Boris Goldengorin | Computer Science | Best Researcher Award

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Prof. Boris Goldengorin | Computer Science | Best Researcher Award

Optimal Management of Tools in Computer Science at Ohio University, United States

Prof. Boris Goldengorin is a globally recognized expert in combinatorial optimization, applied mathematics, and operations research, with a career spanning over five decades. Holding multiple PhDs and a Doctor of Science, he pioneered groundbreaking data correcting algorithms that revolutionized the solving of complex optimization problems such as the Quadratic Cost Partition, Max-Cut, and Traveling Salesman Problems. With over 100 publications in leading international journals and numerous books and monographs, his research has significantly advanced quantitative logistics, supply chain management, and industrial engineering. His algorithms have consistently outperformed global benchmarks, holding world records in solving large-scale combinatorial problems. Prof. Goldengorin has also served as an associate editor for several prestigious journals and has mentored generations of top-performing researchers and students. Honored internationally for his scientific contributions, he continues to influence both theoretical research and practical applications across disciplines, making him a leading figure in modern combinatorial optimization and applied mathematics.

Professional Profile

Education

Prof. Boris Goldengorin possesses an extensive and diverse educational background, reflecting his deep expertise across engineering, applied mathematics, and optimization. He earned his first MSc in Electrical Engineering from Ryazan Radio-Engineering Institute, Russia, in 1967, followed by a second MSc in Applied Mathematics from the Moscow Institute of Electronics and Mathematics in 1973. He completed his PhD in Engineering Sciences at the prestigious VNIINMASH, part of the USSR Ministry of Standardization, in 1975. Further demonstrating his commitment to advanced research, he earned a Doctor of Science (ScD) in Engineering Sciences from the Institute for System Analysis at the USSR Academy of Sciences in 1989. His academic journey continued internationally, obtaining a PhD in Combinatorial Optimization from the University of Groningen, The Netherlands, in 200

Professional Experience

Prof. Boris Goldengorin has built a distinguished career as a researcher, professor, and global leader in combinatorial optimization and operations research. He has held prominent academic and research positions at top institutions, including the University of Groningen (Netherlands), Ohio University (USA), and Khmelnitsky National University (Ukraine), contributing extensively to the fields of mathematical programming, quantitative logistics, and industrial engineering. His pioneering work on data correcting algorithms has shaped modern approaches to solving large-scale optimization problems. Prof. Goldengorin also serves as an associate editor for leading journals such as the Journal of Global Optimization, Journal of Combinatorial Optimization, and Journal of Computational and Applied Mathematics, showcasing his influence in global scientific discourse. Alongside his research, he has mentored generations of students, many of whom have become world-class researchers. His career reflects a rare blend of theoretical innovation, practical application, and global academic leadership, making him a pivotal figure in applied mathematics and operations research.

Research Interest

Prof. Boris Goldengorin’s research interests lie at the intersection of combinatorial optimization, operations research, applied mathematics, and quantitative logistics, where he has made pioneering contributions for over five decades. His primary focus is on developing data correcting algorithms (DCA) and tolerance-based approaches, which have significantly advanced the efficient solving of large-scale optimization problems. His work spans supply chain management, industrial engineering, network analysis, and scheduling problems, with a particular emphasis on benchmark instances such as the Quadratic Cost Partition Problem, Max-Cut Problem, Traveling Salesman Problem, and Simple Plant Location Problem. Beyond classical optimization, Prof. Goldengorin explores the mathematical foundations of algorithmic efficiency and robustness, contributing to big data analysis, game theory, and image processing. His research combines theoretical rigor with computational innovation, enabling faster and more accurate solutions to some of the most computationally challenging problems across disciplines, ensuring long-term impact on both academia and industry applications.

Awards and Honors

Prof. Boris Goldengorin has received numerous awards and honors throughout his illustrious career, recognizing his extraordinary contributions to combinatorial optimization, applied mathematics, and operations research. In 2015, he was named C. Paul Stocker Honorary Professor in Industrial and Systems Engineering at Ohio University, USA. In 2013, the United States Citizenship and Immigration Services (USCIS) granted him Honorable Recognition as an Alien with Extraordinary Ability in Science, Technology, and Education. In 2008, he was recognized as the Best Scientist in Applied Mathematics and Informatics by the Municipality of Khmelnitsky Region, Ukraine. His contributions were further acknowledged in 2005 when Khmelnitsky National University awarded him an Honorary Doctorate in Applied Mathematics and Computer Technologies. Earlier, in 2003, he was named a Fellow in Quantitative Logistics by the Royal Netherlands Academy of Arts and Sciences. These prestigious honors reflect Prof. Goldengorin’s global impact and pioneering role in advancing applied mathematics and optimization research.

Research Skills

Prof. Boris Goldengorin possesses exceptional research skills that span theoretical development, algorithm design, computational experimentation, and interdisciplinary application. His ability to formulate complex combinatorial optimization problems, develop innovative algorithms such as Data Correcting Algorithms (DCA), and rigorously validate their performance through extensive computational benchmarking sets him apart as a world-class researcher. His expertise includes algorithmic design for large-scale optimization problems, quantitative logistics modeling, and supply chain optimization, showcasing his ability to translate mathematical theory into practical solutions. Prof. Goldengorin also excels in analyzing computational complexity, ensuring his algorithms not only produce optimal solutions but do so with unmatched speed and efficiency, often outperforming the leading methods globally. His collaborative research style, combining mentorship, teamwork, and interdisciplinary thinking, has produced high-impact publications across applied mathematics, operations research, game theory, and industrial engineering, making him a highly versatile and innovative researcher with profound analytical and computational skills.

Conclusion

Dr. Boris Goldengorin is highly suitable for the Best Researcher Award.

His exceptional track record in combinatorial optimization, algorithmic innovations, world-record computational achievements, and long-term research leadership position him as a top contender for such a prestigious award.

His global impact, cross-disciplinary contributions, and ability to outperform top research teams in algorithmic efficiency make him a standout figure in applied mathematics, optimization, and industrial engineering.

Publications Top Noted

  • Proceedings of the 11th International Conference on Integer Programming and Combinatorial Optimization
    M. Jünger, V. Kaibel
    Springer-Verlag
    2005 — 233 citations

  • Branch and peg algorithms for the simple plant location problem
    B. Goldengorin, D. Ghosh, G. Sierksma
    Computers & Operations Research 30 (7), 967-981
    2003 — 112 citations

  • The data-correcting algorithm for the minimization of supermodular functions
    B. Goldengorin, G. Sierksma, G.A. Tijssen, M. Tso
    Management Science 45 (11), 1539-1551
    1999 — 76 citations

  • Improvements to MCS algorithm for the maximum clique problem
    M. Batsyn, B. Goldengorin, E. Maslov, P.M. Pardalos
    Journal of Combinatorial Optimization 27, 397-416
    2014 — 65 citations

  • Network approach for the Russian stock market
    A. Vizgunov, B. Goldengorin, V. Kalyagin, A. Koldanov, P. Koldanov, etc.
    Computational Management Science 11, 45-55
    2014 — 65 citations

  • A hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problem
    E. Ahmadi, B. Goldengorin, G.A. Süer, H. Mosadegh
    Applied Soft Computing 65, 214-229
    2018 — 60 citations

