Yasser Almoteri | Mathematics | Research Excellence Award

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Assist. Prof. Dr. Yasser Almoteri | Mathematics | Research Excellence Award

Imam Mohammad Ibn Saud Islamic University | Saudi Arabia

Dr. Yasser Almoteri is an Assistant Professor of Applied Mathematics at Al-Imam Mohammad Ibn Saud Islamic University in Riyadh, Saudi Arabia, where he contributes to advancing interdisciplinary mathematical research and graduate education. He earned his PhD in Applied Mathematics from the New Jersey Institute of Technology (NJIT) in 2023, completing a dissertation focused on bacterial motion and spread in porous environments, a topic that bridges biomathematics, complex fluids, and computational modeling. His advanced training also includes a Master of Science in Mathematics from New York University (2017) and a Bachelor of Science in Applied Mathematics from Al-Imam Mohammad Ibn Saud Islamic University (2011). Before joining the faculty, Dr. Almoteri served as a Research Assistant and Teaching Assistant at NJIT from 2018 to 2023, where he gained extensive experience in mathematical modeling, numerical simulations, and interdisciplinary collaborations. His research explores biomathematics, collective behavior of micro-swimmers, and fluid–structure interactions in complex and impure environments. He has presented his work at several prestigious conferences, including the APS March Meeting, APS Division of Fluid Dynamics, and the International Congress on Industrial and Applied Mathematics (ICIAM). Dr. Almoteri has earned notable academic recognitions, including the Silver Medal at the Dana Knox Research Showcase (2021) and the Outstanding Graduate Student Award at NJIT (2022). His work has been supported through competitive research and teaching assistantships. Alongside his academic pursuits, he is skilled in mathematical modeling and programming using MATLAB and R. He is fluent in Arabic and proficient in English, enabling effective communication in diverse academic settings.

Profiles: Scopus | Google Scholar

Featured publications

Almoteri, Y., & Lushi, E. (2025). Chemotactic aggregation dynamics of micro-swimmers in Brinkman flows. arXiv preprint arXiv:2504.20925.

Almoteri, Y. (2023). Bacterial motion and spread in porous environments (Doctoral dissertation, New Jersey Institute of Technology).

Almoteri, Y., & Lushi, E. (2025). Microswimmer collective dynamics in Brinkman flows. Physical Review Fluids, 10(8), 083102.

Almoteri, Y., Guzmán-Lastra, F., & Lushi, E. (2025). Micro-swimmers in Brinkman flow: Coupled dynamics and motion near surfaces. Division of Fluid Dynamics Annual Meeting.

Almoteri, Y., & Ghezal, A. (2025). On the existence and uniqueness of two-dimensional nonlinear fuzzy difference equations with logarithmic interactions. Mathematics, 13(21), 3532.

Dimitrios Tsourounis | Computer Science | Best Researcher Award

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Dr. Dimitrios Tsourounis | Computer Science | Best Researcher Award

Dr. Dimitrios Tsourounis | Computer Science | University of Patras | Greece

Dimitrios Tsourounis is a passionate computer scientist specializing in computer vision, deep learning, and quantum machine learning. Born on February 26, 1991, in Greece, Dimitrios earned his Ph.D. from the University of Patras in 2023, focusing on deep learning strategies for problems with limited data. He has contributed significantly to advancing machine learning methods and quantum computing integration, currently working as a Research Scientist at Quantum Neural Technologies (QNT) in Athens. Dimitrios is also involved in autonomous aerial systems research at the Athena Research Center, applying computer vision techniques to fuse radar and RGB camera data for UAVs. His multidisciplinary expertise includes physics, electronics, and artificial intelligence, supported by multiple successful EU-funded projects. With a proven track record in innovation and real-world applications, Dimitrios is recognized for bridging theoretical research and industrial challenges, particularly in quantum-enhanced machine learning and biometric security.

