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HELLO, I'MADEER KHAN

AI researcher passionate about developing smart solutions for the built world — applying software engineering, machine learning, and AI to create innovative solutions.

[ SEE MY RESUME ]

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Publications

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Projects

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National Awards

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WHAT I DO.

AI & ML researcher working on generative AI, LLM-integrated digital twins, computer vision, and geospatial data science for the built environment

> Machine Learning & Deep Learning

-Training and evaluating deep learning models for vision, robustness, and generative tasks
-Designing neural network layers, including a network coding layer (NNCL) that recovers erased features under extreme erasure (IEEE Access, 2025)
-Applying ML to spatio-temporal and engineering data, e.g. ANN-CA urban growth modeling (EJRS, 2022)

PythonPyTorchTensorFlowscikit-learnJupyterNumPyPandas

> Generative AI & LLMs

-Generative AI for automated building design and AEC workflows across diffusion, autoregressive, and hybrid models
-LLM-integrated digital twin systems for management, adaptive control, and human-AI collaboration in architecture
-Building conversational agents with LangChain and OpenAI APIs

Hugging FaceLangChainOpenAIStreamlit

> Computer Vision & 3D

-Face recognition with deep embeddings (EE488B, KAIST)
-Point cloud rendering and architectural visualization in SketchUp and Enscape 3D
-Real-time digital twin communication with MQTT in Unity 3D

OpenCVUnityC#

> Geospatial & Spatial Data Science

-Land use / land cover classification and urban growth modeling with random forests and ANN-CA
-Satellite imagery analysis and future-scenario simulation with QGIS and MOLUSCE
-Parametric environmental simulation with Rhino, Grasshopper, and Ladybug Tools

QGISRGit

> Research & Engineering

-Peer-reviewed publication in Automation in Construction (Q1), IEEE Access, and EJRS
-Structural health monitoring and experimental validation
-Docker, Linux, and reproducible research workflows

LaTeXDockerLinuxGitHub

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PROFICIENCY.

Focused on machine learning, deep learning, generative AI, and spatial data science.

Machine Learning & Deep Learning90%

Generative AI & LLMs85%

Computer Vision & 3D80%

Geospatial & Spatial Data Science85%

Research & Engineering90%

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EDUCATION.

Korea Advanced Institute of Science & Technology (KAIST)

MSc in Civil & Environmental Engineering

Feb 2024 - Aug 2025

Research on automated building design and LLM-integrated digital twins.

-Generative AI approaches for automated architectural design (Automation in Construction, 2025).
-LLM-integrated digital twin management and adaptive control for buildings.

Capital University of Science and Technology (CUST)

BSc in Civil Engineering

Gold Medalist

2018 - 2022

Graduated as the overall best achiever of the university.

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EXPERIENCE.

NeoBIM GMBH

AI Research Engineer

Oct 2023 - Present

> Lead AI research and development for a BIM startup in Germany.

-Designing LLM-integrated digital twin systems and automated design workflows.
-Applying generative AI to architecture, engineering, and construction.

Korea Advanced Institute of Science & Technology (KAIST)

Graduate Researcher

Feb 2024 - Aug 2025

> Researched generative AI for automated building design and LLM-integrated digital twins.

-Led a systematic review of generative models for architectural design automation, published in Automation in Construction (Q1).
-Developed digital twin frameworks with LLM integration for adaptive building control.

Joyn Group Pvt. Ltd.

Data Scientist

Aug 2023 - Oct 2023

> Applied machine learning to business data and product workflows.

-Built data pipelines and ML models for business decision support.

Capital University of Science and Technology

Undergraduate Researcher (FYP)

2021 - 2022

> Final-year project on a simple, sustainable approach for structural health monitoring of structures.

-Experimental and numerical validation of damage detection using snapback and harmonic tests.
-Published in the Capital University of Science and Technology journal.

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PROJECTS.

[PROJ_001]

Digital Twin

A Unity3D-based digital twin system using MQTT for real-time bidirectional communication, visualization, and control between physical devices (Arduino/ESP32 sensors and actuators) and their virtual counterparts.

[PROJ_002]

Face Embeddings

A framework for training deep face-recognition embeddings - final project for Deep Learning for Computer Vision (EE488B) at KAIST, Fall 2024.

GITHUB

[PROJ_003]

Podcast Summarizer

OpenAI GPT-based podcast summarizer with a cloud-deployed backend and a Streamlit frontend. Paste any podcast RSS feed to get summaries and highlights.

LIVE DEMO

[PROJ_004]

Talk with Images

A Streamlit app that answers questions about uploaded images through a LangChain and OpenAI GPT conversational agent.

GITHUB

[PROJ_005]

Al-Bahar Tower Facades

Designed the mechanical facades of Al-Bahar Tower in Rhino with parametric programming in Grasshopper, integrating Ladybug Tools to simulate facades opening and closing in response to the sun's path.

LIVE DEMO

[PROJ_006]

Game Development in Unity3D

A Unity3D project from the Computer Graphics Theory and Application (GCT522) course exploring procedural generation and shader-based weather effects in a dynamic environment.