  • Tolerance-based branch and bound algorithms for the ATSP
    M. Turkensteen, D. Ghosh, B. Goldengorin, G. Sierksma
    European Journal of Operational Research 189 (3), 775-788
    2008 — 54 citations

  • Lower tolerance-based branch and bound algorithms for the ATSP
    R. Germs, B. Goldengorin, M. Turkensteen
    Computers & Operations Research 39 (2), 291-298
    2012 — 47 citations

  • Tolerances applied in combinatorial optimization
    B. Goldengorin, G. Jäger, P. Molitor
    Journal of Computational Science 2 (9), 716-734
    2006 — 47 citations

  • Cell formation in industrial engineering: Theory, Algorithms and Experiments
    B. Goldengorin, D. Krushinsky, P.M. Pardalos
    Springer
    2013 — 45 citations

  • Solving the simple plant location problem using a data correcting approach
    B. Goldengorin, G.A. Tijssen, D. Ghosh, G. Sierksma
    Journal of Global Optimization 25, 377-406
    2003 — 38 citations

  • Requirements of standards: optimization models and algorithms
    B. Goldengorin
    (No specific journal listed)
    1995 — 35 citations

  • Worst case analysis of max-regret, greedy, and other heuristics for multidimensional assignment and traveling salesman problems
    G. Gutin, B. Goldengorin, H.J.
    Journal of Heuristics, 169-181
    2008 — 34 citations

  • Complexity evaluation of benchmark instances for the p-median problem
    B. Goldengorin, D. Krushinsky
    Mathematical and Computer Modelling 53 (9-10), 1719-1736
    2011 — 32 citations

  • Flexible PMP approach for large-size cell formation
    B. Goldengorin, D. Krushinsky, J. Slomp
    Operations Research 60 (5), 1157-1166
    2012 — 31 citations

Fengyu Liu | Computer Science | Best Researcher Award

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Dr. Fengyu Liu | Computer Science | Best Researcher Award

PhD candidate at Southeast University, China

Fengyu Liu is a dedicated researcher specializing in deep learning, integrated navigation, intelligent unmanned systems, multi-sensor fusion, and SLAM (Simultaneous Localization and Mapping). He has authored 10 academic papers, including 5 SCI-indexed Q1 journal articles, and has contributed significantly to the fields of robotics and sensor technology. With 5 domestic invention patents and 1 PCT patent, his work demonstrates a strong focus on innovation. He has received numerous awards, including the National Scholarship and the Southeast University ‘Zhishan’ Scholarship, and has won four national and provincial-level first prizes in student competitions. He actively participates in academic conferences and serves as a reviewer for IEEE TIM, IEEE Sensor Journal, and MST journals. His research contributions and leadership in the academic community make him a promising figure in the field of intelligent navigation and robotics.

Professional Profile

Education

Fengyu Liu earned his B.S. degree in Electronic Science and Technology from the School of Instrument and Electronics, North University of China, in 2020. Currently, he is pursuing a Ph.D. in Instrument Science and Technology at the School of Instrument Science and Engineering, Southeast University, Nanjing, China. His doctoral research focuses on deep learning-driven navigation, SLAM, and multi-sensor fusion for intelligent unmanned systems. Throughout his academic journey, he has been recognized for his outstanding performance, receiving prestigious scholarships and awards for academic excellence and research contributions.

Professional Experience

During his undergraduate studies, Fengyu Liu served as the Chair of the Embedded Laboratory at the Innovation Elite Research Institute, where he led multiple student research projects. He has been actively involved in presenting at international conferences, including the 2023 International Conference on Robotics, Control, and Vision Engineering (Tokyo) and the China-Russia “Navigation and Motion Control” Youth Forum (2024, Nanjing). His research findings have been published in top-tier journals, and he has contributed as a reviewer for leading IEEE journals. His expertise in SLAM, sensor fusion, and AI-driven navigation technologies has led to patents and real-world applications, making him a key contributor to the advancement of autonomous systems and intelligent robotics.

Research Interests

Fengyu Liu’s research focuses on deep learning, integrated navigation, intelligent unmanned systems, multi-sensor fusion, and simultaneous localization and mapping (SLAM). His work explores advanced sensor fusion techniques, including the integration of LiDAR, cameras, inertial measurement units (IMUs), and deep learning models to enhance navigation accuracy and autonomy in complex environments. He is particularly interested in developing robust localization algorithms for dynamic and unstructured environments, with applications in robotics, autonomous vehicles, and aerospace navigation. His contributions to AI-driven SLAM and vision-based perception systems aim to improve real-time mapping, object recognition, and motion estimation for next-generation autonomous systems.

Awards and Honors

Fengyu Liu has received multiple prestigious awards, including the National Scholarship and the Southeast University ‘Zhishan’ Scholarship, recognizing his academic excellence. He has won four first prizes at national and provincial-level university student competitions, demonstrating his problem-solving skills and technical expertise. His research has also been recognized at academic conferences, earning him the Outstanding Paper Award at the 2022 Science and Technology Workers Seminar of the Chinese Society of Inertial Technology. His participation in international research forums, such as the China-Russia “Navigation and Motion Control” Youth Forum (2024, Nanjing), further highlights his growing impact in the field.

Research Skills

Fengyu Liu possesses a diverse skill set in deep learning, computer vision, and multi-sensor data fusion, particularly for robotics and autonomous navigation. He is proficient in developing AI-based SLAM algorithms, sensor calibration techniques, and real-time embedded system implementations. His expertise extends to software tools and programming languages, including Python, MATLAB, C++, TensorFlow, and PyTorch, which he utilizes for machine learning and signal processing applications. He has hands-on experience with robotic perception systems, LiDAR-based mapping, and inertial navigation technologies, contributing to multiple high-impact research projects. Additionally, his role as a peer reviewer for IEEE TIM, IEEE Sensor Journal, and MST journals reflects his strong analytical and critical evaluation skills in cutting-edge research.

Conclusion

Fengyu Liu is a highly promising young researcher with strong academic contributions, patents, and international recognition. His research in SLAM, deep learning, and multi-sensor fusion aligns with cutting-edge advancements in robotics and AI. His leadership roles, awards, and editorial responsibilities further strengthen his profile.

For the Best Researcher Award, he is a strong candidate, but additional international collaborations, funded research projects, and industry partnerships could further enhance his competitiveness for top-tier global research awards.

