3

Copper: a performance curve generator for buildingenergy si..:

Lerond, Jérémy ; Rahman, Aowabin ; Zhang, Jian.
Journal of Open Source Software.  8 (2023)  82 - p. 4876 , 2023
Link: https://doi.org/10.21105..
 
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4

tell: a Python package to model future totalelectricity loa..:

McGrath, Casey R. ; Burleyson, Casey D. ; Khan, Zarrar...
Journal of Open Source Software.  7 (2022)  79 - p. 4472 , 2022
Link: https://doi.org/10.21105..
 
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5

Multi-fidelity Bayesian Optimization for Co-design of Resil..:

, In: 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS),
Vasisht, Soumya ; Rahman, Aowabin ; Ramachandran, Thiagarajan.. - p. 298-299 , 2022
Link: https://doi.org/10.1109/..
 
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6

AdverSAR: Adversarial Search and Rescue via Multi-Agent Rei..:

, In: 2022 IEEE International Symposium on Technologies for Homeland Security (HST),
Rahman, Aowabin ; Bhattacharya, Arnab ; Ramachandran, Thiagarajan... - p. 1-7 , 2022
Link: https://doi.org/10.1109/..
 
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7

Neural Ordinary Differential Equations for Nonlinear System..:

, In: 2022 American Control Conference (ACC),
Rahman, Aowabin ; Drgona, Jan ; Tuor, Aaron. - p. 3979-3984 , 2022
Link: https://doi.org/10.23919..
 
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8

On-policy learning-based deep reinforcement learning assess..:

Lee, Joon-Yong ; Rahman, Aowabin ; Huang, Sen..
Science and Technology for the Built Environment.  28 (2022)  9 - p. 1150-1165 , 2022
Link: https://doi.org/10.1080/..
 
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9

Methodology and analytical approach to investigate the impa..:

Rahman, Aowabin ; Smith, Amanda D. ; Xie, Yulong..
Journal of Building Performance Simulation.  15 (2022)  1 - p. 128-147 , 2022
Link: https://doi.org/10.1080/..
 
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10

Investigating the efficacy of machine learning tools in mod..:

Shirolkar, Narayan ; Patwardhan, Prachi ; Rahman, Aowabin..
Carbon.  174 (2021)  - p. 605-616 , 2021
Link: https://doi.org/10.1016/..
 
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11

Multiscale effects masked the impact of the COVID-19 pandem..:

Burleyson, Casey D. ; Rahman, Aowabin ; Rice, Jennie S...
Applied Energy.  304 (2021)  - p. 117711 , 2021
Link: https://doi.org/10.1016/..
 
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12

A machine learning framework for predicting the shear stren..:

Rahman, Aowabin ; Deshpande, Prathamesh ; Radue, Matthew S....
Composites Science and Technology.  207 (2021)  - p. 108627 , 2021
Link: https://doi.org/10.1016/..
 
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13

A void descriptor function to uniquely characterize pore ne..:

Erickson, John M. ; Rahman, Aowabin ; Spear, Ashley D.
International Journal of Fracture.  225 (2020)  1 - p. 47-67 , 2020
Link: https://doi.org/10.1007/..
 
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14

Flexible Reinforcement Learning Framework for Building Cont..:

, In: Proceedings of the 1st International Workshop on Reinforcement Learning for Energy Management in Buildings & Cities,
Lee, Joon-Yong ; Huang, Sen ; Rahman, Aowabin.. - p. 34-38 , 2020
Link: https://dl.acm.org/doi/1..
 
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15

Predicting Microstructure-Sensitive Fatigue-Crack Path in 3..:

Pierson, Kyle ; Rahman, Aowabin ; Spear, Ashley D.
JOM.  71 (2019)  8 - p. 2680-2694 , 2019
Link: https://doi.org/10.1007/..
 
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