Thunyawat Limpiti | Engineering | Best Research Article Award

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Thunyawat Limpiti | Engineering | Best Research Article Award

Assist. Prof. Dr Thunyawat Limpiti, School of Engineering and Technology, Walailak University, Thailand

Asst. Prof. Dr. Thunyawat Limpiti is a dedicated Thai academic and researcher currently serving as a Lecturer at the School of Engineering and Technology, Walailak University. With a strong foundation in electrical and telecommunication engineering, he holds a Doctor of Engineering degree from King Mongkut’s Institute of Technology Ladkrabang. Dr. Limpiti specializes in RF and microwave circuit design, antenna engineering, wireless power transmission, and material characterization. Throughout his career, he has combined theoretical depth with practical innovation to address complex challenges in healthcare, agriculture, and communications. His interdisciplinary work spans advanced antenna design, RF sensors, and dielectric property analysis. Dr. Limpiti has authored numerous high-impact publications and has actively collaborated in national and international conferences. His research not only contributes to technological advancement but also emphasizes real-world applicability in areas such as intelligent monitoring, implantable sensors, and smart agriculture. His professional commitment and scholarly outputs continue to shape the future of wireless technologies.

Publication Profile

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Education

Dr. Thunyawat Limpiti pursued all his higher education degrees at the prestigious King Mongkut’s Institute of Technology Ladkrabang, Thailand. He earned his Bachelor of Engineering in Telecommunication Engineering in 2005, establishing a solid grounding in communication technologies. Building upon this, he completed his Master of Engineering in Telecommunication Engineering in 2008, where his thesis focused on the “Dielectric Properties Determination by Using Magnitude of Mutual Coupling of Dipole Antennas between Perpendicular and Parallel Polarizations.” In 2013, he achieved his Doctor of Engineering in Electrical Engineering with a dissertation titled “Switchable Antennas and Their Application in Dielectric Properties Determination.” His academic training integrated core engineering principles with specialized research in antennas, RF systems, and electromagnetic theory. These qualifications underpin his expertise in wireless communications and materials sensing, and have equipped him to make significant contributions to both academia and industry through teaching, applied research, and innovation in sensor and antenna technologies.

Experience

Asst. Prof. Dr. Thunyawat Limpiti has extensive academic and research experience in electrical and telecommunication engineering. Currently serving as a Lecturer at the School of Engineering and Technology, Walailak University, he has led and participated in various research initiatives focusing on RF/microwave design, wireless systems, and smart sensors. Prior to this role, he was actively engaged in advanced antenna and circuit development for medical, defense, and agricultural applications. He is highly skilled in the design and simulation of transmission lines, RFID-based antennas, wireless power transmission systems, and dielectric characterization. Dr. Limpiti has supervised numerous student projects and theses while contributing to the improvement of engineering curricula. He has collaborated with multidisciplinary teams and international researchers, published in reputable journals, and presented at global conferences. His practical work often translates into intelligent systems such as humidity control units and wearable health monitoring devices, demonstrating his ability to bridge theory and real-world application.

Awards and Honors

While specific awards and honors are not explicitly listed in the data provided, Asst. Prof. Dr. Thunyawat Limpiti’s numerous high-impact publications and active participation in international conferences such as ISAP and ECTI indicate his recognition in the academic and engineering communities. His contributions to peer-reviewed journals including IEEE Access, Progress in Electromagnetics Research, and International Journal of Electrical and Computer Engineering reflect scholarly excellence. His research in implantable sensors, antenna optimization, and intelligent systems has positioned him as a notable contributor in the field. Furthermore, his work on smart agriculture and wireless health monitoring has earned attention for its innovation and societal impact. Being consistently selected as a collaborator and lead author on complex, interdisciplinary projects is a testament to the trust and respect he commands from peers. Future formal awards are likely to follow, given the trajectory and quality of his academic and practical achievements in wireless communication technologies.