Publications Top Noted

  • Confidence Factor Based Robust Localization Algorithm with Visual-Inertial-LiDAR Fusion in Underground Space

  • LiDAR-Aided Visual-Inertial Odometry Using Line and Plane Features for Ground Vehicles

    • Authors: Jianfeng Wu, Xianghong Cheng, Fengyu Liu, Xingbang Tang, Wengdong Gu
    • Year: 2025
    • DOI: 10.1109/TVT.2025.3527472

  • Spatial Feature Recognition and Layout Method Based on Improved CenterNet and LSTM Frameworks

  • Transformer-Based Local-to-Global LiDAR-Camera Targetless Calibration With Multiple Constraints

  • Spacecraft-DS: A Spacecraft Dataset for Key Components Detection and Segmentation via Hardware-in-the-Loop Capture

  • A Visual SLAM Method Assisted by IMU and Deep Learning in Indoor Dynamic Blurred Scenes

  • A Spatial Layout Method Based on Feature Encoding and GA-BiLSTM

  • Combination of Iterated Cubature Kalman Filter and Neural Networks for GPS/INS During GPS Outages

    • Authors: Fengyu Liu, Xiaohong Sun, Yufeng Xiong, Huang Haoqian, Xiao-ting Guo, Yu Zhang, Chong Shen
    • Year: 2019
    • DOI: 10.1063/1.5094559

Dengtian Yang | Computer Science | Best Researcher Award

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Mr. Dengtian Yang | Computer Science | Best Researcher Award

Student at Institute of Microelectronics of the Chinese Academy of Sciences, China

Yang Dengtian is a promising researcher in the field of Circuit and System, currently pursuing his Ph.D. at the Institute of Microelectronics of the Chinese Academy of Sciences. His research interests focus on hardware-software co-optimization, object detection, and hardware acceleration, with key contributions in developing post-processing accelerators for object detection and improving micro-architecture design for GPGPU. Yang’s project experience spans from UAV object detection to the design of System on Chip (SoC) and the deployment of deep learning models on specialized hardware like NVDLA IP. His dedication to advancing technology is reflected in his published works in renowned journals. Yang is a proactive learner, often sharing his findings on blogs, contributing to the academic community’s growth. His work is poised to have a significant impact in fields such as artificial intelligence, hardware design, and computer vision.

Professional Profile 

Education

Yang Dengtian began his academic journey at Xi’an Jiaotong University, where he earned his Bachelor’s degree in Electronic Science and Technology in 2020. His strong foundational knowledge in electronics laid the groundwork for his current research. In 2020, he began his Ph.D. at the Institute of Microelectronics of the Chinese Academy of Sciences, specializing in Circuit and System. His doctoral research has primarily focused on hardware-software co-optimization and advanced object detection systems, areas that combine his deep understanding of both electronics and cutting-edge computing techniques. Yang’s education has been integral in shaping his research pursuits, allowing him to contribute valuable insights into hardware acceleration and the optimization of machine learning systems. His academic journey is ongoing, with an expected completion of his Ph.D. in 2025.

Professional Experience

Yang has worked on several innovative projects throughout his academic career. His recent project, “Learn and Improve Vortex GPGPU,” focuses on understanding GPGPU micro-architecture design and developing improvements for performance optimization. Another notable project was the “Post-Processing Accelerator for Object Detection,” where he investigated hardware-software co-optimization methods, contributing to the development of a unified accelerator system for object detection. In 2023, Yang worked on the “SoC Building and Yolox-Nano Network Deployment Based on NVDLA IP,” where he built an SoC with NVDLA IP and deployed a Yolox-Nano model on a specialized hardware platform. Yang has also worked on solutions to reduce off-chip memory accesses for CNN inference and deployed deep learning models using Vitis-AI. These experiences, along with his publications in renowned journals, highlight his advanced technical expertise and problem-solving abilities in cutting-edge electronics and AI research.

Research Interest

Yang Dengtian’s primary research interest lies in the intersection of Circuit and System design, hardware-software co-optimization, and artificial intelligence (AI). His work focuses on developing hardware accelerators for deep learning applications, particularly in object detection and micro-architecture optimization. He is passionate about creating more efficient systems for processing large-scale data, especially in environments that require real-time processing, such as unmanned aerial vehicles (UAVs) and embedded systems. Yang’s research includes developing GPGPU micro-architectures, improving System on Chip (SoC) designs, and enhancing the deployment of deep learning models on specialized hardware, such as NVDLA IP. His research aims to bridge the gap between hardware capabilities and software needs, making AI applications more accessible and efficient. He is particularly interested in creating unified frameworks for hardware-software co-design, which could significantly advance machine learning and computer vision technologies.

Awards and Honors

Yang Dengtian’s outstanding contributions to research have been recognized through various accolades. His publication in reputable journals, such as Information and IEICE Transactions on Information and Systems, demonstrates the impact of his work in the field of hardware and software co-optimization. While still early in his career, Yang’s commitment to research excellence has already led to numerous recognitions in his academic community. He has also been acknowledged for his innovative projects in hardware acceleration for AI applications, particularly in the development of post-processing accelerators for object detection. Yang’s work is a testament to his technical expertise and his potential for future awards as his research continues to make significant strides in the fields of electronics, AI, and machine learning. Given his promising trajectory, Yang is likely to receive further honors as his doctoral studies progress and his body of work grows.

Conclusion

Yang Dengtian is undoubtedly a strong contender for the Best Researcher Award due to his innovative approach to research, technical expertise, and significant contributions to the field of hardware-software co-design and optimization. His passion for learning, combined with his publications and project experience, highlights his potential to make substantial advancements in his area of study. However, expanding his collaborations and enhancing the practical impact of his research could further solidify his status as a leading researcher in the field.

Recommendation: Yang Dengtian is highly deserving of the Best Researcher Award, with his strengths outweighing areas for improvement. His future contributions are expected to have a lasting impact in the fields of object detection, hardware acceleration, and micro-architecture design.

Publications Top Noted

  • Title: Nano-carriers of combination tumor physical stimuli-responsive therapies
    Authors: W Jin, C Dong, D Yang, R Zhang, T Jiang, D Wu
    Journal: Current Drug Delivery
    Volume & Issue: 17 (7), 577-587
    Year: 2020
    Cited by: 7
  • Title: Object Detection Post Processing Accelerator Based on Co-Design of Hardware and Software
    Authors: D Yang, L Chen, X Hao, Y Zhang
    Journal: Information
    Volume & Issue: 16 (1), 63
    Year: 2025
    Cited by: Not yet cited (as of 2025)

 

Siliang Ma | Computer Science | Best Researcher Award

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Dr. Siliang Ma | Computer Science | Best Researcher Award

Senior Algorithm Engineer at School of Computer Science and Engineering, South China University of Technology, China

Dr. Siliang Ma, a Ph.D. candidate at South China University of Technology, is an accomplished researcher specializing in computer science with a focus on image processing and machine learning. With an excellent academic record, including a bachelor’s degree from South China Agricultural University (GPA: 3.99/5), Dr. Ma has made significant contributions to cutting-edge research. His works, published in esteemed journals such as Acta Automatica Sinica and Image and Vision Computing, address topics like calligraphy character recognition, multilingual scene text spotting, and efficient bounding box regression through novel loss functions like MPDIoU and FPDIoU. A skilled programmer proficient in Python, Java, and C#, he has developed robust image processing algorithms and software applications. Dr. Ma also contributes as a reviewer for leading conferences like ICRA and ICASSP, reflecting his commitment to advancing the research community. His innovative and impactful work positions him as a rising talent in computational science.

Professional Profile 

Education

Dr. Siliang Ma has a strong educational background in computer science and engineering. He is currently pursuing a Ph.D. at the South China University of Technology, where he has maintained an excellent GPA of 86.33/100. His doctoral research focuses on cutting-edge topics in image processing, machine learning, and computational algorithms, demonstrating both theoretical depth and practical relevance. Prior to this, Dr. Ma earned his bachelor’s degree from South China Agricultural University, graduating with a remarkable GPA of 3.99/5. His undergraduate studies in mathematics and informatics laid a solid foundation for his advanced research pursuits, equipping him with the analytical and technical skills essential for solving complex computational problems. Through rigorous academic training and dedication, Dr. Ma has excelled in his education, which is further reflected in his extensive publications in high-impact journals and his active engagement in academic conferences and peer reviews.

