Frequent elements on query defined ranges. - Ran Ben-Basat; Rana Shahout; Roy Friedman (INFOCOM Workshops, 2018)

Heavy Hitters over Interval Queries. - Ran Ben-Basat; Roy Friedman; Rana Shahout (CoRR, 2018)

Stream Frequency Over Interval Queries. - Ran Ben-Basat; Roy Friedman; Rana Shahout (Proc. VLDB Endow., 2018)

EvenDB: optimizing key-value storage for spatial locality. - Eran Gilad; Edward Bortnikov; Anastasia Braginsky; Yonatan Gottesman; Eshcar Hillel; Idit Keidar; Nurit Moscovici; Rana Shahout (EuroSys, 2020)

CELL: Counter Estimation for Per-flow Traffic in Streams and Sliding Windows. - Rana Shahout; Roy Friedman; Dolev Adas (ICNP, 2021)

CELL: counter estimation for per-flow traffic over sliding windows. - Rana Shahout; Dolev Adas; Roy Friedman (SYSTOR, 2021)

SQUAD: combining sketching and sampling is better than either for per-item quantile estimation. - Rana Shahout; Roy Friedman; Ran Ben Basat (SYSTOR, 2022)

Box queries over multi-dimensional streams. - Roy Friedman; Rana Shahout (Inf. Syst., 2022)

Sketching the Path to Efficiency: Lightweight Learned Cache Replacement. - Rana Shahout; Roy Friedman (OPODIS, 2023)

Interface Design to Mitigate Inflation in Recommender Systems. - Rana Shahout; Yehonatan Peisakhovsky; Sasha Stoikov; Nikhil Garg 001 (RecSys, 2023)

Together is Better: Heavy Hitters Quantile Estimation. - Rana Shahout; Roy Friedman; Ran Ben Basat (Proc. ACM Manag. Data, 2023)

Press ECCS to Doubt (Your Causal Graph). - Markos Markakis; Ziyu Zhang 002; Rana Shahout; Trinity Gao; Chunwei Liu; Ibrahim Sabek; Michael J. Cafarella (GUIDE-AI@SIGMOD, 2024)

Learning-Based Heavy Hitters and Flow Frequency Estimation in Streams. - Rana Shahout; Michael Mitzenmacher (ICNP, 2024)

Learning-Augmented Frequency Estimation in Sliding Windows. - Rana Shahout; Ibrahim Sabek; Michael Mitzenmacher (ICNP, 2024)

SkipPredict: When to Invest in Predictions for Scheduling. - Rana Shahout; Michael Mitzenmacher (NeurIPS, 2024)

Distributed Recoverable Sketches. - Diana Cohen; Roy Friedman; Rana Shahout (OPODIS, 2024)

Sawmill: From Logs to Causal Diagnosis of Large Systems. - Markos Markakis; An Bo Chen; Brit Youngmann; Trinity Gao; Ziyu Zhang 002; Rana Shahout; Peter Baile Chen; Chunwei Liu; Ibrahim Sabek; Michael J. Cafarella (SIGMOD Conference Companion, 2024)

Fast Inference for Augmented Large Language Models. - Rana Shahout; Cong Liang 005; Shiji Xin; Qianru Lao; Yong Cui 001; Minlan Yu; Michael Mitzenmacher (CoRR, 2024)

Federated Learning Clients Clustering with Adaptation to Data Drifts. - Minghao Li 003; Dmitrii Avdiukhin; Rana Shahout; Nikita Ivkin; Vladimir Braverman; Minlan Yu (CoRR, 2024)

From Logs to Causal Inference: Diagnosing Large Systems. - Markos Markakis; Brit Youngmann; Trinity Gao; Ziyu Zhang 002; Rana Shahout; Peter Baile Chen; Chunwei Liu; Ibrahim Sabek; Michael J. Cafarella (Proc. VLDB Endow., 2024)

Geometric Sketch: The Inflatable-Shrinkable Sketch. - Dvir Biton; Roy Friedman; Rana Shahout (AINA (2), 2025)

Don't stop me Now: Embedding based Scheduling for LLMS. - Rana Shahout; Eran Malach; Chunwei Liu; Weifan Jiang; Minlan Yu; Michael Mitzenmacher (ICLR, 2025)

Queueing, Predictions, and LLMs: Challenges and Open Problems. - Michael Mitzenmacher; Rana Shahout (CoRR, 2025)