Hi, I'm Babitdor Kayang Khonglah
AI/ML Engineer specializing in LLM orchestration, RAG architectures, and building intelligent systems that scale.
About Me
Passionate about building intelligent systems and pushing the boundaries of AI
I'm an AI/ML Engineer specializing in LLM orchestration and RAG architectures. Currently pursuing my Master's in Artificial Intelligence at FAU Erlangen-Nürnberg, I build intelligent systems that leverage cutting-edge AI technologies.
My expertise spans multi-agent workflows, vector databases, and deploying AI solutions at scale. I'm passionate about building tools that enhance developer productivity and automate complex workflows.
Education
M.Sc. Artificial Intelligence
Friedrich-Alexander-Universität Erlangen–Nürnberg
03/2024 – Present
B.Tech. Computer Science & Engineering
National Institute of Technology, Meghalaya
04/2018 – 04/2022
Technical Skills
Technologies and tools I use to build amazing things
Python
Language
JavaScript
Language
TypeScript
Language
C++
Language
LangGraph
AI/ML
LangChain
AI/ML
CrewAI
AI/ML
RAG
AI/ML
LLM
AI/ML
Docker
DevOps
PostgreSQL
Database
MongoDB
Database
Vector DB
Database
Git
DevOps
React
Frontend
Node.js
Backend
Projects
A selection of my recent work and experiments
Multi-Agent Research Intelligence System
Advanced AI-powered multi-agent research system orchestrating specialized AI agents to conduct comprehensive research, synthesize information, and generate professional reports. Features 10 research strategies, parallel swarm research, self-critique quality control, RAG knowledge management, and dual-format report generation (Markdown + PDF).
SysML v2 Multi-Agent Workflow Automation
Sophisticated AI-powered system for generating and validating SysML v2 code using multi-agent architecture with RAG and vector database integration. Features intelligent code generation with context awareness, automated multi-step validation with syntax and semantic checks, automatic error detection and fixing, knowledge management with RAG system, solution memory using ChromaDB vector database, optional human approval with feedback integration, and real-time analytics dashboard.
Nami-Code: Deep Agent Framework & AI Coding Assistant
Open-source AI agent framework and terminal-based coding assistant enabling LLMs to handle complex multi-step tasks through advanced planning, context management, and parallel execution. Features planning tools, filesystem operations, subagent spawning, persistent memory, and MCP support for extensible tool integration.
S.A.R.A.H. – Smart Assistant Real At Heart
A fully local desktop voice assistant powered by a fine-tuned LLaMA 3.2 model. Uses a real-time STT → LLM → TTS pipeline with LiveKit for voice streaming, Deepgram for speech-to-text, and Cartesia AI for natural voice responses. Can understand natural language commands and invoke tools like launching apps, reading emails, or organizing files — all while running 100% offline for complete privacy.
Speaker Voice Separation with Dual-Path Transformers
Enhancing the Dual-Path RNN framework by replacing the original recurrent modules with intra-chunk and inter-chunk Transformer layers. This hybrid architecture aims to better capture both local and global audio dependencies for superior multi-speaker separation. Intra-chunk Transformer applies self-attention within small audio chunks to model fine-grained, short-term temporal features, while Inter-chunk Transformer captures long-range context by attending across chunk sequences.
Assistive Sidewalk Segmentation: Fine-Tuning SAM 2.1 with a Custom Dataset for the Visually Impaired
Developed a comprehensive training and deployment pipeline for fine-tuning Segment Anything Model (SAM) 2.1 by Meta on custom sidewalk imagery, aimed at enabling assistive vision systems for the visually impaired. The project spans data preprocessing, dynamic prompt generation, mixed-precision training, checkpointing, and model evaluation, culminating in an interactive Streamlit application for real-time segmentation and inference.
ogAI: Multi-Model LLM Discord Assistant
Built a fully customizable AI-powered Discord bot that integrates multiple local and cloud-based language models (e.g., Ollama, Gemini, GPT-4) to deliver intelligent, context-aware responses across diverse use cases including general Q&A, summarization, and creative tasks. Features integrated multiple backends, flexible routing logic to dynamically select models based on task or user input, prompt templates, system messages, and conversation context tracking.
N8N-Framework: AI-Powered SysMLv2 Systems Engineering Platform
Advanced AI-powered systems engineering platform integrating SysMLv2 with multi-agent LLMs to assist in designing, modeling, analyzing, and optimizing complex systems. Built on n8n workflow automation, features AI-driven code generation, multi-agent analysis (KPI-Analyst, SysML-Expert, MA-Solver), rigorous ANTLR4-based validation, Eclipse SysON integration for visual modeling, and comprehensive knowledge management with RAG capabilities.
Get In Touch
I'm always open to discussing new opportunities, research collaborations, or interesting AI/ML projects.