I am a specialized AI Systems Engineer focused on building offline-first AI media production tools, self-hosted LLM infrastructure, and multi-agent automation pipelines. My recent work spans the full spectrum — from ONNX model export pipelines and local inference routing to multi-lane video editors, 2D lip sync studios, and LangGraph-orchestrated content automation — all running entirely on local hardware.

• 40+ Active Codebases spanning offline video production, local AI runtimes, voice synthesis, LLM fine-tuning, and enterprise automation.
• Offline-First Philosophy: Every tool I build runs without cloud dependencies — TTS, SFX, video stitching, lip sync, and sketch animation all on-device.
• Production AI Deployments: Veteran of enterprise SaaS backends, browser automation agents, local AI OS builds, and ONNX inference pipelines.

I am applying for doctoral positions in medical imaging AI. The question I want to work on: given a 3D scan and a clinician's question about it, produce an answer in plain clinical language that points to the exact voxels it came from — where segmentation, visual grounding and language stop being three fields and become one.

The gap I keep running into is between fluent output and grounded output. Fine-tuning a vision-language model on radiography produces report-like text almost immediately; establishing that the text is traceable to a region of the image is a much harder problem, and the one I want to work on properly.

Academic service. Conference organiser for ICPSE-2021, ICPSE-2022 (International Conferences on Physical Sciences & Engineering) and ICSMAND (9th International Conference on Semiconductor Materials & Nano-Devices). President of the Natural Resources Defence Council & Society at KFUEIT. Organised the 1st South Punjab Science Mela, 2021.

📄 Full CV (PDF) · 🔬 Research profile for academic readers

Here is a curated overview of my primary repositories representing deep engineering focus and production capabilities:

A locally-run, offline-first Windows desktop application that automates voiceover generation, sound effect creation, and multi-lane video stitching — entirely without any cloud dependency.

• Engineering Highlights:
  • Multi-Lane Timeline Editor: Drag, reorder, split, merge, and edit clips across 3 independent lanes with a browser-based UI.
  • Local TTS Engine: Generates realistic voiceovers from text scripts entirely on-device using PocketTTS.
  • Local SFX Engine: Generates sound effects from text prompts using ONNX-exported Stable Audio 3 Small, running fully on CPU.
  • Auto-Captions: Word-by-word caption overlays burned into final video via FFmpeg drawtext filters.
  • Background Music Mixer: Mixes ambient music tracks with adjustable volume into the final rendered output.
  • Rebuilt Timeline UI: Sticky-scroll track headers/ruler and stable React keys eliminate audio stutter and DOM rebuild lag during playback.
• Key Stack: Python, FFmpeg, ONNX Runtime, PocketTTS, FastAPI, WebSockets, React.

A self-hosted, open-source, air-gapped AI runtime Operating System — enabling companies, developers, and researchers to orchestrate state-of-the-art AI agents and multi-model workflows completely locally, from an RTX 2070 laptop to enterprise clusters.

• Engineering Highlights:
  • Universal Inference Layer: Abstracts backend engines (Ollama, vLLM, SGLang, llama.cpp, TensorRT) under a single dynamic routing API.
  • Hybrid Memory System: Merges semantic vector embeddings (Qdrant) and entity-relationship knowledge graphs (FalkorDB) for human-like agent context recall.
  • Distributed Task Orchestration: Celery + Valkey Streams drive parallelized multi-agent loops and complex DAG workflows.
  • Zero API Keys, 100% Privacy: No external phone-homes, no vendor lock-in, fully air-gapped deployment.
• Key Stack: Python, FastAPI, Celery, Valkey Streams, Qdrant, FalkorDB, Ollama, vLLM, Docker.

A locally-run, offline-first Windows desktop application for 2D animators — automatically generating frame-accurate lip-sync video from character sprites and a dialogue script.

• Engineering Highlights:
  • Phoneme Detection: Rhubarb Lip Sync extracts mouth shape timings (phonemes A–X) at frame-level accuracy from generated or provided WAV audio.
  • Character Studio: Upload full-body character images, define face regions, and map custom mouth sprites to each phoneme.
  • Script-Driven Voice: [Character Name] tagged dialogue scripts converted to audio locally via PocketTTS.
  • ONNX Face Tracking: Optional ONNX-based face/gaze tracking for characters with animated heads.
  • Video Compositor: Composites frames + mouth sprites + audio into final MP4s via FFmpeg — no external rendering software needed.
• Key Stack: Python, Rhubarb Lip Sync, ONNX Runtime, FFmpeg, PocketTTS, FastAPI.