Author Profile

Scopus | Orcid | Google Scholar

Education 

Dimitrios completed his Ph.D. in Computer Vision at the University of Patras, Greece (2017-2023), specializing in deep learning, neural networks, and AI strategies for limited data scenarios under Prof. George Economou’s supervision. His doctoral thesis explored novel transfer learning and knowledge distillation techniques. Prior to this, Dimitrios earned an M.Sc. in Electronics, Engineering and Computer Science (2015-2017) from the University of Patras, graduating summa cum laude with a thesis on deep sparse coding. His academic foundation was built on a B.Sc. in Physics (2010-2015) from the same university, graduating magna cum laude, with research focused on sparse representation for offline handwritten signature recognition. Dimitrios also briefly studied medicine before shifting to physics and computing, showcasing a diverse academic background. Throughout his studies, he demonstrated academic excellence, receiving top grades and honors in rigorous technical fields that combine physical sciences with computer engineering.

Experience

Dimitrios currently works as a Research Scientist in Quantum Machine Learning at Quantum Neural Technologies (QNT) in Athens, designing quantum algorithms and integrating machine learning with quantum computing for industrial applications such as pharmaceuticals, cryptography, and finance. Since July 2025, he has been a Computer Vision Scientist at the Athena Research Center, focusing on UAV systems that fuse radar and camera data for autonomous aerial navigation. His Ph.D. research (2017-2023) involved deep learning for limited data, emphasizing convolutional neural networks and biometric applications. Dimitrios contributed to the DeepSky project on cloud type estimation using multi-sensor data and worked on Greek lip reading datasets employing deep sequential models. He also participated in RoadEye, developing AI solutions for road condition monitoring, pothole, and speed bump detection. Throughout his career, Dimitrios has utilized tools like Python, PyTorch, TensorFlow, Qiskit, and Matlab, continuously merging theoretical innovation with practical applications in computer vision, AI, and quantum technologies.

Awards and Honors

Dimitrios Tsourounis has received notable recognition for his academic and research excellence. He was awarded a prestigious scholarship from the Greek State Scholarships Foundation (IKY) to support his Ph.D. studies, reflecting his outstanding merit. Throughout his academic career, Dimitrios graduated summa cum laude for his M.Sc. and magna cum laude for his B.Sc., highlighting consistent academic distinction. His research contributions have been supported by competitive European Union and Greek national funding programs, including co-funding for projects such as DeepSky and RoadEye. Dimitrios has also been acknowledged within the quantum computing and AI research communities for pioneering integration of machine learning with quantum frameworks. His work has earned invitations to collaborate with leading academic and industry partners, reinforcing his reputation as an innovative scientist. While yet to accumulate traditional prize awards, his growing publication record and project leadership positions underscore his impact and future promise in computer science and quantum technologies.

Research Focus 

Dimitrios Tsourounis’s research centers on computer vision, deep learning, and quantum machine learning, with a particular focus on addressing challenges of limited data availability in neural network training. His Ph.D. work pioneered transfer learning and knowledge distillation methods tailored to biometric security and pattern recognition. Currently, Dimitrios explores quantum-enhanced machine learning algorithms leveraging variational quantum circuits to improve performance on complex scientific and industrial problems. His expertise also spans multimodal data fusion, combining radar and visual data in autonomous aerial systems to enhance object detection accuracy. Additionally, he investigates sequential deep learning architectures for tasks such as lip reading in the Greek language and environmental sensing through cloud type recognition using thermal and all-sky cameras. Dimitrios integrates classical machine learning frameworks like PyTorch with quantum programming tools such as Qiskit and Pennylane, pushing the frontier of hybrid classical-quantum AI. His work aims to bridge theoretical advances and practical applications across fields including cryptography, healthcare, and autonomous vehicles.

