Research that moves from theory to production
Our research teams work at the edges of systems, machine learning, and scientific computing — publishing openly and shipping the results into real-world deployments.
40+
Peer-reviewed papers
12
Open-source projects
7
Active research areas
Where we focus
Cross-disciplinary teams pursuing open problems with measurable, deployable outcomes.
High-Performance Systems
Memory allocators, lock-free data structures, and runtime schedulers engineered for predictable performance at scale.
Machine Learning
Efficient training and inference, model compression, and retrieval-augmented architectures for production workloads.
Scientific Computing
Abstraction layers and numerical methods that make large-scale simulation portable across heterogeneous hardware.
Distributed Systems
Consensus, replication, and fault-tolerance primitives for low-latency services spanning regions and clouds.
Security & Cryptography
Applied cryptography, confidential computing, and formal verification of safety-critical software components.
Compilers & Languages
Domain-specific languages and optimizing compilers that close the gap between expressive code and bare-metal speed.
Selected publications
A sample of recent work from our research teams, published at leading venues.
- OSDI 2026
Virtualmalloc: A Tier-Aware Allocator for Predictable Tail Latency
- NeurIPS 2025
Sparse Retrieval Without the Index: Streaming Memory for Long-Context Models
- SC 2025
Portable Abstraction Layers for High-Performance Scientific Simulation
- SOSP 2024
Deterministic Scheduling for Multi-Tenant GPU Clusters