Milos Vasic | Material science | Best Researcher Award

Dr. Milos Vasic | Material science | Best Researcher Award

Dr. Miloš Vasić is a seasoned expert in the field of chemical technology and inorganic chemical engineering, with nearly 20 years of research and professional experience. A Ph.D. graduate from the University of Belgrade, he specializes in recycling processes, mechanical activation of raw materials, and optimization of material properties—particularly in the context of porous and ceramic materials. In recent years, he has expanded his focus to include polymer investigations and the development of innovative construction products. Dr. Vasić has contributed to over 117 scientific papers, including 23 indexed in the Web of Science. He is actively involved in high-impact national and international projects and plays a leading role in the standardization and certification of building materials in Serbia. His work extends to quality assurance, technical consulting, and scientific cooperation, and he currently chairs the Serbian Standards Institute’s Committee for Masonry Structures.

Profile

🎓 Education

Dr. Miloš Vasić obtained his Ph.D. in Technical Sciences in the field of Chemistry and Chemical Technology from the Faculty of Technology and Metallurgy, University of Belgrade, in 2014. His doctoral studies focused on the physical and chemical processes involved in optimizing raw materials and ceramic properties. He completed his B.Sc. in Inorganic Chemical Engineering from the same institution in 2005, building a strong foundation in inorganic material processing, reaction kinetics, and industrial-scale applications. Throughout his academic training, Dr. Vasić emphasized interdisciplinary approaches, merging principles of chemistry, process engineering, and materials science. His education has equipped him to engage in both theoretical modeling and practical implementation of new materials, especially in the field of construction ceramics and industrial recycling, laying the groundwork for his substantial research and development contributions in academia and industry alike.

🧪 Experience

Dr. Miloš Vasić currently serves as a researcher at the Laboratory for Building Ceramics, where he specializes in the testing and development of clay-based and ceramic construction products. He has led numerous national and bilateral projects on material recycling, energy efficiency in ceramic production, and the design of self-compacting concretes using waste. Since 2019, he has chaired the Serbian Standards Institute’s Committee for Masonry Structures, overseeing regulatory and technical guidelines. He has been instrumental in maintaining laboratory quality systems aligned with SRPS EN ISO/IEC 17025 standards. In 2020, he became a technical expert for Proficiency Testing (PT) at the IMS Institute, contributing to Serbia’s designation of AVCP bodies for construction products. His practical and regulatory contributions have influenced policy-making, quality standards, and innovation within the materials testing and certification sector.

🏅 Awards and Honors

While specific named awards are not explicitly listed, Dr. Miloš Vasić’s professional recognitions are evident through his appointments and leadership roles. He was named as the responsible person in the Serbian government’s designation decision for construction product performance verification (Decision No. 35-00-0108/2020-08), reflecting national-level trust in his technical expertise. His appointment as Chair of the Serbian Standards Institute’s Committee for Masonry Structures since 2019 underscores his influence and authority in standardization. He has also been selected as a technical expert for IMS Institute’s Proficiency Testing, indicating peer recognition in the domain of ceramic and masonry product quality assurance. His invitation to lead or participate in multiple nationally and internationally funded scientific projects demonstrates his high standing in Serbia’s R&D community. These roles and responsibilities serve as testament to his reputation, leadership, and contributions to material sciences and standardization efforts.

🔬 Research Focus

Dr. Miloš Vasić’s research spans multiple interdisciplinary domains within chemical technology, with an emphasis on recycling of inorganic raw materials, mechanical activation, and optimization of porous construction materials. His early research centered on ceramic building materials, including clay masonry units and roof tiles, analyzing their physical and chemical properties under various industrial processes. He has developed and modeled drying parameters for energy efficiency and sustainable material production. Over the last seven years, his research scope has expanded to include polymer materials and the design of novel construction products. Through involvement in major projects, including collaborations with Turkey and the EU’s COST actions, he has advanced knowledge in nanopowder-based ceramics, self-compacting concrete, and multifunctional composite materials. Dr. Vasić’s applied research has significantly influenced industrial practices, national standards, and sustainable construction technologies.

Conclusion

Dr. Miloš Vasić is a dedicated researcher and technical leader whose interdisciplinary expertise in chemical engineering and construction materials has driven advancements in sustainable technologies, standardization, and industrial process optimization.

