Igor Sitnik | Computer Science | Best Researcher Award

Prof. Igor Sitnik | Computer Science | Best Researcher Award

Leading Researcher from Joint Institute for Nuclear Research, Russia

Igor M. Sitnik is a distinguished physicist known for his pioneering contributions to nuclear and particle physics. With a research career spanning over five decades, he has played a central role in the analysis and interpretation of complex experimental data, particularly in the fields of light nuclei reactions and polarization phenomena. Sitnik has been instrumental in leading experimental collaborations at premier research institutions such as the Joint Institute for Nuclear Research (JINR) in Dubna and Jefferson Lab (JLab) in the United States. His career is marked by scientific rigor, collaborative leadership, and a commitment to advancing knowledge in subatomic physics. Having received multiple first-class JINR awards, he is recognized by his peers for excellence and innovation in experimental physics. His work has not only contributed valuable insights into nuclear structures and reaction mechanisms but also to the development of computational tools that enhance data interpretation in high-energy physics. With several highly cited publications, including one with over 900 citations, Sitnik remains a respected authority in his domain. His contributions continue to influence experimental design, data processing, and the theoretical understanding of fundamental particles, making him a deserving candidate for top honors in scientific achievement.

Professional Profile

Education

Igor M. Sitnik graduated from the Physics Department of Moscow State University in 1964, a renowned institution known for its rigorous training in fundamental and applied sciences. His education at one of the most prestigious universities in Russia provided him with a strong foundation in theoretical and experimental physics. During his formative academic years, he cultivated a deep interest in nuclear and subatomic physics, which would later define the focus of his professional career. His undergraduate studies were rooted in classical mechanics, quantum theory, electrodynamics, and statistical mechanics—courses that equipped him with analytical tools necessary for advanced research. His time at Moscow State University also introduced him to early computational methods and data analysis techniques, which he later expanded upon through decades of research. While no specific postgraduate degrees are mentioned, Sitnik’s career trajectory suggests extensive post-degree specialization and hands-on training in experimental nuclear physics and detector technology. His continuous professional development through participation in international collaborations and technical projects reflects a lifetime commitment to learning and scientific inquiry. The academic rigor and mentorship he received during his education played a significant role in shaping his methodical approach to research and long-term contributions to physics.

Professional Experience

Igor M. Sitnik has had a long and impactful career as a researcher, leader, and innovator in the field of nuclear and particle physics. Since the 1970s, he has been responsible for off-line analysis in his group at the Joint Institute for Nuclear Research (JINR) in Dubna. In the 1970s and 1980s, he led groundbreaking studies on the breakup reactions of light nuclei on various targets, a body of work that earned him the prestigious 1st JINR Prize in 1989. Moving into the 1990s, Sitnik shifted his focus to polarization phenomena, for which he also received the 1st JINR Prize in 1997. During this period, he served as co-spokesman for Proposal LNS 249 at Saturne-2 (JINR), underscoring his leadership role in international experimental collaborations. In the late 1990s, he became the spokesman for the “ALPHA” spectrometer project in Dubna. Most recently, he has been actively involved in studying the proton electric-to-magnetic form factor ratio (Gep/Gmp) at Jefferson Lab in the USA, with portions of this research conducted in Dubna, culminating in the 1st JINR Prize in 2020. His professional journey reflects a consistent dedication to experimental excellence, leadership in high-profile projects, and innovation in nuclear science.

Research Interests

Igor M. Sitnik’s research interests are centered around nuclear and particle physics, with a specific focus on reaction dynamics, polarization effects, and form factor studies. In the early stages of his career, he was deeply involved in investigating the breakup reactions of light nuclei, exploring how nuclear interactions change with varying target materials. This line of inquiry provided insights into nuclear structure and reaction mechanisms. In the subsequent decades, he expanded his interests to include polarization phenomena, examining spin-dependent interactions and their implications in nuclear scattering processes. These studies have practical applications in understanding fundamental nuclear forces and contribute to precision modeling in theoretical physics. More recently, Sitnik has engaged in form factor measurements at Jefferson Lab (JLab), particularly the ratio of electric to magnetic form factors of the proton (Gep/Gmp). This research is essential for understanding the internal structure of protons and has implications for quantum chromodynamics. Additionally, Sitnik has demonstrated a strong interest in data analysis methodologies, developing a minimization program in the 2010s for handling complex, multi-variable datasets. His ability to integrate experimental design with computational analysis defines his holistic and innovative approach to research in modern nuclear physics.

Research Skills

Igor M. Sitnik possesses a robust set of research skills that span experimental design, data analysis, computational modeling, and scientific communication. His early work in nuclear reaction dynamics required meticulous experimental planning, including the selection of beam-target configurations and detector setups. Sitnik’s responsibility for off-line analysis within his group highlights his proficiency in processing and interpreting large volumes of experimental data—skills that are essential in high-energy and nuclear physics research. He has demonstrated expertise in statistical analysis and error minimization, evident from the development of a custom minimization program for multi-set tasks. This computational tool showcases his aptitude for programming and algorithmic optimization, allowing for efficient parameter fitting in complex physical models. In collaborative settings, Sitnik has frequently held leadership roles, which underline his ability to manage interdisciplinary teams and guide long-term research projects. His high citation counts indicate a strong capability in publishing impactful findings and presenting them to the scientific community. Whether through experimental rigour, theoretical insight, or data processing innovation, Sitnik’s research skills reflect a well-rounded and highly competent physicist who has contributed significantly to advancing experimental techniques and analytical methodologies in his field.