Professional Experience

Dr. Siliang Ma has gained valuable professional experience through diverse roles in research and industry, complementing his academic achievements. He interned as a Data Analyst at the China Construction Bank Guangdong Branch Technology Center, where he conducted financial data analysis using PostgreSQL, mastering database operations and complex linked table queries. As a Quality Engineer at the China Mobile Guangdong Branch Business Support Center, he developed a JavaWeb-based minimum feature set for user registration, login, and management, and implemented automated quality testing workflows using Jenkins. These roles allowed Dr. Ma to hone his skills in software development, data analysis, and quality assurance, showcasing his ability to translate theoretical knowledge into practical applications. Additionally, his expertise in programming and image processing has led to impactful contributions in academia, particularly in algorithm development. This blend of industrial and research experience positions Dr. Ma as a versatile professional in computer science and engineering.

Research Interest

Dr. Siliang Ma’s research interests lie at the intersection of computer vision, machine learning, and image processing. He is particularly focused on developing innovative algorithms and techniques for efficient and accurate object detection, scene text recognition, and character recognition. His work explores advanced loss functions, such as MPDIoU and FPDIoU, to optimize bounding box regression for both traditional and rotated object detection. Additionally, Dr. Ma has a keen interest in multilingual scene text spotting, where he leverages character-level features and benchmarks to improve the accuracy of text recognition across diverse languages. His research extends to robust graph learning and hypergraph-enhanced self-supervised models for social recommendation systems, showcasing his ability to address complex, real-world challenges. Through his work, Dr. Ma aims to bridge theoretical advancements with practical applications, contributing to the broader fields of artificial intelligence, data analysis, and computational optimization.

Award and Honor

Dr. Siliang Ma has been recognized for his academic and research excellence through various accolades and contributions. As a Ph.D. candidate at South China University of Technology, his consistent high performance, reflected in his impressive GPA, underscores his dedication to academic rigor. Although specific awards or honors are not explicitly listed in his profile, his role as a reviewer for prestigious conferences such as ICRA and ICASSP highlights his esteemed position within the research community. Dr. Ma’s impactful publications in top-tier journals and conferences, including Acta Automatica Sinica and Image and Vision Computing, further demonstrate the high regard in which his work is held. His innovative contributions to image processing and machine learning have earned him recognition as a rising talent in his field. These achievements reflect Dr. Ma’s commitment to advancing computational science and his growing influence in academic and professional circles.

Conclusion

Siliang Ma is a strong candidate for the Best Researcher Award due to his impressive academic record, significant publications, and technical expertise. His contributions to advanced image processing algorithms and innovative loss functions for object detection demonstrate technical ingenuity and research excellence. To further strengthen his profile, he could expand his research impact through interdisciplinary work, mentorship roles, and greater industry engagement.

Publications Top Noted

  • Title: FPDIoU Loss: A loss function for efficient bounding box regression of rotated object detection
    Authors: Siliang Ma, Yong Xu
    Year: 2024
    Citation: Ma, S., & Xu, Y. (2024). FPDIoU Loss: A loss function for efficient bounding box regression of rotated object detection. Image and Vision Computing. https://doi.org/10.1016/j.imavis.2024.105381
  • Title: Rethinking Multilingual Scene Text Spotting: A Novel Benchmark and a Character-Level Feature Based Approach
    Authors: Siliang Ma, Yong Xu
    Year: 2024
    Citation: Ma, S., & Xu, Y. (2024). Rethinking Multilingual Scene Text Spotting: A Novel Benchmark and a Character-Level Feature Based Approach. American Journal of Computer Science and Technology. https://doi.org/10.11648/j.ajcst.20240703.12

Nunzio Alberto Borghese | Computer Science | Best Researcher Award

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Prof. Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Full professor at Università degli Studi di MIlano, Italy

Professor N. Alberto Borghese is a renowned researcher in computational intelligence and its application to real-world problems. He graduated magna cum laude in Electrical Engineering from Politecnico di Milan and has held significant academic positions, including Full Professor at the University of Milan. His research focuses on innovative methods such as multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with particular emphasis on limited processing time. He has made notable contributions to e-Health and robotics, integrating AI, service robots, virtual communities, and smart objects to improve healthcare and welfare systems. With over 90 journal papers, 140+ conference papers, and 16 international patents, he has a strong academic and industrial impact. He has led several high-profile projects funded by the European Commission and Italian government, including REWIRE, MOVECARE, and AIRCA. His work continues to advance the intersection of AI, robotics, and healthcare, addressing critical societal needs.

Professional Profile 

Education

Professor N. Alberto Borghese received his education in Electrical Engineering, graduating magna cum laude in 1986 from Politecnico di Milan, one of Italy’s leading institutions. This strong academic foundation laid the groundwork for his extensive research career. His academic journey furthered through his role as a tenured researcher at the National Research Council (CNR) from 1987 to 2000, where he began developing his expertise in computational intelligence. This led to his appointment as an Associate and later Full Professor at the Department of Computer Science, University of Milan (UNIMI). At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he has mentored students and led cutting-edge research projects. Professor Borghese’s education and professional development have been marked by continuous innovation, research leadership, and a commitment to applying his knowledge to real-world challenges, particularly in e-Health, robotics, and AI.

Professional Experience

Professor N. Alberto Borghese has had a distinguished professional career, beginning as a tenured researcher at the National Research Council (CNR) from 1987 to 2000. During this time, he built a strong foundation in computational intelligence. He then transitioned to the University of Milan (UNIMI), where he became an Associate Professor and later a Full Professor in the Department of Computer Science. At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he leads innovative research projects focused on AI, robotics, and e-Health. Throughout his career, he has contributed to over 90 journal papers, more than 140 conference papers, and holds 16 international patents. Professor Borghese has led several major research projects funded by the European Commission, including REWIRE, MOVECARE, and FITREHAB, and has been involved in multiple Italian government-funded initiatives. His work bridges academia and industry, addressing pressing societal needs in healthcare and welfare through technological advancements.

Research Interest

Professor N. Alberto Borghese’s research interests lie primarily in the field of computational intelligence, focusing on the development and application of advanced algorithms to solve real-world problems. He specializes in multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with an emphasis on optimizing solutions for limited processing time. His work extends to the integration of Artificial Intelligence (AI) and robotics, particularly in the domains of e-Health and e-Welfare. Professor Borghese has pioneered the use of service robots, virtual communities, and smart objects, creating innovative platforms that enhance healthcare and welfare systems. His research also explores the intersection of AI with healthcare technologies such as exer-games, aiming to improve accessibility and promote well-being. Additionally, he has a strong focus on interdisciplinary collaboration, leading several European and Italian research projects that combine AI, robotics, and human-centered design to address societal challenges in health, aging, and rehabilitation.