Publications
  • Assessment of the Drone Arm’s Plastic–Metal Joint Mechanical Resistance Following Natural and Artificial Aging of the 3D-Printed Plastic Component

    Materials
    2025-06-01 | Journal article
    CONTRIBUTORS: Miloš R. Vasić; Snežana Vučetić; Vesna Miljić; Miloš Vorkapić; Anja Terzić; Mladen Ćosić; Danica M. Bajić
  • Additive technology and 7R methodology in circular economy for wearable sensors production

    Journal of Engineering Management and Competitiveness
    2024 | Journal article
    CONTRIBUTORS: Miloš Vorkapić; Stefan Ilić; Marko Spasenović; Miloš Vasić; Dragan Ćoćkalo
  • Assessment of construction and demolition waste application for improving frost resistance in masonry clay units

    Science of Sintering
    2024 | Journal article
    CONTRIBUTORS: Milos Vasic, R.; Anja Terzic; Marko Stojanovic; Milos Vorkapic; Dragan Bojovi
  • INCREASE OF FROST RESISTANCE OF CLAY MASONRY UNITS WITH CONSTRUCTION DEMOLITION WASTE ADDITION: A CASE STUDY

    International Journal of Modern Manufacturing Technologies
    2024 | Journal article

    EID:

    2-s2.0-85216944877

    Part ofISSN: 20673604
    CONTRIBUTORS: Vasić, M.; Vorkapić, M.; Bojović, D
  • PETG as an Alternative Material for the Production of Drone Spare Parts

    Polymers
    2024-10-24 | Journal article
    CONTRIBUTORS: Marija Z. Baltić; Miloš R. Vasić; Miloš D. Vorkapić; Danica M. Bajić; Ján Piteľ; Petr Svoboda; Aleksandar Vencl

Abdul Majeed | Material Sciences | Best Researcher Award

Dr. Abdul Majeed | Material Sciences | Best Researcher Award

Dr. Abdul Majeed is a dynamic educator, researcher, and science communicator with 6 years of teaching and 11 years of research experience in materials science, blending experimental and theoretical expertise in nanomaterials, complex oxides, and magnetic materials. As an Assistant Professor at The Islamia University of Bahawalpur, he is dedicated to mentoring students and delivering engaging, hands-on physics instruction. His exceptional communication, organizational, and multi-tasking skills complement his academic contributions, fostering a collaborative learning environment and promoting scientific inquiry. Known for simplifying complex scientific concepts, Dr. Majeed is committed to knowledge dissemination, community engagement, and pursuing innovative research for societal benefit.

Profile

Education 🎓

Dr. Majeed earned his Ph.D. in Physics from the University of Malakand, focusing on the effects of cation substitution in hexagonal nanoferrites, preceded by an M.Phil. in Physics from The Islamia University of Bahawalpur on rare-earth doped nanocrystallites, and a BS in Physics from Islamia College University, Peshawar. His education encompasses solid theoretical foundations in materials science, magnetism, quantum mechanics, and computational physics. He is proficient in synthesis techniques like sol-gel auto-combustion, micro-emulsion, and ultrasound-assisted methods, and skilled in material characterization techniques including XRD, SEM, TEM, VSM, UV-Vis, FTIR, and impedance analysis. Dr. Majeed also completed a diploma in English Language, enhancing his academic and professional communication

Experience 👨‍🏫

Dr. Majeed is currently serving as an Assistant Professor in the Department of Physics at The Islamia University of Bahawalpur since March 2021, teaching undergraduate and MPhil-level physics courses, supervising research students, and coordinating academic and student affairs. Previously, he taught Physics and Mathematics at the Government Higher Secondary School Rehanpur, where he also held the role of Chief Proctor. He has over 11 years of research experience in materials science, particularly in synthesizing and characterizing complex oxide nanomaterials. He actively contributes to administrative duties including BS program coordination, LMS management, and student affairs leadership, reflecting his multifaceted involvement in academia and institutional development.

Awards & Recognitions 🏅

Dr. Abdul Majeed has received recognition for his impactful research through multiple publications in reputed journals such as Ceramics International, Journal of Alloys and Compounds, and Materials Science in Semiconductor Processing. His work is widely cited in the field of microwave absorption materials and magnetic oxides. He actively collaborates with international scholars and contributes to high-impact studies, particularly in experimental and computational material sciences. His academic excellence is reflected in his outstanding academic grades (CGPA above 3.5 in all degrees) and his leadership in teaching, coordination, and student mentorship roles. His visibility on platforms like Google Scholar and ResearchGate underscores his scholarly influence and engagement.

