ABD AI LAB

Intelligent Systems

The umbrella direction connecting AI, robotics, BCI and automation into unified intelligent systems.

Artificial Intelligence

Algorithms and models that let systems perceive, learn and make decisions.

Machine Learning

Learning patterns from data rather than explicit rules — the foundation for the deep learning, reinforcement learning and BCI classification work in this lab.

Deep Learning

Layered neural network architectures for perception and pattern recognition.

Reinforcement Learning

Learning a policy through interaction and feedback rather than labeled examples.

Computer Vision

Extracting information from images — object detection and classification feeding robotic perception.

Robotics

Programming and controlling physical machines — industrial arms, collaborative robots and mobile platforms.

ROS 2

The middleware framework used to build and coordinate robotic software components.

Robot Control

Low-level command and coordination of robotic actuators and joints.

Motion Planning

Computing collision-free, feasible paths for a robot to follow.

Navigation

Localizing a mobile robot and planning its route through an environment.

Brain-Computer Interface

Systems that decode brain activity into signals a machine can act on.

EEG

Electroencephalography — recording electrical brain activity through the scalp.

Signal Processing

Cleaning and transforming raw sensor signals into a usable form.

Feature Extraction

Reducing a signal to the specific measurements a classifier needs.

Classification

Assigning a label to a signal or sample based on its extracted features.

Human-Machine Interaction

The interface layer between a human's intent and a machine's response.

Hybrid-Adaptive BCI

The M.Sc. thesis research: a hybrid adaptive BCI that decodes real-time EEG with deep learning to help control industrial and medical robotic devices.

Data Engineering

Building the pipelines that move and shape data for AI and robotics systems.

SQL

Structured query language for working with relational data.

Python

The primary language across this lab's AI, data and automation work.

Automation

Connecting industrial control systems and AI-driven workflows into coordinated processes.

AI Agents

Software agents that use LLMs and tools to carry out multi-step tasks.

Workflow Orchestration

Sequencing and connecting automated steps into a reliable workflow.

Software Architecture

The structural decisions behind how a system's components fit together.

TypeScript

A typed superset of JavaScript used for the software built in this lab.

Next.js

The React framework this website (and the AI Lab itself) is built on.

Hybrid Adaptive BCI

M.Sc. thesis engineering a hybrid adaptive Brain-Computer Interface that decodes real-time EEG with deep learning to control industrial robotic manipulators and medical assistive devices.

AI Job Agent

An engineering system that combines AI agents, LLM analysis and workflow automation to collect, process and act on job data end-to-end.

ROS2 Robotics Systems

Robot control and simulation work built on ROS2, exploring intelligent behaviors and human-robot interaction.

Intelligent Data Pipeline

A data engineering system for ingesting, processing and serving structured data through reliable, intelligent pipelines.

Jet Engine Design and Performance Simulation

B.Sc. graduation project designing a complete jet engine assembly — compressor, combustion chamber, turbine and exhaust — using thermodynamic cycle analysis and fluid mechanics, modelled in CAD and validated with ANSYS and MATLAB simulations.