Ran Ben Basat
Associate Professor
Designs streaming and compression algorithms for networks and distributed systems, including gradient compression for distributed machine learning training.
Ran Ben Basat's lab at UCL works on efficient training & inference and distributed, cloud & edge systems. 22 papers since 2023, 9 at top venues, mostly SIGCOMM and ICDE. 2 PhD students.
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 41%
- PhD students
- 2
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 7 papers2026 · T1 4 · collecting
- 2 papers2025 · T1 0
- 9 papers2024 · T1 3
- 4 papers2023 · T1 2
T1 venuesOtherVenues: SIGCOMM, ICDE, NeurIPS, ICML, SIGMOD
Research focuspaper titles that use each topic's words
- Efficient training & inference4 papers
- compression4 papers
- Distributed, cloud & edge systems3 papers
- distributed3 papers
- learning training0 papers
Paper list
From the lab homepage.
20267 papers
- ACM SIGMETRICSBetter than Optimal: Improving Adaptive Stochastic Quantization Using Shared Randomness
- IEEE/IFIP NOMSCounter Pools: Counter Representation for Efficient Stream Processing
- SIGCOMM (T1)DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce
- ACM SIGOPS ATCHACK: Homomorphic Acceleration via Compression of the Key-Value Cache for Disaggregated LLM Inference
- SIGCOMM (T1)Honey, I Shrunk the Headers With Flow.ZIP
- NeurIPS (T1)Quantizing With Randomized Hadamard Transforms: Efficient Heuristic Now Proven
- ICDE (T1)Spatiotemporal Sketch Disaggregation: Streaming Analytics with Heterogeneous Resources
20252 papers
- ACM SPAABounded Memory in Distributed Networks
- USENIX NSDIEnabling Silent Telemetry Data Transmission with InvisiFlow
20249 papers
- IEEE/ACM Transactions on NetworkingA Generic Framework for Finding Special Quadratic Elements in Data Streams
- ICML (T1)Accelerating Federated Learning with Quick Distributed Mean Estimation
- ACM HotNetsBeyond Throughput and Compression Ratios: Towards High End-to-end Utility of Gradient Compression
- ICDE (T1)DISCO: A Dynamically Configurable Sketch Framework in Skewed Data Streams
- ACM CoNEXTF3: Fast and Flexible Network Telemetry with an FPGA coprocessor
- NeurIPS (T1)Optimal and Approximate Adaptive Stochastic Quantization
- ACM CoNEXTSQUID: Faster Analytics via Sampled Quantile Estimation
- USENIX NSDITHC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression
- ACM HotNetsWhen ML Training Cuts Through Congestion: Just-in-Time Gradient Compression via Packet Trimming
20234 papers
- USENIX ATCAdaptive Online Cache Capacity Optimization via Lightweight Working Set Size Estimation at Scale
- SIGCOMM (T1)Direct Telemetry Access
- ACM SIGCOMM CCRFast In-kernel Traffic Sketching in eBPF
- SIGMOD (T1)Together is Better: Heavy Hitters Quantile Estimation
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UCLFall 2027
Not announced yet
Computer Science MPhil/PhD
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Your notes
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Data
Some numbers could not be verified:
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.