Award and Honor

Professor N. Alberto Borghese has received numerous awards and honors throughout his distinguished academic and research career. His recognition stems from his innovative contributions to computational intelligence, AI, and robotics, particularly in the fields of e-Health and e-Welfare. With over 90 journal papers and 140+ conference papers, his research has garnered widespread acclaim, reflected in his h-index of 42. He has also been honored for his extensive intellectual property contributions, holding 16 international patents. His leadership in research has been recognized through his involvement in high-profile projects funded by the European Commission and Italian government, such as REWIRE (FP7), MOVECARE (H2020), and AIRCA (2023-2025). These honors not only underline his academic excellence but also highlight his impact on advancing technology in healthcare and welfare systems. His continued success in securing major funding and his role in shaping interdisciplinary research make him a highly respected figure in his field.

Conclusion

Based on his exceptional academic qualifications, pioneering research in computational intelligence and e-Health, leadership in high-profile projects, and impressive publication and patent record, N. Alberto Borghese is a highly suitable candidate for the Best Researcher Award. Addressing minor improvements in public engagement and cross-disciplinary impact could further strengthen his candidacy. Nonetheless, his proven expertise and contributions make him a deserving nominee.

Publications Top Noted

  • Kinematic determinants of human locomotion
    • Authors: N. Alberto Borghese, L. Bianchi, F. Lacquaniti
    • Year: 1996
    • Citations: 553
  • Different brain correlates for watching real and virtual hand actions
    • Authors: D. Perani, F. Fazio, N. A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, …
    • Year: 2001
    • Citations: 402
  • Autocalibration of MEMS accelerometers
    • Authors: I. Frosio, F. Pedersini, N. A. Borghese
    • Year: 2008
    • Citations: 261
  • Time-varying mechanical behavior of multijointed arm in man
    • Authors: F. Lacquaniti, M. Carrozzo, N. A. Borghese
    • Year: 1993
    • Citations: 202
  • Internal models of limb geometry in the control of hand compliance
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1992
    • Citations: 197
  • Reading the reading brain: a new meta-analysis of functional imaging data on reading
    • Authors: I. Cattinelli, N. A. Borghese, M. Gallucci, E. Paulesu
    • Year: 2013
    • Citations: 188
  • A functional-anatomical model for lipreading
    • Authors: E. Paulesu, D. Perani, V. Blasi, G. Silani, N. A. Borghese, U. De Giovanni, …
    • Year: 2003
    • Citations: 163
  • The role of vision in tuning anticipatory motor responses of the limbs
    • Authors: F. Lacquaniti
    • Year: 1993
    • Citations: 151
  • Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames
    • Authors: M. Pirovano, E. Surer, R. Mainetti, P. L. Lanzi, N. A. Borghese
    • Year: 2016
    • Citations: 148
  • Self-adaptive games for rehabilitation at home
    • Authors: M. Pirovano, R. Mainetti, G. Baud-Bovy, P. L. Lanzi, N. A. Borghese
    • Year: 2012
    • Citations: 146
  • Transient reversal of the stretch reflex in human arm muscles
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1991
    • Citations: 144
  • Computational intelligence and game design for effective at-home stroke rehabilitation
    • Authors: N. A. Borghese, M. Pirovano, P. L. Lanzi, S. Wüest, E. D. de Bruin
    • Year: 2013
    • Citations: 139
  • Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity
    • Authors: R. Oberti, M. Marchi, P. Tirelli, A. Calcante, M. Iriti, A. N. Borghese
    • Year: 2014
    • Citations: 128
  • Usability and effects of an exergame-based balance training program
    • Authors: S. Wüest, N. A. Borghese, M. Pirovano, R. Mainetti, R. van de Langenberg, …
    • Year: 2014
    • Citations: 121
  • Pattern recognition in 3D automatic human motion analysis
    • Authors: G. Ferrigno, N. A. Borghese, A. Pedotti
    • Year: 1990
    • Citations: 121

Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

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Mrs. Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Assistant Professor at Dr Subhash University, India

Khyati Bhupta is a highly motivated and accomplished professor specializing in the field of pharmacy. She is dedicated to both teaching and research, with a passion for fostering student development using modern teaching methods and advanced pedagogy. Her work is defined by her dedication to innovation and academic excellence. Her experience and skills, particularly in the pharmaceutical sector, make her a valuable contributor to both academia and the industry.

Professional profile

Education 📚

Khyati holds a PhD in Pharmacy, which she earned in May 2013 from Dr. Subhash University, Gujarat. Prior to her PhD, she completed her Master’s in Pharmacy with a specialization in Quality Assurance from Gujarat Technological University in 2009, and her Bachelor’s in Pharmacy from Sardar Patel University in 2007. Her academic journey reflects a consistent focus on pharmaceutical sciences, with an emphasis on quality and research.

Professional Experience🎓

Over the years, Khyati has built extensive experience as a professor in pharmacy, contributing significantly to both teaching and research. She is skilled in handling pharmaceutical instruments and software, which has been vital in her research and practical work. Her expertise in communication and documentation further enhances her teaching capabilities, making her an effective educator who fosters learning through modern approaches and methodologies.

Research Interest🎓

Khyati’s research primarily focuses on pharmaceutical sciences, with significant work on benzothiazole derivatives, exploring their potential as antidiabetic and antiviral agents. She has published multiple papers on these topics in renowned journals such as MDPI and the Annals of the Romanian Society for Cell Biology. Her work also involves method development for pharmaceutical analysis, including titrimetric methods and RP-HPLC method development for drug estimation, reflecting her deep engagement in pharmaceutical research and innovation.

Awards and Honors 🏆

Khyati has received several recognitions for her contributions to research. In August 2022, she was granted a patent from the Government of India, demonstrating her innovative contributions to pharmaceutical science. Additionally, she received a grant from the SSIP (Student Startup and Innovation Policy) under the Gujarat Government in October 2023 for her work on a startup project, highlighting her potential in translating research into practical applications.

Publications top noted📜

  • BENZOTHIAZOLE: AS AN ANTIDIABETIC AGENT
    • Authors: Khyati Bhupta
    • Journal: Annals of the Romanian Society for Cell Biology
    • Year: 2021
    • Citations: N/A 📊💊
  • BENZOTHIAZOLE MOIETY AND ITS DERIVATIVES AS ANTIVIRAL AGENTS
    • Authors: Khyati Bhupta
    • Journal: MDPI
    • Year: 2021
    • Citations: N/A 🦠🔬
  • Biological Screening and Structure Activity Relationship of Benzothiazole
    • Authors: Khyati Bhupta
    • Journal: Research Journal of Pharmacy and Technology
    • Year: 2022
    • Citations: N/A 🧪📈
  • Development of Titrimetric Method for Estimation of Furosemide Tablets by Using Mixed Co-Solvency Process
    • Authors: Khyati Bhupta
    • Journal: International Journal of Biology, Pharmacy and Allied Sciences
    • Year: 2022
    • Citations: N/A ⚖️💊
  • RP-HPLC Method Development and Validation for Simultaneous Estimation of Ranitidine Hydrochloride and Domperidone in Combination
    • Authors: Khyati Bhupta
    • Journal: International Journal of Pharmacy, Biology and Allied Science
    • Year: 2023
    • Citations: N/A 📊🔬

