Rana Shahout

rana@seas.harvard.edu

I am a Postdoctoral fellow at Harvard University, working with Michael Mitzenmacher and Minlan Yu.

I develop algorithms for data-intensive systems, with a focus on LLM inference, as well as streaming and queueing. I use theory and machine learning to guide efficient and reliable design.

Short bio:

I received my Ph.D. from the Department of Computer Science at Technion, advised by Roy Friedman. Before that, I worked at Mellanox (Nvidia now) as a senior software engineer. I also received my B.Sc. and M.Sc. from Technion.

News:

Sept 25': Mars for fast inference for augmented LLMs has been accepted to NeurIPS 2025
June 25': "Queueing, Predictions, and Large Language Models: Challenges and Open Problems" has been accepted to Stochastic Systems.
June 25': We presented a tutorial at SIGMETRICS 2025 on queueing systems, predictions, and LLM inference [slides].
April 25': Two papers, "Faster, Cheaper, Just as Good" and "Prefix and Output Length-Aware Scheduling for Efficient Online LLM Inference" will appear at the ICLR Workshop on Sparsity in LLMs (SLLM).
Mar 25': We uploaded a paper to arXiv on how queueing theory helps in understanding and improving LLM inference.
Jan 25': "DON’T STOP ME NOW:EMBEDDING BASED SCHEDULING FOR LLMS" has been accepted to ICLR 2025.
Oct 24': We uploaded a paper on fast inference for augmented LLMs to the arxiv.
Oct 24': "Distributed Recoverable Sketches" has been accepted to OPODIS 2024.
Oct 24': We uploaded a paper on embedding based scheduling for LLMs to the arxiv.
Oct 24': "Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing" has been accepted to CIDR 2025.
Sept 24': "SkipPredict: When to Invest in Predictions for Scheduling" has been accepted to NeurIPS 2024.
Sept 24': "From Logs to Causal Inference: Diagnosing Large Systems" has been accepted to VLDB 2025.
Aug 24': "Learning-Augmented Frequency Estimation in Sliding Windows" has been accepted as a workshop to IEEE ICNP 2024.
Jul 24': "Learning-Based Heavy Hitters and Flow Frequency Estimation in Streams" has been accepted to IEEE ICNP 2024.
Jun 24': We uploaded a paper on learning-based heavy hitters and flow frequency estimation in streams to the arXiv.
Jun 24': "Press ECCS to Doubt (Your Causal Graph)" has been accepted to GUIDE-AI@SIGMOD 2024 and got the best paper award!
Mar 24': "Sawmill: From Logs to Causal Diagnosis of Large Systems" has been accepted as a demo to SIGMOD 2024.
Feb 24': We uploaded our paper on when to invest in predictions for scheduling to the arXiv.
Nov 23': "Sketching the Path to Efficiency: Lightweight Learned Cache Replacement" has been accepted to OPODIS 2023.
Jul 23': I have been awarded the Zuckerman Postdoctoral Fellowship
Jul 23': I have been awarded the Israeli Council for Higher Education Postdoctoral Fellowship
Jul 23': "Interface Design to Mitigate Inflation in Recommender Systems" has been accepted to RecSys 2023

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Rana Shahout

News:

Sept 25': Mars for fast inference for augmented LLMs has been accepted to NeurIPS 2025

June 25': "Queueing, Predictions, and Large Language Models: Challenges and Open Problems" has been accepted to Stochastic Systems.

June 25': We presented a tutorial at SIGMETRICS 2025 on queueing systems, predictions, and LLM inference [slides].

April 25': Two papers, "Faster, Cheaper, Just as Good" and "Prefix and Output Length-Aware Scheduling for Efficient Online LLM Inference" will appear at the ICLR Workshop on Sparsity in LLMs (SLLM).

Mar 25': We uploaded a paper to arXiv on how queueing theory helps in understanding and improving LLM inference.

Jan 25': "DON’T STOP ME NOW:EMBEDDING BASED SCHEDULING FOR LLMS" has been accepted to ICLR 2025.

Oct 24': We uploaded a paper on fast inference for augmented LLMs to the arxiv.

Oct 24': "Distributed Recoverable Sketches" has been accepted to OPODIS 2024.

Oct 24': We uploaded a paper on embedding based scheduling for LLMs to the arxiv.

Oct 24': "Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing" has been accepted to CIDR 2025.

Sept 24': "SkipPredict: When to Invest in Predictions for Scheduling" has been accepted to NeurIPS 2024.

Sept 24': "From Logs to Causal Inference: Diagnosing Large Systems" has been accepted to VLDB 2025.

Aug 24': "Learning-Augmented Frequency Estimation in Sliding Windows" has been accepted as a workshop to IEEE ICNP 2024.

Jul 24': "Learning-Based Heavy Hitters and Flow Frequency Estimation in Streams" has been accepted to IEEE ICNP 2024.

Jun 24': We uploaded a paper on learning-based heavy hitters and flow frequency estimation in streams to the arXiv.

Jun 24': "Press ECCS to Doubt (Your Causal Graph)" has been accepted to GUIDE-AI@SIGMOD 2024 and got the best paper award!

Mar 24': "Sawmill: From Logs to Causal Diagnosis of Large Systems" has been accepted as a demo to SIGMOD 2024.

Feb 24': We uploaded our paper on when to invest in predictions for scheduling to the arXiv.

Nov 23': "Sketching the Path to Efficiency: Lightweight Learned Cache Replacement" has been accepted to OPODIS 2023.

Jul 23': I have been awarded the Zuckerman Postdoctoral Fellowship

Jul 23': I have been awarded the Israeli Council for Higher Education Postdoctoral Fellowship

Jul 23': "Interface Design to Mitigate Inflation in Recommender Systems" has been accepted to RecSys 2023