Artificial Intelligence · Robotics · Intelligent Systems
ABD ELSALAM
AI & Robotics Engineer
I build intelligent systems that
PERCEIVE · LEARN · DECIDE · ACT.
Connecting Artificial Intelligence, Robotics, and Data to build intelligent machines and autonomous systems that move intelligence into the physical world.
- AI / ML — Intelligence: Deep Learning, Computer Vision, NLP / LLMs, Reinforcement Learning
- ROBOTICS — Action: ROS2, Control & Kinematics, Simulation (Gazebo), Perception & Navigation
- DATA — Insight: Data Engineering, ETL / ELT, Cloud & Databricks, Analytics & Insights
- SENSORS — Perception: Perception, Sensor Fusion, Computer Vision, Real-time Systems
- HUMAN–MACHINE INTERACTION — Brain-computer interfaces: Brain-Computer Interfaces, EEG Signal Processing, Adaptive AI, Assistive Systems
- AUTOMATION — Efficiency & Impact: Autonomous Systems, AI Agents, Real-world Deployment, Efficiency & Impact
8+ Years
Robotics & Automation
Engineering Experience
B.Sc.
Mechanical Power Engineering
Zagazig University
M.Sc.
Robotics & Automation
JAMK University of Applied Sciences
AI + Robotics
Research & Engineering
Intelligent Systems
01 — Capabilities
What I Work Across
Five areas that connect research, engineering and 8+ years of industrial practice.
02 — System Pipeline
From Data to Intelligent Action
A systems view of how data, intelligence, robotics and automation connect.
I work across the boundary between software intelligence and physical systems — connecting data, machine learning, robotics, control and intelligent automation to build real-world intelligent systems.
Sensors
EEG, industrial and robotic sensing
Data
Acquisition, pipelines, processing
AI / ML
Models, inference, decoding
Decision
Planning, adaptive control logic
Robotics
Motion, manipulation, control
Automation
Workflows, agents, orchestration
Intelligent Systems
Real-world, deployed outcomes
03 — Research Focus
Research
Exploring intelligent systems that connect humans, machines, data and artificial intelligence.
Artificial Intelligence and Machine Learning
Deep learning, neural networks, CNN, LSTM, Transformers, reinforcement learning and computer vision, applied to robotics and signal decoding.
Brain-Computer Interfaces
EEG acquisition and decoding, signal processing and adaptive, learning-driven BCI systems for robotic and assistive control.
Intelligent Robotics
AI-driven industrial and collaborative robots, with perception-driven, adaptive behaviour in unstructured environments.
Autonomous Systems
Motion planning, navigation, SLAM and robot perception underpinning autonomous mobile robots and industrial robotic arms.
Human-Robot Interaction
Interfaces between humans, AI systems and robots — including shared control and safety-aware collaboration.
04 — Featured Research
Hybrid-Adaptive Brain-Computer Interface
Hybrid Adaptive Brain-Computer Interface Using Artificial Intelligence for Controlling Industrial Robots and Medical Assistive Devices
M.Sc. thesis (JAMK University of Applied Sciences) engineering a hybrid adaptive Brain-Computer Interface that decodes real-time EEG with deep learning to control industrial robotic manipulators and medical assistive devices.
05 — Engineering Projects
Selected Projects
Systems spanning AI, robotics, automation and data engineering.
Hybrid Adaptive BCI
Problem
Manual control is impractical for users with severe motor impairment, and in industrial settings where hands-free operation is needed.
Build
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.
Technology
AI Job Agent
Problem
Manually searching, filtering and evaluating job postings across multiple sources doesn't scale.
Build
An engineering system that combines AI agents, LLM analysis and workflow automation to collect, process and act on job data end-to-end.
Technology
ROS2 Robotics Systems
Problem
Bridging AI-driven decision-making with real robot behavior requires a dependable control and simulation layer.
Build
Robot control and simulation work built on ROS2, exploring intelligent behaviors and human-robot interaction.
Technology
Intelligent Data Pipeline
Problem
Intelligent systems are only as reliable as the data feeding them — inconsistent pipelines undermine everything built on top.
Build
A data engineering system for ingesting, processing and serving structured data through reliable, intelligent pipelines.
Technology
06 — Publications
Publications
A clean academic record — updated as research is completed and released.
Thesis
Hybrid Adaptive Brain-Computer Interface Using Artificial Intelligence for Controlling Industrial Robots and Medical Assistive Devices
2026Abdelsalam Ali Abdelsalam Mohamed
M.Sc. Thesis, JAMK University of Applied Sciences, Jyväskylä, Finland
Engineers a hybrid adaptive Brain-Computer Interface enabling hands-free, non-invasive EEG control of industrial robotic manipulators and medical assistive devices, combining deep learning (CNN/LSTM) motor-imagery decoding with an online-adaptive layer and a ROS 2 / Gazebo robot control stack, verified through simulation-first testing with a shared-control safety layer.
07 — Latest Activity
Events and Professional Activity
Recent conferences, workshops and professional engagements.
DevOps Finland September meetup
DevOps Finland
Attended the DevOps Finland September meetup at Netlight, exploring agentic AI, cloud operations, software development, and the evolving role of AI agents.
Microsoft Data Platform User Group: In-person September meetup @ Innofactor
Microsoft Data Platform User Group – Finland
Attended the Microsoft Data Platform User Group meetup at Innofactor, exploring Microsoft Fabric, data engineering, analytics, AI, and practical approaches to modern data platform workflows.
Let's build intelligent systems.
Open to research collaboration, robotics and automation roles, AI and robotics projects, and technical consulting.
Helsinki, Finland
- Research collaboration
- Robotics and automation roles
- AI / Robotics projects
- Technical collaboration