Research Focus

Dr. Thunyawat Limpiti’s research centers around RF/microwave circuit and antenna design for advanced communication and sensing systems. His work includes switchable antennas, dielectric property characterization using techniques such as open-ended probe, cavity resonator, and free-space methods. He specializes in the development of antennas for RFID, wearable sensors, and implantable medical devices. He also investigates energy harvesting and wireless power transmission systems, aiming to create efficient, low-power solutions. A significant portion of his research is devoted to intelligent sensor systems for applications in defense, agriculture, and healthcare—such as humidity controllers for mushroom houses and low-noise potentiostats for pH sensors. Dr. Limpiti integrates electromagnetic theory with machine learning to improve antenna adaptability and signal accuracy. His multidisciplinary approach enables real-world problem-solving through the fusion of materials science, wireless engineering, and data-driven control systems, advancing smart technology development for environmental monitoring and medical diagnostics.

Publication Top Notes

  1. 📡 A High Linearity and Low-noise Potentiostat with Current Mirror, Chopper Stabilization and Relaxation Circuit Techniques for Implantable Sensor Applications (2025)

  2. 🧠 Low-Noise and High Linearity Potentiostat for Implantable Rumen pH Sensor Using Current Mirror Combined with Chopper Technique (2024)

  3. 🍬 Intelligent Sensor System with Transmission Coefficient in X-band Frequency for Determining Sugar Content (2023)

  4. 🌊 A Novel Catchment Estimation for Super-resolution DEM with Physically based Algorithms: Surface Water Path Delineation and Specific Catchment Area Calculation (2023)

  5. 🍄 An Intelligent Humidity Control System for Mushroom Growing House by Using Beam-switching Antennas with Artificial Neural Networks (2023)

  6. 🛰️ A Novel Algorithm to Delineate Surface Water Paths on Digital Elevation Model Image with Boundary Element Method (2022)

  7. 📶 Bandwidth Enhancement of Dual-band Bi-directional Microstrip Antenna Using CSRR with Defected Structure for 3/5 GHz Applications (2022)

  8. ❤️ Intelligent Medical System with Low-Cost Wearable Monitoring Devices to Measure Basic Vital Signals of Admitted Patients (2021)

  9. 🔥 ระบบตรวจวัดและควบคุมอุณหภูมิภายในตู้ฆ่าเชื้อก้อนวัสดุเพาะเห็ดอัตโนมัติด้วยการสื่อสารบลูทูธ (2564)

  10. 📡 Measurement of Radiated Field from Transmitting Antennas Located in Various Environments (2019)

  11. 🌿 การพัฒนาสายอากาศโมโนโพลย่านความถี่ C ร่วมกับการเรียนรู้ของโครงข่ายประสาทเทียมเพื่อประยุกต์ใช้ในการตรวจสอบน้ำยางปนเปื้อน (2562)

  12. 📶 A High-Gain Double Reflectors Microstrip-Fed Slot Antenna for WLAN and WiMAX Applications (2017)

  13. 📻 Design of a Magneto-Electric Dipole Antenna for FM Radio Broadcasting Base Station Antenna Implementation (2017)

  14. 📡 Design of a Log-Periodic Dipole Antenna (LPDA) for 0.8-2.5 GHz Band Applications (2017)

Muhammad Shahab | Engineering | Best Research Article Award

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Muhammad Shahab | Engineering | Best Research Article Award

Mr Muhammad Shahab, King Fahd University of Petroleum and Minerals, KFUPM, Saudi Arabia

Muhammad Shahab is a motivated robotics and control systems researcher currently pursuing his MSc in System and Control Engineering at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. With a background in Mechatronics Engineering from the University of Engineering and Technology, Peshawar, he has consistently demonstrated a passion for innovation in autonomous systems, fault-tolerant control, and cyber-physical systems. He has contributed to multiple high-impact research projects and publications, particularly in mobile robotics and intelligent control algorithms. His academic journey is marked by scholarships, competitive projects, and technical achievements that reflect his commitment to advancing technology in robotics and automation. With strong programming and problem-solving skills, Muhammad is well-equipped to handle complex engineering challenges. He actively contributes to the academic community through teaching assistantships, publications, and collaborative research. His future vision revolves around developing resilient, adaptive autonomous systems with real-world applications in smart industries and transportation.

