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Portrait of Muhammad Shaheer Akhtar
Based in Pakistan & Saudi Arabia--:--:--
Open to work
01 — About

I work at the intersection of AI research and shipping software. Final-year CS at FAST NUCES, IBM-certified, published across quantum computing, federated learning, and agentic LLMs — I bring ideas from a blank file to a system that self-heals in production.

Now building
CloudAide — an AI cloud support engineer
Focus
Agentic LLMs, multi-agent orchestration & Rust
Ships
2 AI MVPs at prAIsm · 3 published papers
Also
Chapter Lead, AI Collective Islamabad

Selected work

(06) — hover to explore ↗
(01) CloudAide Autonomous AI cloud support engineer that self-heals AWS infrastructure — a four-phase retrieval pipeline (bi-encoders → FAISS → cross-encoders → LLaMA 3.1) grounded in a 50,000-row incident dataset. PythonFAISSAWSOllama AI · Retrieval (02) Lucid Orchestrator MCP server built for Lucid Motors: real-time fleet diagnostics over concurrent vehicle streams — async telemetry ingestion, multi-model ML routing, and a two-tier Redis + TimescaleDB state layer. PythonMCPRedisFAISS Enterprise · Lucid Motors (03) Cortex An autonomous agent that plans, acts, and remembers — a self-correcting cognitive loop with 384-dimension vector memory, 4 interchangeable LLM providers, and 3 run modes: CLI, interactive, REST API. PythonAgentic AITool CallingMIT Autonomous Agents (04) Relay An LLM gateway in Rust: BLAKE3 exact-match response caching and automatic OpenAI → Anthropic failover on 5xx and timeouts — cutting latency and inference cost with zero client-code changes. RustLLM InfraCachingFailover Infrastructure · Rust (05) RelocAitor An AI relocation advisor rendered on an interactive 3D WebGL globe, scoring destinations worldwide against your personal preference profile. ReactThree.jsWebGL 3D · AI (06) InsightForge An SRE-grade observability engine closing the full four-stage loop — batched async log ingestion, Elasticsearch-indexed querying, dynamic dashboards, and metrics-driven alerting. FastAPIElasticsearchReactDocker Infra · SRE

Most AI demos never survive contact with production. Mine are built to stay up. I don't hand work off between teams — the retrieval math, the agent, the API, the dashboard — I build every layer myself, so the system that ships is the one I designed.

— 80 signal, 20 noise. That's the whole method.
02 — Published research
P.01

Performance Analysis of Grover's Algorithm under Depolarizing Noise in NISQ Devices

Quantum algorithm robustness under realistic noise conditions on near-term quantum hardware.

Quantum Computing
P.02

Federated Learning for Mental Health Applications: Adaptive & Privacy-Preserving Early Detection

A privacy-first federated architecture for early detection — sensitive data never leaves the device.

Federated ML
P.03

CloudAIde: An Agentic Framework for Autonomous Cloud Infrastructure Remediation Using LLMs

An end-to-end LLM agent framework for detecting, diagnosing, and self-healing cloud incidents.

Agentic AI
03 — Capabilities
(A)AI & Machine Learning+

Retrieval systems and autonomous agents, from the embedding math up to the orchestration layer.

RAG pipelinesFAISS vector searchCross-encoder re-rankingAgentic LLMsFine-tuningPyTorchTensorFlow
(B)Full-Stack Engineering+

Interfaces and services that hold up under real traffic — built end to end, no handoffs.

ReactNext.jsFastAPIFlaskNode / ExpressWebSocketsDesign systems
(C)Cloud & DevOps+

Infrastructure that deploys itself and tells you when something breaks.

AWSDockerLinuxCI/CD · GitHub ActionsNginxObservability
(D)Research & Systems+

Three published papers at the edge of the field — where the interesting problems still are.

Quantum computing (NISQ)Federated learningAgentic frameworksNYAS young member
(E)Cybersecurity+

Offense-informed defence — deception infrastructure, attack telemetry, and asking how a system breaks before shipping it.

Honeypots · CowrieSIEM · Elastic StackNetwork securityThreat telemetryGoogle Cybersecurity cert
(F)Data Analytics+

From raw logs to decisions — cleaning, modelling, and visualising data until it argues for itself.

Python · Pandas · NumPyStatistical analysisData visualisationTimescaleDBGoogle Advanced Data Analytics
04 — Certifications
01
IBM — AI Engineering Professional Certificate
02
DeepLearning.AI — Machine Learning Specialization · Andrew Ng, Stanford Online
03
Google — Advanced Data Analytics
04
Google Cloud — Vertex AI · Advanced Generative AI
05
Anthropic — Responsible AI & Constitutional AI
06
Anthropic — Introduction to Model Context Protocol (MCP)
07
AWS — Cloud Practitioner Essentials
08
Microsoft — Azure AI Fundamentals (AI-900)
09
Google — Cybersecurity Professional
10
Cisco — CCNA: Introduction to Networks
05 — Live from GitHubfetching
Followers
Public repos
Total stars
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Language mix — across repositories

06 — Contact

Let's build
something that ships.

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