Sarra Jebri | Computer Science | Best Researcher Award

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Dr. Sarra Jebri | Computer Science | Best Researcher Award

Assistant professor of National Engineering School of Gabes, Tunisia

Sarra Jebri is an accomplished researcher and educator with a robust background in telecommunications. She earned her PhD from Ecole Nationale d’Ingénieurs de Tunis, specializing in IoT security and privacy, and has a comprehensive educational foundation that includes a National Diploma of Engineering and a Master’s in Instrumentation and Communication. Her professional experience includes significant teaching roles at the National School of Engineers in Gabès, reflecting her expertise in the field. Jebri’s research focuses on critical areas such as security, mutual authentication, and IoT, with several influential publications presented at international conferences. 🌟🌿🔬

Professional profile

Education📚

Sarra Jebri holds a PhD in Telecommunications from Ecole Nationale d’Ingénieurs de Tunis (ENIT) with a focus on Internet of Things (IoT) security and privacy. Her academic journey includes a National Diploma of Engineering in Communications and Networks from Ecole Nationale d’Ingénieurs de Gabès (ENIG), where she studied IPTV services, and a Master’s degree in Instrumentation and Communication from the Faculty of Sciences of Sfax, focusing on information system design. She also has a Bachelor’s Degree in Mathematics. Her diverse educational background underscores her strong foundation in telecommunications and related fields, preparing her well for research excellence.

Professional Experience🏛️

Sarra Jebri has extensive teaching experience in telecommunications, having served as a Contractual Teacher at the National School of Engineers in Gabès from 2020 to 2024 and as a Vacant Teacher from 2014 to 2019. This teaching experience, combined with her practical knowledge in the field, demonstrates her capability in both academic and applied research environments.

Research Interest🌐

Sarra Jebri’s research focuses on security, mutual authentication, privacy, and IoT. Her recent publications include notable works such as “Local Learning-based Collaborative Authentication In Edge-Fog Network” and “Light Automatic Authentication of Data Transmission in 6G/IoT Healthcare System,” presented at prestigious international conferences. Her research contributions are recognized through multiple conference papers, indicating a strong engagement with current challenges in her field.

Certifications🏆

Jebri has obtained several certifications, including Cisco and Huawei networking and security qualifications, and has strong programming skills in C, C++, Java, and Matlab. Her certifications reflect her ongoing commitment to professional development and her ability to apply theoretical knowledge in practical scenarios.

Publications top noted📜

Bechoo Lal | Computer Science | Best Researcher Award

Published on by NESIN Awards

Dr. Bechoo Lal | Computer Science | Best Researcher Award

Associate Professor of KLEF- KL University Vijayawada Campus Andhra Pradesh, India

Dr. Bechoolal 🌟 is an esteemed Associate Professor in Computer Science/Data Science with a passion for inspiring students through a deep understanding of technology and research. With a solid academic foundation that includes a PGP in Data Science from Purdue University and multiple PhDs in Information Systems and Computer Science 🎓, he brings a wealth of expertise to his teaching and research. Dr. Bechoolal has extensive experience in various institutions, from KLEF KL Deemed University to Western College 🏫, and has made significant contributions through his numerous research publications and certifications 🏅. His interests span Machine Learning, Data Science, and programming languages, and he actively engages in projects that explore digital transformation and its societal impacts 💻🔍. Fluent in English and Hindi 🇬🇧🇮🇳, he continues to advance knowledge and inspire the next generation of tech professionals.

Publication profile

Education

Dr. Bechoolal 🎓 is a distinguished academic with a rich educational background in Computer Science and Data Science. He earned a PGP in Data Science from Purdue University 🌟, where he specialized in data regression models and predictive data modeling. Dr. Bechoolal holds multiple PhDs—one in Information Systems from the University of Mumbai and another in Computer Science from SJJT University 🧠. His foundational studies include a Master of Technology in Computer Science from AAI-Deemed University, a Master of Computer Applications from Banaras Hindu University, and an undergraduate degree in Statistics from MG. Kashi Vidyapeeth University 📚. His continuous quest for knowledge is also reflected in his various certifications, including Machine Learning from Stanford University and an IBM Data Science Professional Certificate 🏅.

Academic Qualification

  • 📜 PGP in Data Science (2020-2021) from Purdue University, USA – Specializing in data regression models, predictive data modeling, and accuracy analyzing using machine learning.
  • 📜 PhD in Information System (2015-2019) from the University of Mumbai, India – Research Area: Data Science.
  • 📜 PhD in Computer Science (2011-2015) from SJJT University, India – Research Area: Machine Learning.
  • 📜 Master of Technology (M. Tech) in Computer Science and Engineering (2004-2006) from AAI-Deemed University, Allahabad, India.
  • 📜 Master of Computer Application (MCA) (1995-1998) from Institute of Science, Banaras Hindu University (BHU), India.
  • 📜 Graduation (Statistics-Hons) (1990-1993) from the Department of Mathematics and Statistics, MG Kashi Vidyapeeth University, India.

Data Science Certifications and Training

  • 🎓 Machine Learning, Stanford University, USA (2020)
  • 🎓 IBM Data Science Professional Certificate (2020)
  • 🎓 Data Science and Big Data Analytics (2019), ICT Academy, Govt. of India
  • 🎓 Security Fundamentals, Microsoft Technology Associate (2017)
  • 🎓 Intelligent Multimedia Data Warehouse and Mining (2009), University of Mumbai
  • 🎓 Python Programming (2017), University of Mumbai, India

 

Teaching Interest 

  • 📘 Data Science/Machine Learning
  • 📘 Database 📘 C/C++/Python Programming Languages
  • 📘 Software Engineering

Research Interest

  • 🔍 Machine Learning
  • 🔍 Data Science

Computer Science/Data Science Skills

💻 Machine Learning, Data Visualization, Big Data Analytics

📊 Predictive Modelling: Supervised Learning (Linear and Logistic Regression, Decision Tree, Support Vector Machine (SVM), Naïve Bayes Classifiers), Unsupervised Learning (K-Means clustering, principal components analysis (PCA))

💻 Programming Languages: Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn), SPSS, R-Programming