Publication Profile

scopus

Education

Muhammad Shahab is currently enrolled in the Master of Science (MSc) program in System and Control Engineering at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, under a fully funded scholarship. His graduate coursework includes advanced subjects such as Linear Multivariable Control, Nonlinear Control, System Identification, Advanced Robotics, and Machine Learning, with a CGPA of 3.607. Earlier, he earned his Bachelor of Science (BSc) in Mechatronics Engineering from the University of Engineering and Technology Peshawar, Pakistan, in 2021 with a CGPA of 3.4. His undergraduate training focused on Mechatronic System Design, Robotics, Control Systems, and Embedded Systems. He was also awarded the Prime Minister’s Laptop for academic excellence. His educational background blends mechanical design, electronics, and intelligent control, forming a strong foundation for robotics and automation research. He has also participated in numerous technical projects, showcasing his practical grasp of engineering systems and real-time implementation.

Experience

Muhammad Shahab has a rich blend of academic and industrial experience. Currently, he is a Teaching Assistant at KFUPM for the course “Path Planning and Navigation for Mobile Robots,” where he supports students with algorithms, assignments, and conceptual understanding. As a Research Assistant at KFUPM, he is working on a review paper related to prognostics and diagnosis of machine tools in Industry 5.0. Previously, he completed internships at three different engineering firms in Pakistan: Mir Engineering Pvt. Ltd., where he worked on solar water systems; Shama Ghee Pvt. Ltd., focusing on boiler house operations and motor maintenance; and Pakistan Locomotive Factory, gaining insights into CNC machining and locomotive systems. Additionally, his undergraduate projects, including a 3D wire bending machine and autonomous vehicle control, reflect a practical grasp of real-world systems. His roles consistently demonstrate a focus on automation, robotics, control, and diagnostics, contributing to both learning and innovation.

Awards and Honors

Muhammad Shahab has received notable academic recognitions throughout his educational journey. At KFUPM, he is a recipient of a fully funded scholarship for his MSc studies in System and Control Engineering, a testament to his academic excellence and research potential. During his undergraduate studies at UET Peshawar, he was awarded the Prime Minister’s Laptop as part of a government merit-based initiative for high-achieving students. Additionally, his Final Year Project, an Automatic 3D Wire Bending Machine, was funded by the National Grassroots ICT Research Initiative (NGIRI) — a prestigious acknowledgment aimed at supporting impactful student innovations in Pakistan. These awards not only underscore his technical competence but also his ability to apply engineering knowledge to real-world problems. His continuous involvement in funded projects and competitive academic environments highlights his dedication to advancing his expertise in robotics, intelligent control systems, and industrial automation.

Research Focus

Muhammad Shahab’s research interests revolve around the intersection of robotics, control theory, and intelligent fault-tolerant systems. His work emphasizes robust and adaptive control for autonomous systems, including mobile robots and self-driving vehicles. He is particularly focused on cyber-physical systems where real-time responsiveness and reliability are critical. His research includes data-driven techniques like Q-learning and machine learning for predictive diagnostics and fault-tolerance, ensuring resilient operation in uncertain environments. His recent contributions explore formation control of wheeled mobile robots, trajectory tracking in autonomous lane changes, and sensor fusion under varying environmental conditions. He also delves into predictive maintenance strategies within the scope of Industry 5.0, contributing to the evolution of smart industrial systems. Through both simulation and hardware-based projects, Muhammad aims to bridge theoretical advancements with practical applications, building systems that are not only autonomous but also intelligent, self-correcting, and suitable for deployment in safety-critical domains like transportation and manufacturing.

Publication Top Notes

📄Particle Swarm Optimization tuned PID Control of Hybrid Renewable Energy-based Multi-area Power System – IEEE CyberScience Congress, 2023
📄 Trajectory Tracking Control for Lane Change Maneuvers in Autonomous Vehicles – ICARCV 2024 (Accepted)
📄 A Data-Driven Fault-Tolerant Approach for Mobile Robots Using Q-Learning and Regression – IEEE Conference (Under Preparation)
📄 Formation Control of Wheeled Mobile Robots with Fault Tolerant Capabilities – Robotics MDPI (Accepted, March 2025)
📄 State of the Art and Future Trends in Predictive Maintenance in the Context of Industry 5.0 – International Journal of Production Research (Under Review)
📄 A Comprehensive Survey on Formation Control of Mobile Robots: From Classical to Intelligent Fault-Tolerant Strategies – Annual Review of Control (Under Preparation)
📄 Impact of Environmental Conditions on Sensor Fusion, Motion Planning, and Control of Autonomous Vehicles – International Journal of Intelligent Transportation Systems Research (Under Review)

