Mate Fazekas | Autonomous Vehicles | Best Researcher Award

Posted on by Academic achievements

Mr. Mate Fazekas | Autonomous Vehicles | Best Researcher Award

Ph.D. student at HUN-REN Institute for Computer Science and Control (SZTAKI), Hungary

MátĂ© Fazekas is a dedicated researcher and senior software developer based in Budapest, Hungary. Since 2017, he has contributed significantly as a research associate at the HUN-REN Institute for Computer Science and Control, focusing on state estimation and model identification for autonomous vehicles. From 2022 to 2024, he expanded his expertise as a senior software developer at HUMDA Lab Kft., specializing in developing control systems for autonomous racecars. Currently pursuing a PhD in Robotics at the Budapest University of Technology and Economics, MátĂ©’s research centers on model calibration for autonomous vehicles integrating machine learning techniques. He holds an MSc in Electrical Engineering and a BSc in Mechatronics Engineering from the same institution, both awarded with highest honors. Proficient in languages including Hungarian and English, he excels in programming languages like Matlab, Python, C/C++, and LabVIEW, complemented by strong skills in CAD software and Microsoft Office applications.

Professional Profiles

Education

MátĂ© Fazekas pursued his academic journey at the Budapest University of Technology and Economics, achieving academic excellence throughout. He completed his Bachelor of Science in Mechatronics Engineering from the Faculty of Mechanical Engineering, graduating summa cum laude in 2017. His undergraduate thesis focused on the development of an automated parking system. Subsequently, he earned his Master of Science in Electrical Engineering and Informatics from the Faculty of Electrical Engineering and Informatics, also graduating summa cum laude in 2019. His master’s thesis centered on state and parameter estimation for car-like robots. Currently, he is continuing his academic pursuits as a PhD student in Robotics at the Faculty of Vehicle Engineering, where his research involves model calibration for autonomous vehicles integrating machine learning techniques.

Professional Experience

Máté Fazekas has gained valuable experience in both research and software development roles. Since December 2017, he has served as a Research Associate at the HUN-REN Institute for Computer Science and Control in Budapest, focusing on state estimation and model identification for autonomous vehicles. Concurrently, from June 2022 to June 2024, he worked as a Senior Software Developer at HUMDA Lab Kft., specializing in the development of control systems for autonomous racecars. His expertise includes integrating GNSS, IMU, and odometry for vehicle localization, along with developing advanced software solutions for autonomous systems.

Research Interest

MátĂ© Fazekas, a Budapest-based researcher and Senior Software Developer at HUMDA Lab Kft., specializes in robotics and autonomous systems. Since 2017, he has contributed significantly as a research associate at the HUN-REN Institute for Computer Science and Control, focusing on state estimation and model identification for autonomous vehicles using GNSS, IMU, and odometry technologies. His current role involves developing control systems for autonomous racecars, enhancing their performance and automation capabilities. Educationally, MátĂ© is pursuing a PhD in Robotics at Budapest University of Technology and Economics, exploring model calibration for autonomous vehicles with machine learning integration. He holds a master’s degree in Electrical Engineering and Informatics, where his research focused on state and parameter estimation for robotic systems, and a bachelor’s degree in Mechatronics Engineering, emphasizing automated parking systems. His technical skills include proficiency in Matlab, Python, C/C++, and LabVIEW, as well as CAD and FEM tools like SolidWorks, Inventor, and Ansys.

Research skills

Mate Fazekas is proficient in multiple languages, with Hungarian as his mother tongue and English at an intermediate B2 level. His computer skills include intermediate proficiency in Microsoft Office tools such as Word, Excel, PowerPoint, Access, and Project. He also possesses intermediate skills in Computer-Aided Design (CAD) and Finite Element Method (FEM) software like SolidWorks, Inventor, and Ansys. In programming, Mate demonstrates intermediate proficiency in languages such as C/C++ and LabVIEW, along with advanced skills in MATLAB and intermediate proficiency in Python. These skills equip him well for his research and development roles, particularly in robotics and autonomous vehicle technologies.