Publications 

  • “Deep Sparse Coding for Signal Representation”

  • “Neural Networks for Biometric Applications with Limited Data”

  • “Quantum Variational Circuits in Machine Learning”

  • “Fusion of Radar and RGB Data in UAV Object Detection”

  • “Lip Reading Greek Words Using Sequential Deep Learning”

  • “Cloud Type Estimation with All-Sky and Thermal Cameras”

  • “Real-Time Road Condition Monitoring via Computer Vision”

  • “Knowledge Distillation Techniques in Convolutional Neural Networks”

Conclusion

Dimitrios Tsourounis exemplifies a forward-thinking computer scientist, seamlessly integrating deep learning and quantum computing to tackle real-world challenges. His academic excellence, coupled with his innovative research in limited-data neural networks and quantum-enhanced AI, positions him as a leading researcher in computer vision and machine learning. Dimitrios’s contributions advance both theoretical knowledge and practical solutions across diverse sectors, from autonomous systems to pharmaceuticals. His dedication and interdisciplinary approach promise significant future impact in computer science and emerging quantum technologies.

 

Iustina Ivanova | Computer Science | Best Researcher Award

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Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

👤 Mrs. Iustina Ivanova, FBK, Italy

Iustina Ivanova is an accomplished researcher in the field of Artificial Intelligence (AI) with a focus on computer vision and machine learning applications in real-world scenarios. She holds a Master’s degree in Artificial Intelligence from the University of Southampton, where she earned distinction for her research on neural networks for object detection. Currently, Iustina is engaged in AI research in smart agriculture at the Fondazione Bruno Kessler in Italy. Over the years, she has contributed to a variety of high-impact projects, including developing a recommender system for outdoor sport climbers and researching sensors for sports activity analysis. Her work has earned her several well-regarded publications and recognition in the AI and computer vision communities.

Professional Profile

Scopus

Orcid

🌟 Summary of Suitability for the Research for Best Researcher Award

Iustina Ivanova demonstrates exceptional qualifications for the “Research for Best Researcher Award.” Her academic background, professional experience, and research contributions highlight her significant impact on the fields of artificial intelligence (AI), machine learning, and computer vision. Her academic journey is distinguished by a Master’s degree in Artificial Intelligence with distinction from the University of Southampton and ongoing research pursuits during her Ph.D. studies. While her Ph.D. remains incomplete, the work she has undertaken—such as her contributions to recommender systems and computer vision—showcases her ability to address complex, real-world problems.

Professionally, Iustina’s research experience is diverse and impactful. At the Fondazione Bruno Kessler, she has been actively involved in applying AI to smart agriculture, addressing sustainability and innovation in the domain. Her previous roles, including as a Computer Vision Data Scientist and Data Science Moderator, further demonstrate her ability to bridge academia and industry.

🎓 Education

Iustina Ivanova has an impressive academic background in computer science and AI. She completed her Master of Science in Artificial Intelligence with distinction at the University of Southampton, UK, in 2018. Before that, she earned a Specialist degree in Software Engineering from Bauman Moscow State Technical University, Russia, in 2013. In 2019, she pursued a PhD in Computer Science at the Free University of Bolzano, Italy, although she later decided to focus more on practical AI applications. Her academic journey includes notable achievements such as developing research in neural networks for object detection, which has been the cornerstone of her professional career in AI.

💼  Professional Experience 

Iustina Ivanova has a diverse and robust professional background in AI and computer vision. She currently works as a researcher at the Fondazione Bruno Kessler, Italy, specializing in the use of AI for smart agriculture. Prior to this, Iustina served as a Data Science Moderator at Netology, Russia, where she designed and delivered online courses in statistics and mathematics for data science students. She also worked as a Computer Vision Data Scientist at OCRV, Russia, where she helped develop a video-based tracking system for railway workers, focusing on object detection and worker time measurement. Iustina’s role as a teacher of informatics and mathematics at Repetitor.ru involved preparing high school students for their final exams, ensuring that many students successfully entered top universities. Throughout her career, she has collaborated on numerous innovative projects in AI, particularly in outdoor sports and smart agriculture.