A fully automated, sequential content pipeline that discovers viral YouTube videos, writes original scripts, generates TTS audio + AI images + whiteboard sketch animations, and uploads to YouTube — orchestrated by LangGraph multi-agents.

• Engineering Highlights:
  • LangGraph DAG Agents: Full viral_finder → await_approval → data_collection → script_generation → media_generation → upload pipeline with crash-safe resumption via Supabase pipeline_stage state.
  • Thin-State Architecture: LangGraph state holds only IDs — every agent reads inputs fresh from Supabase/GCS and writes outputs back, eliminating context bloat.
  • Human-in-the-Loop Gate: await_approval polls yt_results.approved — a human reviews generated scripts before media production begins.
  • Integrated Sketch Animation: Converts AI-generated images into whiteboard sketch animations using Omni Sketches on GCP VM.
• Key Stack: Python, LangGraph, FastAPI, APScheduler, Supabase, Google Cloud Storage, FFmpeg, Gemini.

An open-source ONNX conversion pipeline for Stability AI's Stable Audio 3 Small — enabling CPU/GPU audio generation inference without a PyTorch runtime dependency.

• Engineering Highlights:
  • Exports the full diffusion pipeline into 4 standalone ONNX modules: Text Encoder → Conditioner → DiT (Diffusion Transformer) → Decoder (Oobleck).
  • Supports both stable-audio-3-small-music and stable-audio-3-small-sfx model variants.
  • Runtime-agnostic deployment on CUDA, DirectML, and CPU via ONNX Runtime — no PyTorch installation required at inference time.
• Key Stack: Python, ONNX Runtime, HuggingFace Diffusers, Stability AI, PyTorch.

A tightly integrated suite of offline voice engineering tools covering real-time TTS streaming, multi-engine workstations, and full voice-driven AI assistants.

• Engineering Highlights:
  • Pocket_TTS: Low-latency real-time TTS streaming via WebSockets (~200ms to first chunk), voice cloning support, CPU-only, glassmorphism web UI.
  • Aura-TTS: Unified offline speech workstation managing engine lifecycles (Kokoro-TTS, Pocket-TTS, Supertonic) via custom mutual exclusion locking under RAM/VRAM constraints.
  • OrpheusAssistant: Offline voice agent with WebRTC bi-directional streams (aiortc), Whisper Large STT, and LLaMA 3.2 3B — integrated with n8n for workflow tool execution.
• Key Stack: Python, FastAPI, WebRTC, WebSockets, PipeCat, PyTorch, n8n, Docker.

A specialized research-to-production pipeline repository detailing high-throughput fine-tuning, reasoning models, and edge optimizations.

• Engineering Highlights:
  • Fine-tuning pipelines utilizing Unsloth kernels for parameter-efficient optimizations (LoRA / QLoRA).
  • RLHF training using Group Relative Policy Optimization (GRPO) without a separate Critic model (pioneered by DeepSeek-R1), targeting Qwen3 8B.
  • Horizontal engineering recipes for Mixture-of-Experts (MoE) kernels and ModernBERT dense classification systems.
• Key Stack: Unsloth, PyTorch, LoRA, QLoRA, HuggingFace Transformers, TRL, JAX.

A note on timing: these are older projects — university work, internship builds and independent experiments — developed offline over several years and only pushed to GitHub in September 2026. The commit dates reflect when they were uploaded, not when they were written. Each repository's README states its own original timeline.

• 🎬 Offline-First Media Architect: Building complete AI video production stacks that run 100% on local hardware — ONNX inference, FFmpeg rendering, TTS streaming, and lip sync compositing.
• 🧠 AI Pipeline Engineer: Expert in LangGraph DAG orchestration, Kafka event streaming, Celery distributed workers, and multi-agent system design.
• 📦 Docker-first Deployer: Containerizing complex AI stacks with multi-stage builds and clean Docker Compose networking configs.