Abdelrhman BASSIOUNY | Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Abdelrhman BASSIOUNY | Computer Science and Artificial Intelligence | Best Researcher Award

University of Bremen Germany

Abdelrhman Bassiouny is a passionate Egyptian robotics researcher specializing in marine robotics, autonomous systems, and AI-powered disassembly. With international experience across Germany, France, and Egypt, he combines technical mastery in robotics with a strong academic background. He thrives in hands-on innovation, contributing to cutting-edge projects from underwater VSLAM to robotic e-waste disassembly. 🌊🤖

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Research Gate

Scopus

🎓 Education

Abdelrhman is currently completing his Erasmus Mundus Joint Master’s Degree in Marine & Maritime Intelligent Robotics (MIR), where he studied at Université de Toulon (France) and Universidad Jaume I (Spain). He graduated with honors in Mechatronics & Automation Engineering from Ain Shams University, Egypt. He also expanded his knowledge through specialized online courses in Deep Learning, Self-Driving Cars, and Project Management. 📘🌍
🔗 Master MIR Program
🔗 Ain Shams University

🛠️ Experience

Abdelrhman brings versatile research and teaching experience:

  • Master Thesis Intern at University of Bremen (Germany): Developed a query interface and machine learning pipeline for NEEMs robotics database.

  • Underwater VSLAM Intern at Laboratoire COSMER (France): Benchmarked SLAM algorithms using BlueROV in collaboration with IFREMER.

  • Research Assistant at Ain Shams University (Egypt): Led autonomous robotic disassembly projects, winning 3rd place in Robothon 2021.

  • Teaching Assistant at Ain Shams University: Taught ROS-based robotic control and supervised final-year projects.
    🌐 LinkedIn | 🌍 Personal Website

🔬 Research Interests

Abdelrhman’s research centers on:

  • Autonomous Robotics & Human-Robot Interaction 🤝

  • Symbolic Reasoning & Knowledge Representation 🧠

  • Underwater SLAM and Marine Robotics 🌊

  • E-waste Disassembly Automation using AI ♻️

  • ROS, TensorFlow, and Vision-based Robotics 📷

🏆 Awards

  • 🥇 Best Scientific Methodology AwardRoboCup MSL 2022 (Thailand)
    RoboCup 2022 History

  • 🥈 Runner-UpMIR Championship – Guerledus Challenge 2022
    Challenge Info

  • 🥉 3rd Place + Lightning Speed AwardRobothon Grand Challenge 2021 (TUM, Germany)
    Robothon Video

📚 Publications Top Notes: 

Prompt: Publications with hyperlinks, published year, journal (if applicable), and citation details in paragraph form.

Abdelrhman has authored two impactful research publications related to robotic disassembly of electronic waste:

“Comparison of Different Computer Vision Approaches for E-waste Components Detection to Automate E-waste Disassembly” (2021) – This paper evaluates vision-based algorithms for component detection, supporting more efficient and sustainable e-waste recycling.
🔗 View Publication
📈 Cited by: Google Scholar results

“Autonomous Non-Destructive Assembly/Disassembly of Electronic Components using A Robotic Arm” (2021) – Introduced a robotic system for semi-destructive disassembly using ROS and vision systems.
🔗 View Publication
📈 Cited by: Google Scholar results

Ali Raza | Computer Science and Artificial Intelligence | Young Scientist Award

Mr. Ali Raza | Computer Science and Artificial Intelligence | Young Scientist Award

lecturer The University Of Lahore Pakistan

Ali Raza is a passionate researcher, educator, and developer specializing in computer science. With a strong academic background and extensive experience in machine learning, deep learning, and computer vision, he has contributed significantly to cutting-edge research. Currently serving as a Lecturer at the University of Lahore, Ali has also worked as a Visiting Lecturer at KFUEIT and a Full Stack Python Developer in the software industry. His expertise lies in AI-driven solutions, research writing, and technological advancements in artificial intelligence.

Profile

Google Scholar

Education 🎓

  • MS Computer Science (2021-2023) | Khwaja Fareed University of Engineering and Information Technology (KFUEIT), CGPA: 3.93
  • BS Computer Science (2017-2021) | KFUEIT, CGPA: 3.47

Professional Experience 💼

  • Lecturer | University of Lahore (2024 – Present)
  • Visiting Lecturer | KFUEIT (2022 – 2023)
  • Full Stack Python Developer | BuiltinSoft Software Industry (2020 – 2021)

Research Interests 📈

Ali Raza’s research focuses on artificial intelligence, machine learning, deep learning, and computer vision. He is particularly interested in developing AI-driven solutions for medical imaging, agricultural applications, and energy consumption prediction. His contributions span multiple domains, showcasing his ability to integrate AI with real-world challenges.

Awards & Certifications 🏆

  • Best Researcher Award | ScienceFather (26/06/2024)
  • Use of Generative AI in Higher Education | Punjab Higher Education Commission
  • Machine Learning with Python (ML0101EN) | IBM Developer Skills Network

Publications Top Notes: 📚

Ali Raza has authored 61 research publications in reputed journals with high impact factors. Below are some of his recent publications:

“Novel Transfer Learning Approach for Hand Drawn Mathematical Geometric Shapes Classification” (2025) PeerJ Computer Science (IF: 3.8)

“Citrus Diseases Detection Using Innovative Deep Learning Approach and Hybrid Meta-Heuristic” (2025) PLOS ONE (IF: 2.9)

“Novel Deep Neural Network Architecture Fusion for Energy Consumption Prediction” (2025) PLOS ONE (IF: 2.9)

“Novel Transfer Learning Based Bone Fracture Detection Using Radiographic Images” (2025) BMC Medical Imaging (IF: 2.9)

“Novel Transfer Learning Approach for Detecting Infected and Healthy Maize Crops” (2025) Food Science & Nutrition (IF: 3.5)

“BdSentiLLM: A Novel LLM Approach to Sentiment Analysis of Product Reviews” (2024) IEEE Access (IF: 3.4)

“An Innovative Artificial Neural Network Model for Smart Crop Prediction” (2024) PeerJ Computer Science (IF: 3.8)

“Enhanced Interpretable Thyroid Disease Diagnosis Using Synthetic Oversampling and Machine Learning” (2024) BMC Medical Informatics (IF: 3.3)

“Diagnosing Epileptic Seizures Using EEG Data and Independent Components” (2024) Digital Health (IF: 3.7)

“A Novel Meta Learning Based Approach for Thyroid Syndrome Diagnosis” (2024) PLOS ONE (IF: 2.9)