🏅Awards and Recognition 

Iustina Ivanova’s dedication and excellence in the field of AI have been recognized through multiple prestigious awards and accolades. Notably, she won several editions of the NOI Hackathon, including the SFSCON Edition (2021, 2022, 2024) and the Open Data Hub Edition (2022), showcasing her ability to create cutting-edge solutions in AI and data science. Her contributions to research and development in AI for sports activity analysis and computer vision have been published in highly regarded journals and conferences, such as the ACM Conference on Recommender Systems and IEEE Conferences. Iustina has also received recognition for her teaching contributions, inspiring future generations of data scientists. Her projects, especially those related to sports climbers’ recommender systems and sensor data analysis, have received wide acclaim for their innovation and real-world impact.

🌍 Research Skills On Computer Science

Iustina Ivanova’s research expertise spans artificial intelligence, machine learning, computer vision, and recommender systems. She is particularly skilled in using AI techniques to solve complex problems in real-world applications. Her work with neural networks for object detection and sensor data analysis has led to significant advancements in both sports and smart agriculture sectors. Iustina is proficient in Python, OpenCV, machine learning frameworks like PyTorch and TensorFlow, and data analysis tools such as Jupyter Notebook and Git. She is well-versed in the development of recommender systems and has implemented innovative solutions for outdoor sports, including climbing crag recommendations. Her interdisciplinary approach combines knowledge from software engineering, data science, and AI to design systems that enhance user experience and improve decision-making. Iustina is committed to the continual development of her skills, evident in her participation in advanced data science and deep learning courses, as well as her extensive practical work in AI.

📖 Publication Top Notes

  • Climbing crags repetitive choices and recommendations
    • Author: Ivanova, I.
    • Citation: Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023
    • Year: 2023
    • Pages: 1158–1164
  • How can we model climbers’ future visits from their past records?
    • Authors: Ivanova, I., Wald, M.
    • Citation: UMAP 2023 – Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2023
    • Pages: 60–65
  • Introducing Context in Climbing Crags Recommender System in Arco, Italy
    • Authors: Ivanova, I.A., Wald, M.
    • Citation: International Conference on Intelligent User Interfaces, Proceedings IUI
    • Year: 2023
    • Pages: 12–15
  • Climbing crags recommender system in Arco, Italy: a comparative study
    • Authors: Ivanova, I., Wald, M.
    • Citation: Frontiers in Big Data
    • Year: 2023
    • Volume: 6, Article: 1214029
  • Map and Content-Based Climbing Recommender System
    • Authors: Ivanova, I.A., Buriro, A., Ricci, F.
    • Citation: UMAP2022 – Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2022
    • Pages: 41–45
  • Climbing Route Difficulty Grade Prediction and Explanation
    • Authors: Andric, M., Ivanova, I., Ricci, F.
    • Citation: ACM International Conference Proceeding Series
    • Year: 2021
    • Pages: 285–292
  • Climber behavior modeling and recommendation
    • Author: Ivanova, I.
    • Citation: UMAP 2021 – Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2021
    • Pages: 298–303
  • Knowledge-based recommendations for climbers
    • Authors: Ivanova, I., Andrić, M., Ricci, F.
    • Citation: CEUR Workshop Proceedings
    • Year: 2021
    • Volume: 2960
  • Climbing activity recognition and measurement with sensor data analysis
    • Authors: Ivanova, I., Andric, M., Janes, A., Ricci, F., Zini, F.
    • Citation: ICMI 2020 Companion – Companion Publication of the 2020 International Conference on Multimodal Interaction
    • Year: 2020
    • Pages: 245–249
  • Video and Sensor-Based Rope Pulling Detection in Sport Climbing
    • Authors: Ivanova, I., Andrić, M., Moaveninejad, S., Janes, A., Ricci, F.
    • Citation: MMSports 2020 – Proceedings of the 3rd International Workshop on Multimedia Content Analysis in Sports
    • Year: 2020
    • Pages: 53–60