 

Hamna Baig | Engineering | Young Researcher Award

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Hamna Baig | Engineering | Young Researcher Award

Ms. Hamna Baig, COMSATS University Islamabad, Attock Campus, Pakistan

Hamna Baig is a passionate and accomplished Electrical Engineering graduate from COMSATS University Islamabad, Attock Campus. A Gold Medalist with a stellar CGPA of 3.66/4, she blends academic brilliance with innovation and creativity. Her work spans artificial intelligence, robotics, and smart systems—areas where she has made significant strides through hands-on projects, impactful research, and active involvement in technical writing. Hamna’s proactive participation in conferences, internships, and AI-based research projects has not only sharpened her technical expertise but also highlighted her commitment to using technology for social and environmental betterment. Adept in Python, MATLAB, LabVIEW, and embedded systems, she continues to evolve in her pursuit of excellence. Fluent in English, Urdu, and Punjabi, Hamna is driven by her curiosity, resilience, and desire to solve real-world problems through sustainable technology and intelligent systems. She is currently engaged in research and technical writing, aiming to make a lasting impact in the field.

Publication Profile

Google Scholar

Education

Hamna Baig completed her Bachelor of Science in Electrical Engineering from COMSATS University Islamabad, Attock Campus (2020–2024), graduating with distinction and securing a Gold Medal. Her final CGPA of 3.66/4 (91.5%) reflects her unwavering dedication and academic rigor. During her studies, she actively explored artificial intelligence, robotics, and embedded systems, with her thesis titled: “Enhancing Home Comfort with an Artificial Intelligence-based Environmental Control Model”. Hamna supplemented her academic journey with multiple certified online courses, including Machine Learning Specialization and Generative AI for Everyone offered by Stanford University via Coursera. Her technical training spans MATLAB, LabVIEW, Arduino, KEIL, Proteus, and microcontroller-based systems, showcasing both breadth and depth. Driven by curiosity and innovation, Hamna transformed theoretical knowledge into practical, real-world solutions through capstone projects and internships. Her continuous pursuit of learning makes her a standout in the evolving field of intelligent systems and energy-efficient technologies.

Experience

Hamna Baig has gained diverse experience through internships, research positions, and technical writing roles. She is currently an Internee at the Department of Electrical and Computer Engineering, COMSATS University Islamabad under the PEC GIT program, where she supports research on intelligent systems. Previously, she interned at the Ghazi-Barotha Hydro Power Plant (WAPDA) in 2023, gaining field exposure to power systems and operational technologies. Additionally, she works as a Technical Writer (Electrical & Electronics) with CDR Professionals, where she contributes research-based content and technical documentation. Hamna’s practical expertise includes projects in AI-driven sensing systems, robotic control, and smart energy applications. Her collaborative work on software-defined RF sensing and machine learning models demonstrates her ability to blend theoretical knowledge with real-time implementation. From smart home innovations to robotic arms and biomedical sensing, Hamna has exhibited both vision and versatility, positioning herself as a promising young engineer in AI, robotics, and embedded control.

Awards and Honors

Hamna Baig has been recognized for her academic excellence, research presentations, and contributions to intelligent systems. She earned a Gold Medal for outstanding academic performance during her Bachelor’s degree. She received Certificates of Gratitude for presenting papers at major conferences including the International Conference on Innovations in Computing Technologies (UET Peshawar), ICCSI (University of Haripur), and ICCIS (Kohat University). Her research presentations on AI-based fan control, robotic fruit harvesting, and end effector position estimation have been acknowledged for their innovation and technical depth. Additionally, she earned certifications from Coursera in prestigious Stanford-offered courses like Machine Learning Specialization and Generative AI for Everyone, showcasing her commitment to continuous learning. Her accolades reflect her dedication to cutting-edge research and meaningful contributions to the engineering community. These awards and recognitions not only celebrate her achievements but also affirm her potential as a leading innovator in AI-driven electrical and robotic systems.

