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asimibnakhlaque/README.md

ASIM ANSARI

SYSTEMS // AUTONOMOUS AGENTS // MODEL DISTILLATION

STATUS     :: ACTIVE // AI SYSTEMS RESEARCH & ENGINEERING
PORTFOLIO  :: https://asimansari.com
FOCUS      :: SUB-1B SLM DISTILLATION · CYCLIC STATEGRAPHS · HIGH-THROUGHPUT BACKENDS

[01] ARCHITECTURAL PHILOSOPHY

I build small models, deterministic agentic workflows, and resilient backends that run close to the metal.

  • Cyclic State Machines Over Linear Chains: Linear pipelines fail under real-world tool uncertainty. I architect autonomous systems using LangGraph, discrete state machines, explicit state reducers, and bounded self-correction loops.
  • Edge Model Distillation: Distilling multi-turn synthetic action traces into Sub-1B models (SmolLM2-360M, Qwen2.5-0.5B) executing locally on commodity CPU hardware with zero framework bloat.
  • Deterministic Knowledge Retrieval: Grounded hybrid RAG combining ChromaDB dense vectors with Okapi BM25 and AST knowledge graph walks, enforced with sandboxed execution.
  • Resilient Backend Foundations: High-throughput transactional architectures engineered with Java 21 / Spring Boot 3 Virtual Threads and .NET 9 Clean Architecture.

[02] TECHNICAL SPECIFICATIONS

  • Agentic AI & SLMs: LangChain, LangGraph (Cyclic Graphs, Checkpointing, State Reducers), Google GenAI SDK, SLM Distillation, RAG (MMR & Dense/Sparse Hybrid), Unsloth.
  • Languages: Python (FastAPI, AsyncIO, PyTorch), Java (Java 21, Spring Boot 3), C / C++, C# (.NET 9).
  • Databases & Vector Stores: PostgreSQL, SQLite (FTS5 BM25), MongoDB, ChromaDB.
  • Runtime & Infrastructure: Linux / POSIX, Podman / Docker, GGUF CPU inference, Git.

[03] VERIFIED DOSSIER & CONNECT

Pinned Loading

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