Raghad K Mohammed | Computer Science | Academic Excellence Award

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Dr. Raghad K Mohammed | Computer Science | Academic Excellence Award

👤 Dr. Raghad K Mohammed, College of Computer Science and Information Technology, Iraq

Raghad Khaled Mohammed, born on September 29, 1978, is a dedicated academic professional specializing in Computer Networks. She serves as a Lecturer at the College of Dentistry, University of Baghdad, where she has contributed significantly to education and research since 2005. A Muslim, married, and a mother of two, Raghad has consistently balanced her personal and professional life with distinction. Her academic journey began with a Bachelor’s degree from Al-Rafidain in 2002, followed by a Master’s in Computer Networks from the University of Technology in 2005. She is currently pursuing a PhD in Computer Science and Information Technology at the University of Anbar. Her professional roles have included leadership positions, such as Head of the Planning and Quality Assurance Units, showcasing her commitment to academic excellence and institutional development.

Professional Profile

scopus

🌟 Suitability for the Research for Academic Excellence Award

Summary of Suitability
Raghad Khaled Mohammed’s extensive academic journey and professional accomplishments demonstrate her dedication to higher education and research, making her a strong candidate for the Research for Academic Excellence Award. With a career spanning nearly two decades, her contributions as a lecturer at the University of Baghdad’s College of Dentistry, along with leadership roles in quality assurance, planning, and continuing education, reflect her commitment to fostering academic and institutional excellence.

🎓  Education

Raghad Khaled Mohammed’s academic qualifications reflect her dedication to advancing knowledge in Computer Science. She earned her Bachelor’s degree in 2002 from Al-Rafidain, laying the foundation for her career. In 2005, she completed a Master’s degree in Computer Networks from the Informatics Institute for Graduate Studies, University of Technology, Baghdad. This specialization equipped her with technical expertise in designing and managing network systems. Currently, she is pursuing a PhD in Computer Science and Information Technology at the University of Anbar, demonstrating her commitment to lifelong learning and academic growth. Her academic progression highlights her passion for integrating innovative solutions and knowledge-sharing within the field of computer science, with a focus on practical applications that benefit both academia and industry.

💼  Professional Experience

Raghad Khaled Mohammed has a rich professional journey at the University of Baghdad. She started as an Assistant Lecturer in 2005, demonstrating a strong foundation in teaching and academic research. From 2006 to 2009, she led the Planning Department, showcasing her organizational and strategic planning skills. In 2010, she was promoted to Lecturer, reflecting her academic and professional growth. Between 2016 and 2018, she excelled as the Head of the Quality Assurance Unit, where she implemented initiatives to enhance educational standards. Her leadership continued in 2024 as the Head of the Continuing Education Unit, focusing on faculty and student skill development. Raghad’s multifaceted roles underline her expertise in education, administration, and her dedication to fostering an environment of continuous improvement and innovation.

🏅 Awards and Recognition

Raghad Khaled Mohammed’s career is marked by achievements and recognition in academia. Her contributions to quality assurance earned her institutional accolades during her tenure as the Head of the Quality Assurance Unit. Her innovative initiatives in the Planning Department were lauded for their impact on academic progress and administrative efficiency. As a researcher and educator, she has been acknowledged for her role in advancing the field of Computer Networks, earning respect among peers and students alike. Raghad has also been recognized for her leadership in Continuing Education, where she played a pivotal role in professional development programs. These accolades affirm her commitment to academic excellence and her ability to inspire positive change within her institution.

🌍 Research Skills On Computer Science

Raghad Khaled Mohammed possesses diverse research skills, particularly in Computer Networks and Information Technology. Her expertise includes network architecture design, security protocols, and system optimization. She is skilled in using advanced simulation tools and programming languages to develop innovative solutions for complex networking challenges. Raghad’s research focuses on bridging the gap between theoretical concepts and real-world applications, aiming to enhance efficiency and cybersecurity in digital systems. Her ability to integrate interdisciplinary approaches, coupled with her technical expertise, ensures impactful contributions to academia and industry. With ongoing doctoral studies, her research skills continue to evolve, driving advancements in Computer Science and Information Technology.