Research Focus

Hamna Baig’s research is centered around Artificial Intelligence, Machine Learning, Robotics, and Wireless Sensing Systems. Her projects emphasize the application of deep learning and AI models for real-world problem-solving, particularly in healthcare monitoring, smart energy systems, and precision robotics. She has developed RF sensing platforms for gait monitoring in Parkinson’s patients, designed AI-based systems for environmental control, and contributed to machine learning-driven robotic arm control for fruit harvesting and biopsy systems. Hamna’s work also explores adaptive fan control for residential energy efficiency and wireless sensing to prevent bedsores, reflecting her commitment to tech-driven well-being. With a blend of academic rigor and engineering intuition, she is passionate about pushing the boundaries of intelligent systems to improve quality of life. Hamna continues to refine her skills in AI integration with embedded hardware, and her ongoing research contributes to the advancement of energy-aware, health-supportive, and human-centric technologies.

Publication Top Notes

  • 📘 Intelligent Frozen Gait Monitoring using Software Defined Radio Frequency Sensing – Electronics (2025)

  • 🤖 Machine Learning-Based Estimation of End Effector Position in Three-Dimension Robotic Workspace – IJIST Journal (2024)

  • 🍊 A Robotic Approach for Fruit Harvesting with Machine Learning based Joint Angles Prediction – ICCSI Conference (2024)

  • 🌬️ Artificial Intelligence based Adaptive Fan Control in Office Settings for Energy Efficiency – ICCIS Conference / Springer (2024)

  • 🦾 A Robotic Arm Based Intelligent Biopsy System – ICCIS Conference / Springer (2024)

  • 🛏️ Design of an Intelligent Wireless Channel State Information Sensing System to Prevent Bedsores – IEEE Sensors (Under Review)

  • 🏠 Enhancing Home Comfort and Energy Consumption with an AI-based Environmental Sensing Control Model – PeerJ (Under Review)

  • 🌬️ Breathing Techniques Redefined: Pros and Cons of Traditional Methods & the Promise of SDRF Sensing – Elsevier, Digital Communications and Networks (Under Review)

Aleksandar Jovanovic | Engineering Award | Most Reader’s Article Award

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Assoc Prof Dr. Aleksandar Jovanovic | Engineering Award | Most Reader’s Article Award

professor at Faculty of engineering University of Kraguejvac, Serbia

Dr. Aleksandar Jovanovic is a distinguished academic with extensive experience in transportation and traffic engineering. He completed his PhD at the University of Belgrade in 2017, focusing on Operations Research in Urban Transportation. His academic journey also includes an MSc and BSc in Traffic Engineering and Urban Transportation from the same institution. Dr. Jovanovic’s career encompasses a range of positions, including his current role as Associate Professor at the University of Kragujevac, Serbia, where he has been employed since November 2022. He has previously served as a Postdoctoral Associate at the University of Pittsburgh, and as a Visiting Scholar there. His earlier roles include Assistant Professor at the University of Kragujevac, and Visiting Assistant Professor at the University of Banja Luka. His teaching experience spans undergraduate and graduate courses in traffic engineering, both in Serbia and the United States. He has been recognized with several honors, including a Professional Development Award in 2023 and the Best Paper Award at ICCMAE 2018. Dr. Jovanovic was also a recipient of the Serbian Governmental Scholarship from 2006 to 2017.

Professional Profiles:

📚 Education:

Dr. Aleksandar Jovanovic completed his PhD at the University of Belgrade, Serbia, in October 2017, specializing in Operations Research in Urban Transportation at the Faculty of Transport and Traffic Engineering. Prior to this, he earned his MSc in Traffic Engineering from the same institution in October 2011. Dr. Jovanovic’s academic journey began with a BSc in Urban Transportation, also from the University of Belgrade, awarded in October 2010.

Pofessional Experience:

Dr. Aleksandar Jovanovic has accumulated a wealth of experience in academia and research. From November 2022 to October 2023, he served as a Postdoctoral Associate at the University of Pittsburgh’s Swanson School of Engineering. Prior to this, he was a Visiting Scholar at the same institution from August to November 2021. Currently, Dr. Jovanovic holds the position of Associate Professor at the Department for Motor Vehicles and Motors at the University of Kragujevac, Faculty of Engineering in Serbia, a role he has occupied since November 2022. He previously served as an Assistant Professor at the same department from September 2018 to November 2022 and as a Visiting Assistant Professor at the University of Banja Luka, Faculty of Mechanical Engineering, from March 2019 to October 2022. Earlier in his career, Dr. Jovanovic was a Teaching Assistant in the Department of Road Traffic at the State Engineering College of Applied Studies “Tehnikum Taurunum” in Belgrade from September 2016 to September 2018, and a Junior Teaching Assistant at the State Technical College of Applied Studies in Kragujevac from September 2013 to September 2015.

