2025
Iyer, R., Christie, AP., Madhavapeddy, A., Reynolds, S., Sutherland, W. and Jaffer, S., 2025. Careful design of Large Language Model pipelines enables expert-level retrieval of evidence-based information from syntheses and databases Plos One, v. 20
Doi: http://doi.org/10.1371/journal.pone.0323563
Reynolds, SA., Beery, S., Burgess, N., Burgman, M., Butchart, SHM., Cooke, SJ., Coomes, D., Danielsen, F., Di Minin, E., Durán, AP., Hinsley, A., Jaffer, S., Jones, JPG., Li, BV., Madhavapeddy, A., Peck, L., Pettorelli, N., Rodríguez, JP. and Sutherland, WJ., 2025. Conservation changed but not divided Trends in Ecology and Evolution, v. 40
Doi: http://doi.org/10.1016/j.tree.2025.04.002
2024 (Published online)
Collins, M., Beverley, JD., Bracegirdle, TJ., Catto, J., McCrystall, M., Dittus, A., Freychet, N., Grist, J., Hegerl, GC., Holland, PR., Holmes, C., Josey, SA., Joshi, M., Hawkins, E., Lo, E., Lord, N., Mitchell, D., Monerie, P-A., Priestley, MDK., Scaife, A., Screen, J., Senior, N., Sexton, D., Shuckburgh, E., Siegert, S., Simpson, C., Stephenson, DB., Sutton, R., Thompson, V., Wilcox, LJ. and Woollings, T., 2024 (Published online). Emerging signals of climate change from the equator to the poles: new insights into a warming world Frontiers in Science, v. 2
Doi: 10.3389/fsci.2024.1340323
2024 (No publication date)
2024
Wilkins, G., Keshav, S. and Mortier, R., 2024. Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems ACM SIGEnergy Energy Informatics Review, v. 4
Doi: 10.1145/3727200.3727217
Rau, E-P., Gross, J., Coomes, DA., Swinfield, T., Madhavapeddy, A., Balmford, A. and Keshav, S., 2024. Mitigating risk of credit reversal in nature-based climate solutions by optimally anticipating carbon release Carbon Management, v. 15
Doi: 10.1080/17583004.2024.2390854
Rau, E-P., Gross, J., Coomes, DA., Swinfield, T., Madhavapeddy, A., Balmford, A. and Keshav, S., 2024. Research data supporting “Mitigating risk of credit reversal in nature-based climate solutions by optimally anticipating carbon release”
Doi: 10.17863/CAM.110933
Jaffer, S., Dales, MW., Ferris, P., Sorensen, D., Swinfield, T., Message, R., Keshav, S. and Madhavapeddy, A., 2024. Global, robust and comparable digital carbon assets 2024 IEEE International Conference on Blockchain and Cryptocurrency Icbc 2024,
Doi: 10.1109/ICBC59979.2024.10634343
Jaffer, S., Dales, MW., Ferris, P., Sorensen, D., Swinfield, T., Message, R., Keshav, S. and Madhavapeddy, A., 2024. Global, robust and comparable digital carbon assets. ICBC,
Swinfield, T., Shrikanth, S., Bull, JW., Madhavapeddy, A. and zu Ermgassen, SOSE., 2024. Nature-based credit markets at a crossroads Nature Sustainability, v. 7
Doi: 10.1038/s41893-024-01403-w
Nath, P., Moss, H., Shuckburgh, E. and Webb, M., 2024. RAIN: Reinforcement Algorithms for Improving Numerical Weather and Climate Models. CoRR, v. abs/2408.16118
Millar, J., Sethi, S., Haddadi, H. and Madhavapeddy, A., 2024. Poster: Towards Low-Power Comprehensive Biodiversity Monitoring Sensys 2024 Proceedings of the 2024 ACM Conference on Embedded Networked Sensor Systems,
Doi: 10.1145/3666025.3699400
Jaffer, S., Dales, MW., Ferris, P., Sorensen, D., Swinfield, T., Message, R., Keshav, S. and Madhavapeddy, A., 2024. Global, robust and comparable digital carbon assets 2024 IEEE International Conference on Blockchain and Cryptocurrency Icbc 2024,
Doi: 10.1109/ICBC59979.2024.10634343
Berkes, A. and Keshav, S., 2024. SPAGHETTI: a synthetic data generator for post-Covid electric vehicle usage Energy Informatics, v. 7
Doi: 10.1186/s42162-024-00314-6
Nivron, O., Wischik, DJ., Vrac, M. and Shuckburgh, E., 2024. A Temporal Bias Correction using a Machine Learning Attention model. CoRR, v. abs/2402.14169
Holcomb, A., Burns, P., Keshav, S. and Coomes, DA., 2024. Repeat GEDI footprints measure the effects of tropical forest disturbances Remote Sensing of Environment, v. 308
Doi: 10.1016/j.rse.2024.114174
Berkes, A. and Keshav, S., 2024. SOPEVS: Sizing and Operation of PV-EV-Integrated Modern Homes The 15th ACM International Conference on Future and Sustainable Energy Systems,
Doi: 10.1145/3632775.3661941
Vijayakumar, S., Madhavapeddy, A. and Kalyvianaki, E., 2024. Scheduling for Reduced Tail Task Latencies in Highly Utilized Datacenters Socc 2024 Proceedings of the 2024 ACM Symposium on Cloud Computing,
Doi: 10.1145/3698038.3698522
Wilkins, G., Keshav, S. and Mortier, R., 2024. Hybrid Heterogeneous Clusters Can Lower the Energy Consumption of LLM Inference Workloads The 15th ACM International Conference on Future and Sustainable Energy Systems,
Doi: 10.1145/3632775.3662830