📖 Publication Top Notes

Title: U-Net for Genomic Sequencing: A Novel Approach to DNA Sequence Classification
  • Authors: Mohammed, R.K.; Alrawi, A.T.H.; Dawood, A.J.
    Year: 2024
    Journal: Alexandria Engineering Journal
    Volume and Pages: 96, pp. 323–331
    Citations: 0
Title: Optimizing Genetic Prediction: Define-by-Run DL Approach in DNA Sequencing
  • Authors: Mohammed, R.K.; Alrawi, A.T.H.; Dawood, A.J.
    Year: 2023
    Journal: Journal of Intelligent Systems
    Volume and Pages: 32(1), Article ID: 20230130
    Citations: 0
Title: Detecting Damaged Buildings on Post-Hurricane Satellite Imagery Based on Transfer Learning
  • Authors: Al-Saffar, R.; Mohammed, R.K.; Abed, W.M.; Hussain, O.F.
    Year: 2022
    Journal: NeuroQuantology
    Volume and Pages: 20(1), pp. 105–119
    Citations: 1

Milos Kojic | Computational Modeling | Research Excellence Award

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Prof Dr. Milos Kojic | Computational Modeling | Research Excellence Award

Professor of Nanomedicine at Houston Methodist Research Institute, United States

Dr. Milos Kojic is a highly accomplished researcher with an extensive background in mechanical engineering, computational methods, and bioengineering. His career spans over five decades, during which he has made significant contributions to finite element methods (FEM), discrete particle methods, software development, biomechanics, and inelastic material deformation. Dr. Kojic has held multiple prestigious academic and industry positions, authored over 250 papers, and published several key textbooks and monographs. His research and leadership have had a profound impact on both academia and industry, particularly in the fields of nonlinear structural analysis and computational mechanics.

Professional Profile 

Education 🎓

Dr. Milos Kojic has an extensive and distinguished educational background, rooted in mechanical engineering and computational methods. He began his academic journey at the University of Kragujevac in Serbia, where he earned a Bachelor of Science (B.S.) in Mechanical Engineering from 1960 to 1964. His outstanding academic performance during this period earned him a scholarship and a prestigious award as the top student in his class. Continuing his studies, Dr. Kojic pursued a Master of Science (M.S.) in Mechanics at the University of Belgrade from 1964 to 1969, where he deepened his understanding of mechanics and mathematical methods. Seeking to further expand his expertise, Dr. Kojic enrolled at Rice University in Houston, Texas, where he completed his Doctor of Philosophy (Ph.D.) in Mechanical Engineering between 1970 and 1972. His doctoral research focused on the “Influence of Fluid Pressure Gradient on Plasticity of Porous Media,” demonstrating his early commitment to pioneering work in the field of computational mechanics. During his Ph.D. studies, Dr. Kojic received a prestigious Fulbright Foundation Scholarship and an assistantship from Rice University, underscoring his academic excellence and potential. His educational path laid a strong foundation for his remarkable career in research, teaching, and software development, particularly in the areas of finite element methods and biomechanics.

Work Experience 🏛️

Dr. Milos Kojic has had an illustrious career spanning over five decades, with diverse experiences in both academia and industry. His professional journey began at the Faculty of Mechanical Engineering, University of Kragujevac, where he progressed from Assistant Professor to Full Professor, teaching courses in mechanics and computational methods. Over a period of more than 30 years, Dr. Kojic led a team of researchers in developing numerical methods for nonlinear structural analysis, heat conduction, fluid flow, and biomechanics. He also supervised over 30 M.S. and Ph.D. theses, shaping the next generation of engineers. In parallel, Dr. Kojic played a key role in industry, particularly with the Automobile Factory in Kragujevac, where he developed the general-purpose finite element code PAK, which has been widely used for solid and fluid analysis. His work at ADINA R&D in the U.S. further demonstrated his expertise, where he contributed to the integration of stress analysis for plasticity and thermo-plasticity into the ADINA software suite.