Research Interests 🔬

Dr. Abdul Majeed’s research centers on the synthesis, characterization, and modeling of nanostructured materials, including hexagonal ferrites, multiferroics, dielectric materials, and graphene-ferrite composites, for applications in high-frequency electronics, energy storage, and microwave absorption. His work bridges experimental physics with computational simulations, including DFT-based studies using WIEN2k, exploring the electronic, optical, magnetic, and structural behavior of advanced materials. He specializes in sol-gel, co-precipitation, and ultrasound-assisted synthesis methods and uses a variety of advanced characterization tools. His current projects explore co-substituted magnetic oxides, rare-earth doping effects, and smart materials for energy and sensor technologies.

Publications

Lichen Shi | Mechanical Engineering | Best Researcher Award

Prof. Lichen Shi | Mechanical Engineering | Best Researcher Award

 

Profile

Education

Lichen Shi (also written as Shi Lichen) is a distinguished Chinese researcher specializing in intelligent measurement, equipment status monitoring, fault diagnosis, and electromechanical system modeling. He was born on June 28, 1972, and is currently affiliated with the School of Mechanical and Electrical Engineering at Xi’an University of Architecture and Technology (XAUAT), China.

With a strong academic and research background, Professor Shi has dedicated his career to advancing intelligent measurement techniques through deep learning, as well as improving the reliability of electromechanical systems through fault diagnosis and dynamic analysis.

Academic Contributions

Professor Shi has published extensively in prestigious international journals, particularly in IEEE Sensors Journal, Measurement, and Computer Engineering & Applications. His notable works focus on deep learning-based fault diagnosis, graph neural networks, and AI-driven predictive modeling for mechanical systems.

Some of his key contributions include:

  • Developing an AI-based method for reading pointer meters using human-like reading sequences.
  • Proposing a graph neural network and Markov transform fields approach for gearbox fault diagnosis.
  • Introducing CBAM-ResNet-GCN methods for unbalance fault detection in rotating machinery.
  • Advancing domain transfer learning techniques for mixed-data gearbox fault diagnosis.
  • Pioneering a lightweight low-light object detection algorithm (CDD-YOLO) for enhanced industrial applications.

His research findings have contributed significantly to the optimization of industrial machinery, predictive maintenance, and AI-driven automation in electromechanical systems. Many of his publications are frequently cited, underlining their impact on the field.

Research Interests

Professor Shi’s research spans multiple cutting-edge areas, including:

  • Intelligent Measurement with Deep Learning
  • Equipment Status Monitoring and Fault Diagnosis
  • Electromechanical System Modeling and Dynamic Analysis

Professional Impact

As a leading expert in intelligent diagnostics and mechanical system optimization, Professor Shi has played a crucial role in bridging the gap between artificial intelligence and industrial engineering. His contributions have aided in the development of more efficient, predictive, and adaptive electromechanical systems, helping industries reduce downtime and improve operational efficiency.

Publication

  • [1] Qi Liu, Lichen Shi*. A pointer meter reading method based on human-like readingsequence and keypoint detection[J]. Measurement, 2025(248): 116994. https://doi.org/10.1016/j.measurement.2025.116994
  • [2] Haitao Wang, Zelin. Liu, Mingjun Li, Xiyang Dai, Ruihua Wang and LichenShi*. AGearbox Fault Diagnosis Method Based on Graph Neural Networks and MarkovTransform Fields[J]. IEEE Sensors Journal, 2024, 24(15) :25186-25196. doi:
    10.1109/JSEN.2024.3417231
  • [3] Haitao Wang, Xiyang Dai, Lichen Shi*, Mingjun Li, Zelin Liu, Ruihua Wang , XiaohuaXia. Data-Augmentation Based CBAM-ResNet-GCN Method for Unbalance Fault
    Diagnosis of Rotating Machinery[J]. IEEE Sensors Journal, 2024,12:34785-34799. DOI:
    10.1109/access.2024.3368755.
  • 4] Haitao Wang, Mingjun Li, Zelin Liu, Xiyang Dai, Ruihua Wang and Lichen Shi*. RotaryMachinery Fault Diagnosis Based on Split Attention MechanismandGraphConvolutional Domain Adaptive Adversarial Network[J]. IEEE Sensors Journal, 2024,
    24(4) :5399-5413. doi: 10.1109/JSEN.2023.3348597.
  • [5] Haitao Wang, Xiyang Dai, Lichen Shi*. Gearbox Fault Diagnosis Based onMixedData-Assisted Multi-Source Domain Transfer Learning under Unbalanced Data[J]. IEEESensors Journal. doi: 10.1109/JSEN.2024.3477929