I am best known for designing search technologies deployed on hundreds of millions of devices, which power some of the largest tech companies, unicorns and decacorns, AI research labs, and defense and intelligence organizations worldwide. In short:
- CS/AI researcher.
- Trained in Astrophysics.
- Ex Investor - cloud and semiconductors.
- Fluent in English, Russian & Armenian.
- Building Unum Cloud since 2015.
I spent most of the last 20 years writing code. Mostly GPGPU and SIMD. Prefer spaces over tabs, east-const, and procedural programming over object-oriented or functional. Abstractions are evil. Assembly is nice. If you want to get in touch and contribute - my handle is @ashvardanian on most platforms, including Twitter and LinkedIn.
I've designed and maintain the following libraries, datasets, and AI models:
- StringZilla - fast strings processing library for C, C++, Rust, Python, and Swift, replacing GlibC and STL
- USearch - single-file search engine for C, C++, Rust, Swift, Go, Java, C#, Python, JavaScript..., replacing FAISS
- UForm - small multimodal pre-trained AI models with SDKs for Python, JavaScript, and Swift, replacing CLIP
- UCall - backend networking library for C and Python designed with efficient kernel bypass, replacing FastAPI
- UStore - multimodal embedded database for C, C++, and Python designed around key-value stores
- SimSIMD - fast vector-vector math library for C, Python, Rust, and JavaScript, replacing BLAS level 1
- USearch-Molecules - 28 billion embeddings of small molecules for chem-informatics & pharma
Smaller projects include:
- affine-gaps - Less wrong local and global Gotoh sequence alignments in one NumBa Python file
- ParallelReductionsBenchmark - GPGPU benchmarks for SyCL, CUDA, OpenCL, Vulkan, and other parallel tech
- SwiftSemanticSearch - example of on-device real-time AI using UForm and USearch on iOS
- BenchmarkingTutorial - C/C++ tutorial for performance-oriented programming using Google Benchmark
- memchr_vs_stringzilla - Rust micro-benchmark comparing StringZilla to the MemChr crate
- usearch-benchmarks - Billion-scale benchmarks against FAISS, Weaviate, Qdrant, etc.
- ucsb - parallel benchmarks for ACID persistent key-value stores, like RocksDB