| Smoothed online optimization with unreliable predictions D Rutten, N Christianson, D Mukherjee, A Wierman Proceedings of the ACM on Measurement and Analysis of Computing Systems 7 (1 …, 2023 | 17* | 2023 |
| Load balancing under strict compatibility constraints D Rutten, D Mukherjee Mathematics of Operations Research 48 (1), 227-256, 2023 | 14 | 2023 |
| Load balancing under strict compatibility constraints D Rutten, D Mukherjee Abstract Proceedings of the 2021 ACM SIGMETRICS/International Conference on …, 2021 | 9 | 2021 |
| Mean-field Analysis for Load Balancing on Spatial Graphs D Rutten, D Mukherjee Abstract Proceedings of the 2023 ACM SIGMETRICS/International Conference on …, 2023 | 6 | 2023 |
| A new approach to capacity scaling augmented with unreliable machine learning predictions D Rutten, D Mukherjee Mathematics of Operations Research 49 (1), 476-508, 2024 | 4 | 2024 |
| Capacity scaling augmented with unreliable machine learning predictions D Rutten, D Mukherjee ACM SIGMETRICS Performance Evaluation Review 49 (2), 24-26, 2022 | 2 | 2022 |
| Distributed Rate Scaling in Large-Scale Service Systems D Rutten, M Zubeldia, D Mukherjee ACM SIGMETRICS Performance Evaluation Review 51 (2), 21-23, 2023 | | 2023 |
| Modeling Rydberg gases using random sequential adsorption on random graphs D Rutten, J Sanders Physical Review A 103 (3), 033302, 2021 | | 2021 |
| Semi-online algorithms for power-aware load balancing D Rutten, D Mukherjee, M de Berg, S Borst | | 2020 |
| Random intersection graphs as a quantitative model for the Rydberg blockade effect D Rutten | | 2018 |
Debankur MukherjeeLeo and Louise Benatar Early Career Professor and Assistant Professor, Georgia TechVerified email at isye.gatech.edu