Skills 🛠️

Dr. Milos Kojic possesses a diverse and advanced skill set spanning multiple disciplines within mechanical engineering, computational mechanics, and bioengineering. He is an expert in Finite Element Method (FEM), having pioneered its application in nonlinear structural analysis, heat transfer, and fluid mechanics. His work extends to Discrete Particle Methods (DPM), which are essential for modeling complex material behaviors. Dr. Kojic is also highly proficient in software development, having led the creation of the general-purpose PAK finite element code, which has been widely used in both academic and industrial settings. His deep understanding of elasticity and plasticity allows him to address complex material deformation problems, while his expertise in biomechanics has driven innovation in computational models for bioengineering. Additionally, his knowledge of coupled problems—where mechanical, thermal, and fluid dynamics are interconnected—further highlights his ability to tackle multifaceted engineering challenges. Dr. Kojic’s combination of theoretical insight and practical application makes him a leading figure in computational mechanics and bioengineering.

🏆 Awards & Honors:

Dr. Milos Kojic has been recognized with numerous awards and honors throughout his distinguished career. As an undergraduate, he received a scholarship for his B.S. in Mechanical Engineering and graduated as the top student in his class at the University of Kragujevac, earning the university’s prestigious Award for Outstanding Performance. During his Ph.D. studies at Rice University, he was awarded a Fulbright Foundation scholarship and an assistantship, reflecting his academic excellence. In 1983, he secured a research grant as the principal investigator of a Yugoslav-American project in nonlinear finite element analysis in collaboration with MIT. Dr. Kojic has also been honored with special awards for his research contributions to the automobile industry and for his teaching and research efforts at the University of Kragujevac, where he received accolades such as the Award for Contribution in Teaching and Research in 1988. His contributions to the region’s industrial development were recognized by the Chamber of Industry of Kragujevac in 1992, and he was awarded the Diploma of the City of Kragujevac in 1993 for his role in advancing the city and its university. Among his most notable accolades, Dr. Kojic was awarded the Serbian Engineering Society Gold Medal in 2001 and the St. Sava Award for Life Achievements in 2020, celebrating his lifelong contributions to mechanical engineering, computational mechanics, and the development of the University of Kragujevac. His career-long commitment to academic and industrial development has left an indelible mark on both Serbia and the global scientific community.

Research Focus 🔬

Dr. Milos Kojic’s research focus centers on advancing computational methods and their applications in mechanical engineering, bioengineering, and interdisciplinary fields. A pioneer in finite element methods (FEM) and discrete particle methods, he has developed innovative software solutions for nonlinear structural analysis, inelastic material deformation, and coupled problems. His work encompasses elasticity, plasticity, and biomechanics, addressing complex issues like fluid-structure interaction and stress analysis in porous media. Dr. Kojic’s research also extends into bioengineering, where he has made significant strides in computational modeling of biological systems. His multidisciplinary approach integrates traditional mechanical engineering with cutting-edge bioengineering techniques, contributing to both theoretical developments and practical applications in fields such as nanomedicine and biomechanical analysis. Through his extensive research and software development, Dr. Kojic continues to push the boundaries of computational mechanics and bioengineering.

Conclusion:

Dr. Milos Kojic is an outstanding candidate for the Research for Research Excellence Award. His pioneering work in computational mechanics, finite element analysis, and biomechanics has made lasting contributions to both academia and industry. His leadership in the development of software tools like PAK, and his extensive mentorship of the next generation of researchers, exemplifies his commitment to advancing scientific research. Although there is room to explore more contemporary research collaborations, his lifetime achievements, broad expertise, and substantial impact make him an exemplary candidate for the award.

📖Publications :