💻 Operating Systems/Platforms: UNIX/LINUX, WINDOWS, MS-DOS

💻 C/C++, CORE JAVA Programming Languages

💻 DBMS/RDBMS: Oracle, SQL, MySQL, NoSQL

Publication top notes

  • Improving migration forecasting for transitory foreign tourists using an Ensemble DNN-LSTM model
    Authors: Nanjappa, Y., Kumar Nassa, V., Varshney, G., Pandey, S., V Turukmane, A.
    Journal: Entertainment Computing
    Year: 2024
    Citations: 0 📅
  • Using social networking evidence to examine the impact of environmental factors on social followings: An innovative Machine learning method
    Authors: Murthy, S.V.N., Ramesh, P.S., Padmaja, P., Reddy, G.J., Chinthamu, N.
    Journal: Entertainment Computing
    Year: 2024
    Citations: 0 📅
  • Real-Time Convolutional Neural Networks for Emotion and Gender Classification
    Authors: Singh, J., Singh, A., Singh, K.K., Samudre, N., Raperia, H.
    Conference: Procedia Computer Science
    Year: 2024
    Citations: 0 📅
  • Identification of Brain Diseases using Image Classification: A Deep Learning Approach
    Authors: Singh, J., Singh, A., Singh, K.K., Turukmane, A.V., Kumar, A.
    Conference: Procedia Computer Science
    Year: 2024
    Citations: 0 📅
  • Fake News Detection Using Transfer Learning
    Authors: Singh, J., Sahu, D.P., Gupta, T., Lal, B., Turukmane, A.V.
    Conference: Communications in Computer and Information Science
    Year: 2024
    Citations: 0 📅
  • Reliability Evaluation of a Wireless Sensor Network in Terms of Network Delay and Transmission Probability for IoT Applications
    Authors: Mishra, P., Dash, R.K., Panda, D.K., Lal, B., Sujata Gupta, N.
    Journal: Contemporary Mathematics (Singapore)
    Year: 2024
    Citations: 0 📅
  • TRANSFER LEARNING METHOD FOR HANDLING THE INTRUSION DETECTION SYSTEM WITH ZERO ATTACKS USING MACHINE LEARNING AND DEEP LEARNING
    Authors: Upender, T., Lal, B., Nagaraju, R.
    Conference: ACM International Conference Proceeding Series
    Year: 2023
    Citations: 0 📅
  • Monitoring and Sensing of Real-Time Data with Deep Learning Through Micro- and Macro-analysis in Hardware Support Packages
    Authors: Lal, B., Chinthamu, N., Harichandana, B., Sharmaa, A., Kumar, A.R.
    Journal: SN Computer Science
    Year: 2023
    Citations: 0 📅
  • An Efficient QRS Detection and Pre-processing by Wavelet Transform Technique for Classifying Cardiac Arrhythmia
    Authors: Lal, B., Gopagoni, D.R., Barik, B., Kumar, R.D., Lakshmi, T.R.V.
    Journal: International Journal of Intelligent Systems and Applications in Engineering
    Year: 2023
    Citations: 0 📅
  • IOT-BASED Cyber Security Identification Model Through Machine Learning Technique
    Authors: Lal, B., Ravichandran, S., Kavin, R., Bordoloi, D., Ganesh Kumar, R.
    Journal: Measurement: Sensors
    Year: 2023
    Citations: 3 📅📈

Prof Dr. Mehlika Dilek Altıntop | Medicinal Chemistry | Women Researcher Award

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Prof Dr. Mehlika Dilek Altıntop | Medicinal Chemistry | Women Researcher Award

Prof Dr. Anadolu University, Turkey

Dr. Mehlika Dilek Altıntop is a prominent Professor in Pharmaceutical Chemistry at Anadolu University. Her academic journey includes a Bachelor’s from Anadolu University, followed by a Master’s and Ph.D. in Pharmaceutical Chemistry from the same institution. She has served in various academic roles, including Research Assistant, Assistant Professor, and currently as a Professor. Her administrative roles include serving as Associate Director and Quality Coordinator at Anadolu University. Dr. Altıntop has received numerous awards for her research, including the Outstanding Woman Researcher Award and multiple Article Performance Awards. She is actively involved in editorial and guest editing roles in prestigious scientific journals and has supervised numerous master’s and doctoral dissertations in her field.

Professional profile

Scopus

Education 📚

Primary School: İkieylül Elementary School (1991-1996)Secondary School – High School: Eskişehir Anatolian High School (1996-2003)Undergraduate: Anadolu University, Faculty of Pharmacy (2003-2007)Master’s Degree (with Thesis): Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (2007-2009)Doctoral Degree: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (2009-2012)Languages: English (Excellent)

Academic Titles 🎓

Research Assistant: Anadolu University, Faculty of Pharmacy (2010-2012)Research Assistant Doctor: Anadolu University, Faculty of Pharmacy (2012-2014)Assistant Professor Doctor: Anadolu University, Faculty of Pharmacy (2014-2015)Associate Professor Doctor: Anadolu University, Faculty of Pharmacy (2015-2020)Professor Doctor: Anadolu University, Faculty of Pharmacy (2020-Present)Administrative Roles 🏛️Erasmus/Farabi/Mevlana Assistant Coordinator: Anadolu University Faculty of Pharmacy (2013-2014)Associate Director: Anadolu University Graduate School of Health Sciences (2014-2017, 2023)Quality Coordinator: Anadolu University Graduate School of Health Sciences (2022-2023)

Awards and Honors 🏆

Anadolu University Faculty of Pharmacy Championship Award (2007)The Scientific and Technological Research Council of Turkey Graduate Scholarship (2007-2009)Anadolu University Science and Technology Encouragement Award (2014)Anadolu University Gold & Platinum Article Performance Awards (2015)Outstanding Reviewer, European Journal of Medicinal Chemistry (2016)Turkish Pharmacists’ Association Academy of Pharmacy Encouragement Award (2019)ISIF’21 Silver Medal for “Targeted Novel Triazolothiadiazine Derivatives for The Treatment of Lung Cancer” (2021)Award of Outstanding Woman Researcher in Pharmaceutical Chemistry, VIWA 2021

Publication📜

 

Design, Synthesis, and In Vivo Evaluation of a New Series of Indole-Chalcone Hybrids as Analgesic and Anti-Inflammatory Agents
Authors: Baramaki, I., Altıntop, M.D., Arslan, R., Hasan, A., Bektaş Türkmen, N.
Journal: ACS Omega, 2024, 9(10), pp. 12175–12183

Design, Synthesis, and Evaluation of a New Series of 2-Pyrazolines as Potential Antileukemic Agents
Authors: Altıntop, M.D., Cantürk, Z., Özdemir, A.
Journal: ACS Omega, 2023, 8(45), pp. 42867–42877

Design, Synthesis, and Evaluation of a New Series of Hydrazones as Small-Molecule Akt Inhibitors for NSCLC Therapy
Authors: Erdönmez, B., Altıntop, M.D., Akalın Çiftçi, G., Özdemir, A., Ece, A.
Journal: ACS Omega, 2023, 8(22), pp. 20056–20065

A New Series of Hydrazones as Small-Molecule Aldose Reductase Inhibitors
Authors: Altıntop, M.D., Demir, Y., Türkeş, C., Beydemir, Ş., Özdemir, A.
Journal: Archiv der Pharmazie, 2023, 356(4), 2200570

A New Series of Thiazole-Hydrazone Hybrids for Akt-Targeted Therapy of Non-Small Cell Lung Cancer
Authors: Orujova, T., Ece, A., Akalın Çiftçi, G., Özdemir, A., Altıntop, M.D.
Journal: Drug Development Research, 2023, 84(2), pp. 185–199

Synthesis, In Silico and In Vitro Evaluation of New 3,5-Disubstituted-1,2,4-Oxadiazole Derivatives as Carbonic Anhydrase Inhibitors and Cytotoxic Agents
Authors: Kucukoglu, K., Faydali, N., Bul, D., Ozturk, B., Guzel, I.
Journal: Journal of Molecular Structure, 2023, 1276, 134699

Discovery of Small Molecule COX-1 and Akt Inhibitors as Anti-NSCLC Agents Endowed with Anti-Inflammatory Action
Authors: Altıntop, M.D., Akalın Çiftçi, G., Yılmaz Savaş, N., Alataş, Ö., Özdemir, A.
Journal: International Journal of Molecular Sciences, 2023, 24(3), 2648