Publications

  1. Wheel odometry model calibration with neural network-based weighting
    • Authors: Fazekas, M., Gáspár, P.
    • Journal/Conference: Engineering Applications of Artificial Intelligence, 2024
    • Citations: 0
  2. LPV-Based Control Design with Guarantees: a Case Study for Automated Steering of Road Vehicles
    • Authors: Nemeth, B., Fazekas, M., Bagoly, Z., Gaspar, P., Sename, O.
    • Conference: European Control Conference, ECC 2023, 2023
    • Citations: 0
  3. Calibration of the Nonlinear Wheel Odometry Model with an Improved Genetic Algorithm Architecture
    • Authors: Fazekas, M., NĂ©meth, B., Gáspár, P.
    • Conference: Proceedings of the International Conference on Informatics in Control, Automation and Robotics, 2022
    • Citations: 0
  4. Vehicle Control with Cloud-aided Learning Feature: an Implementation on Indoor Platform
    • Authors: NĂ©meth, B., Antal, Z., Marosi, A.C., Fazekas, M., Gáspár, P.
    • Journal: IFAC-PapersOnLine, 2022
    • Citations: 1
  5. Wheel Odometry Model Calibration with Input Compensation by Optimal Control
    • Authors: Fazekas, M., Gáspár, P., NĂ©meth, B.
    • Journal: IFAC-PapersOnLine, 2022
    • Citations: 0
  6. Calibration of Front Wheel Odometry Model
    • Authors: Fazekas, M., Gáspár, P., NĂ©meth, B.
    • Book: Lecture Notes in Mechanical Engineering, 2022
    • Citations: 0
  7. Implementation of a variable-geometry suspension-based steering control system
    • Authors: FĂ©nyes, D., Fazekas, M., NĂ©meth, B., Gáspár, P.
    • Journal: Vehicle System Dynamics, 2022
    • Citations: 6
  8. Parameter Identification of the Nonlinear Wheel Odometry Model with Batch Least Squares Method
    • Authors: Fazekas, M., Gáspár, P., NĂ©meth, B.
    • Conference: Conference on Control and Fault-Tolerant Systems, SysTol, 2021
    • Citations: 1
  9. Velocity estimation via wheel circumference identification
    • Authors: Fazekas, M., Gáspár, P., NĂ©meth, B.
    • Journal: Periodica Polytechnica Transportation Engineering, 2021
    • Citations: 1
  10. Improving the wheel odometry calibration of self-driving vehicles via detection of faulty segments
    • Authors: Fazekas, M., Gaspar, P., Nemeth, B.
    • Conference: IEEE International Conference on Automation Science and Engineering, 2021
    • Citations: 0

 

 

Abdellatif Sadeq | Mechanical | Best Researcher Award

Posted on by Academic achievements

Assist Prof Dr. Abdellatif Sadeq | Mechanical | Best Researcher Award

Ph.D., Qatar University, Qatar

🌍 Dr. Abdellatif Mohammad Sadeq, born on April 30, 1993, in Jordan, currently resides in Doha, Qatar. Fluent in both Arabic and English, Dr. Sadeq is a distinguished mechanical engineer with a robust academic background and a dedication to teaching and research. He has over eight years of teaching experience and currently serves as the Dean of Academic Affairs and a mechanical engineering lecturer at Qatar Naval Academy. Dr. Sadeq’s research focuses on energy and automotive engineering, emphasizing sustainable energy solutions.

Profile

Google Scholar

 

Education🎓

🎓 Dr. Abdellatif Mohammad Sadeq holds a B.Sc. (2015), M.Sc. (2018), and Ph.D. (2022) in Mechanical Engineering from Qatar University. Additionally, in September 2023, he earned a second M.Sc. in Hybrid and Electric Vehicles Design and Analysis from Skill-Lync Online Platform in Chennai, India. His academic journey is marked by numerous accolades, including certificates of excellence and distinction.

Experience🏫

đź’Ľ Dr. Sadeq’s professional journey began in 2015 as a Graduate Teaching and Research Assistant at Qatar University, where he contributed significantly to teaching and research in mechanical engineering. Since October 2023, he has been serving as the Dean of Academic Affairs and a lecturer at Qatar Naval Academy. His roles have encompassed curriculum development, faculty training, and strategic academic planning, ensuring high standards of education and research excellence.

Research Interestsđź“š

🔬 Dr. Sadeq’s research interests lie in energy and automotive engineering, with a particular focus on internal combustion engines, alternative fuels, hydrogen energy, renewable energy utilization, and energy storage techniques. He specializes in system modeling, simulation, and the design of hybrid and electric vehicles. Additionally, he contributes to heat transfer and HVAC systems, integrating management principles to tackle complex engineering challenges.

Awards🏆

🏅 Throughout his academic and professional career, Dr. Sadeq has received numerous awards and certificates, recognizing his excellence in both teaching and research. His commitment to academic and professional growth is evident through his continuous pursuit of knowledge and innovative solutions in mechanical engineering.

Publications

đź“š Dr. Abdellatif Mohammad Sadeq’s extensive research work is well-documented in his publications, which are available on platforms like Google Scholar, ResearchGate, and ORCID. Here are some notable publications:

“Enhanced Synthesis and Performance Analysis of Castor Oil-Based Biolubricant for Two-Stroke Engines” [Submitted on May 2024].

“Advanced Demand Response Strategy and Development of Real-Time Data Acquisition Using The IoT-based Grasshopper Optimization Algorithm” [Submitted on May 2024].

“Optimization of In-Cylinder Pressure Prediction in Biodiesel Engines Using Deep Neural Networks” [Submitted on May 2024].

“Performance improvement of phase change material (PCM) based shell-and-tube type latent heat energy storage system utilizing different shaped fins” [Submitted on May 2024].

“Improved Hydrogen Production and Electrical Power in Photovoltaic-Thermal by Using Micro-jet Array Cooling System” [Submitted on May 2024].