Teaching Experience:

Dr. Aleksandar Jovanovic has an extensive teaching background, spanning both undergraduate and graduate courses. At the University of Pittsburgh, he has served as a Co-Instructor for the undergraduate courses “Traffic Control Systems” in Spring 2023 and “Traffic Management and Operations” in Fall 2023. At the University of Kragujevac, his teaching roles included instructing undergraduate courses such as “Urban Transportation” from Spring 2018 to 2022, “Traffic Safety” from Fall 2018 to 2021, and “Informatics in Traffic Engineering” from Spring 2018 to 2022. He also co-instructed “Traffic and Traffic Roads” from Fall 2018 to 2020. For graduate students at the University of Kragujevac, Dr. Jovanovic taught “Informatic Systems in Traffic Engineering” in Spring 2018 to 2022, and “Operations Research Applications in Traffic Engineering” from Fall 2019 to 2021. Additionally, he provided a lecture on “Applications of Fuzzy Logic Systems in Traffic Signal Control” for graduate students at the Pittsburgh Intelligent Transportation Systems (PITTs) Lab in Fall 2021.

Awards And Honors:

Dr. Aleksandar Jovanovic has received several notable honors and awards throughout his career. In 2023, he was recognized with a Professional Development Award for his poster presentation at the Postdoctoral Data and Dine Symposium. In 2019, he earned the Best Paper Award at the International Conference on Computational Mathematics and Engineering (ICCMAE) 2018 in Timisoara, specifically in the Applied/Computational Mathematics section. Additionally, between 2006 and 2017, Dr. Jovanovic was a recipient of the Serbian Governmental Scholarship, reflecting his academic excellence and commitment to his field.

Skills:

Dr. Aleksandar Jovanovic possesses a diverse set of computer skills and competencies. In the field of traffic simulation and analysis, he is proficient with tools such as PTV Vissim (including COM and VAP), HCS+T7F, Synchro, and SUMO. For design tasks, he utilizes AutoCAD. Additionally, Dr. Jovanovic is skilled in scripting languages, including Matlab and Python, which he employs for various analytical and programming tasks.

📚Publications :

“Area-wide urban traffic control: A Bee Colony Optimization approach”
Authors: A Jovanović, M Nikolić, D Teodorović
Citations: 85
Year: 2017

“Green vehicle routing in urban zones–A neuro-fuzzy approach”
Authors: AD Jovanović, DS Pamučar, S Pejčić-Tarle
Citations: 82
Year: 2014

“Pre-timed control for an under-saturated and over-saturated isolated intersection: a Bee Colony Optimization approach”
Authors: A Jovanović, D Teodorović
Citations: 26
Year: 2017

“Ecology based network traffic control: A bee colony optimization approach”
Authors: A Jovanović, A Stevanović, N Dobrota, D Teodorović
Citations: 13
Year: 2022

“Fixed-time traffic control at superstreet intersections by bee colony optimization”
Authors: A Jovanović, D Teodorović
Citations: 12
Year: 2022

“The assessment and selection of suppliers using AHP and MABAC with type-2 fuzzy numbers in automotive industry”
Authors: N Komatina, D Tadić, A Aleksić, AD Jovanović
Citations: 11
Year: 2023

“Restricted crossing U-turn traffic control by interval Type-2 fuzzy logic”
Authors: A Jovanović, K Kukić, A Stevanović, D Teodorović
Citations: 11
Year: 2023

“Type-2 fuzzy logic based transit priority strategy”
Authors: A Jovanović, D Teodorović
Citations: 10
Year: 2022

“A fuzzy logic simulation model for controlling an oversaturated diverge diamond interchange and ramp metering system”
Authors: A Jovanović, K Kukić, A Stevanović
Citations: 9
Year: 2021

“Multi-objective optimization of a single intersection”
Authors: A Jovanović, D Teodorović
Citations: 8
Year: 2021