Microwave-Assisted Synthesis of a Series of 4,5-Dihydro-1H-Pyrazoles Endowed with Selective COX-1 Inhibitory Potency
Authors: Altıntop, M.D., Temel, H.E., Özdemir, A.
Journal: Journal of the Serbian Chemical Society, 2023, 88(4), pp. 355–365

Design, Synthesis, and Biological Evaluation of a New Series of Arylidene Indanones as Small Molecules for Targeted Therapy of Non-Small Cell Lung Carcinoma and Prostate Cancer
Authors: Altıntop, M.D., Özdemir, A., Temel, H.E., Kaplancıklı, Z.A., Akalın Çiftçi, G.
Journal: European Journal of Medicinal Chemistry, 2022, 244, 114851

A New Series of Thiosemicarbazone-Based Anti-Inflammatory Agents Exerting Their Action Through Cyclooxygenase Inhibition
Authors: Altıntop, M.D., Sever, B., Akalın Çiftçi, G., Alataş, Ö., Özdemir, A.
Journal: Archiv der Pharmazie, 2022, 355(9), 2200136

Ahmet Özdemir | Medicinal Chemistry | Best Researcher Award

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Prof Dr. Ahmet Özdemir | Medicinal Chemistry | Best Researcher Award

Prof Dr. Anadolu University, Turkey

Prof Dr. Ahmet Özdemir is a Professor of Pharmaceutical Chemistry at Anadolu University, holding several prestigious academic titles and administrative roles. With a strong educational foundation in pharmacy and pharmaceutical chemistry, they have supervised both master’s and doctoral theses. Their research has garnered numerous awards, including multiple Article Performance Awards and an ISIF’21 Silver Medal for their invention targeting lung cancer treatment. Dr. [Your Name] has authored significant research on synthesizing bioactive compounds, reflecting their expertise in pharmaceutical chemistry and dedication to advancing medicinal science. They are proficient in English and have an extensive international research profile, including ORCID and Scopus Author IDs.

Professional profile

Scopus

Orcid

Education 🎓

Primary School: Salihli Cumhuriyet Elementary School (1978-1983)Secondary School: Salihli 50. Yıl Secondary School (1983-1986)High School: Salihli High School (1986-1989)Undergraduate: Anadolu University, Faculty of Pharmacy (1990-1994)Master’s Degree (with Thesis): Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (1995-1996)Thesis Title: “The studies on the synthesis, structure elucidations and determination of physicochemical parameters of some 2-substituted-1H-phenantro[9,10-d]imidazole compounds”Supervisor: Prof. Dr. İlhan Işıkdağ, 02.09.1996Doctorate Degree: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (1996-2004)Thesis Title: “Synthesis of some 1-[(N,N-disubstituted-thiocarbonylthio)acetyl]-3-(2-thienyl)-5-aryl-2-pyrazoline derivatives and investigation of their antifungal, antibacterial activities”Supervisor: Prof. Dr. Gülhan Turan, 10.05.2004Foreign Languages: English (Intermediate)

Academic Titles 🏅

Research Assistant: Anadolu University, Faculty of Pharmacy (1997-2004)Research Assistant Doctor: Anadolu University, Faculty of Pharmacy (2004-2005)Lecturer: Anadolu University, Faculty of Pharmacy (2005-2007)Assistant Professor Doctor: Anadolu University, Faculty of Pharmacy (2007-2010)Associate Professor Doctor: Anadolu University, Faculty of Pharmacy (2010-2015)Professor Doctor: Anadolu University, Faculty of Pharmacy (2015-present)

Administrative Tasks 🗂️

Associate Director: Anadolu University Yunus Emre Vocational School (2011-2014)Vice Academic Director: Anadolu University Open Education Faculty, Department of Health Administration (2015-present)

Awards 🏆

Anadolu University Article Performance Award (2014)Anadolu University Gold Article Performance Award (2015)Anadolu University Platinum Article Performance Award (2015)Anadolu University Article Performance Award (2016, 2017, 2018, 2020)Anadolu University Academic Success Award (2019)ISIF’21 Silver Medal: Invention titled “Targeted Novel Triazolothiadiazine Derivatives for The Treatment of Lung Cancer” (2021)Right Holder: Anadolu UniversityInventors: Assoc. Prof. Dr. Belgin Sever, Prof. Dr. Mehlika Dilek Altintop, Prof. Dr. Ahmet Ozdemir, Prof. Dr. Gülşen Akalın Çiftçi

Supervised Master Dissertations 🎓

Supervisor: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical ChemistryStudent: Sevtem GökbulutDissertation Title: “Synthesis of new 5-chloro-6-methoxy-2-[4-(substituted)benzylidene]-2,3-dihydro-1H-inden-1-one derivatives and investigation of their biological effects”Date: 13/01/2017

Supervised Doctorate Dissertations 🎓

Supervisor: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical ChemistryStudent: Muhammed KarabacakDissertation Title: “The Synthesis of New Pyrazoline Derivatives and The Investigation of Their Biological Activities”Date: 15/08/2016

Publication📜

Design, Synthesis, and In Vivo Evaluation of a New Series of Indole-Chalcone Hybrids as Analgesic and Anti-Inflammatory Agents

Baramaki, I., Altıntop, M.D., Arslan, R., Hasan, A., Bektaş Türkmen, N.
ACS Omega, 2024, 9(10), pp. 12175–12183

 

Design, Synthesis, and Evaluation of a New Series of 2-Pyrazolines as Potential Antileukemic Agents

Altıntop, M.D., Cantürk, Z., Özdemir, A.
ACS Omega, 2023, 8(45), pp. 42867–42877

 

Design, Synthesis, and Evaluation of a New Series of Hydrazones as Small-Molecule Akt Inhibitors for NSCLC Therapy

Erdönmez, B., Altıntop, M.D., Akalın Çiftçi, G., Özdemir, A., Ece, A.
ACS Omega, 2023, 8(22), pp. 20056–20065

 

A New Series of Hydrazones as Small-Molecule Aldose Reductase Inhibitors

Altıntop, M.D., Demir, Y., Türkeş, C., Beydemir, Ş., Özdemir, A.
Archiv der Pharmazie, 2023, 356(4), 2200570

 

A New Series of Thiazole-Hydrazone Hybrids for Akt-Targeted Therapy of Non-Small Cell Lung Cancer

Orujova, T., Ece, A., Akalın Çiftçi, G., Özdemir, A., Altıntop, M.D.
Drug Development Research, 2023, 84(2), pp. 185–199

 

Discovery of Small Molecule COX-1 and Akt Inhibitors as Anti-NSCLC Agents Endowed with Anti-Inflammatory Action

Altıntop, M.D., Akalın Çiftçi, G., Yılmaz Savaş, N., Alataş, Ö., Özdemir, A.
International Journal of Molecular Sciences, 2023, 24(3), 2648

 

Microwave-Assisted Synthesis of a Series of 4,5-Dihydro-1H-Pyrazoles Endowed with Selective COX-1 Inhibitory Potency

Altıntop, M.D., Temel, H.E., Özdemir, A.
Journal of the Serbian Chemical Society, 2023, 88(4), pp. 355–365