Awards and Honors

Over the course of his esteemed career, Igor M. Sitnik has been the recipient of several top-tier scientific honors, most notably the 1st JINR Prize, which he has been awarded three times. The first was in 1989 for his extensive work on the breakup reactions of light nuclei, a cornerstone study in nuclear reaction physics. His second 1st JINR Prize was awarded in 1997 for his pivotal research on polarization phenomena in nuclear interactions. This body of work marked an important advancement in understanding spin-dependent processes. The third award came in 2020, recognizing his significant contributions to the study of the Gep/Gmp ratio—a key metric in probing the internal structure of the proton—conducted in part at Jefferson Lab (JLab) and partially in Dubna. These repeated honors from a leading international research institution testify to the lasting impact and high quality of Sitnik’s research. In addition to formal awards, his publication record includes several high-impact papers, one of which has been cited over 900 times, indicating broad recognition by the global physics community. His accolades place him among the most respected experimental nuclear physicists in the post-Soviet scientific world.

Conclusion

Igor M. Sitnik stands out as an exemplary researcher in the field of nuclear and particle physics. His decades-long contributions span pioneering experimental work, leadership in major international collaborations, and the development of advanced data analysis tools. With a career marked by three prestigious 1st JINR Prizes, he has consistently demonstrated a high level of scientific excellence and innovation. His impactful research on nuclear reactions, polarization phenomena, and proton structure has significantly advanced our understanding of subatomic processes. Sitnik’s ability to bridge theoretical insight with practical implementation through software development for data analysis highlights his multidimensional expertise. His research has not only yielded highly cited publications but has also contributed to shaping experimental protocols and analytical methods in modern physics. Though there are opportunities for enhanced mentorship and broader dissemination of his recent work, Sitnik’s legacy is firmly established. He continues to be a vital figure in the scientific community, with a body of work that exemplifies dedication, intellectual rigor, and collaborative spirit. These achievements make him a worthy and compelling candidate for the Best Researcher Award and solidify his position as a leader in advancing the frontiers of nuclear science.

Publications Top Notes

1. The Final Version of the 5D Histogram Package NORA

  • Author: I.M. Sitnik

  • Journal: Computer Physics Communications

  • Year: 2024

2. Debugging the FUMILIM Minimization Package

  • Authors: I.M. Sitnik, I.I. Alexeev, D.V. Nevsky

  • Journal: Computer Physics Communications

  • Year: 2024

  • Citations: 2

3. 5D Histogram Package NORA

  • Author: I.M. Sitnik

  • Journal: Computer Physics Communications

  • Year: 2023

4. Charge Exchange dp→(pp)n Reaction Study at 1.75 A GeV/c by the STRELA Spectrometer

  • Authors: S.N. Basilev, Y.P. Bushuev, S.A. Dolgiy, I.V. Slepnev, J. Urbán

  • Journal: European Physical Journal A

  • Year: 2021

  • Citations: 2

5. The Final Version of the FUMILIM Minimization Package

  • Authors: I.M. Sitnik, I.I. Alexeev, O.V. Selugin

  • Journal: Computer Physics Communications

  • Year: 2020

  • Citations: 9

6. Results of Measurements of the Analyzing Powers for Polarized Neutrons on C, CH₂ and Cu Targets for Momenta Between 3 and 4.2 GeV/c

  • Authors: I.M. Sitnik, S.N. Basilev, Y.P. Bushuev, J. Urbán, J. Mušinský

  • Type: Conference Paper

7. Measurement of Neutron and Proton Analyzing Powers on C, CH, CH₂ and Cu Targets in the Momentum Region 3–4.2 GeV/c

  • Authors: S.N. Basilev, Y.P. Bushuev, O.P. Gavrìshchuk, J. Urbán, J. Mušinský

  • Journal: European Physical Journal A

  • Year: 2020

  • Citations: 5

8. Technical Supplement to “Polarization Transfer Observables in Elastic Electron-Proton Scattering at Q² = 2.5, 5.2, 6.8 and 8.5 GeV²”

  • Authors: A.J.R. Puckett, E.J. Brash, M.K. Jones, B.B. Wojtsekhowski, S.A. Wood

  • Journal: Nuclear Instruments and Methods in Physics Research Section A

  • Year: 2018

 

 

Saeed Mohsen Abosreea | Artificial Intelligence Engineering | Best Researcher Award

Dr. Saeed Mohsen Abosreea | Artificial Intelligence Engineering | Best Researcher Award

Clinical Associate Professor at Department of Otorhinolaryngology-Head and Neck Surgery Yongin Severance Hospital, Yonsei University College of Medicine, South Korea

Dr. Saeed Mohsen Abosreea Hassan is an Assistant Professor of Electronics and Communications Engineering with a Ph.D. from Ain Shams University, Cairo. He has extensive academic experience, currently serving at King Salman International University. His research focuses on cutting-edge areas like deep learning, IoT, and wearable devices, with applications in healthcare and smart systems. Dr. Saeed has published 24 papers in reputable journals such as IEEE Access and Multimedia Tools and Applications, achieving an h-index of 10. His work spans various interdisciplinary fields, including Industry 4.0, human activity recognition, and energy harvesting systems. In addition to his research, he has supervised numerous student projects and contributed significantly to teaching advanced courses in electronics and AI. His contributions to both academia and industry make him a versatile researcher poised for continued impact in technological innovation and healthcare systems.

Profile

Education

Saeed Mohsen Abosreea Hassan holds a Ph.D. in Electronics and Communications Engineering from Ain Shams University, Cairo, Egypt, completed between 2017 and 2020. His doctoral research focused on the design and implementation of hybrid energy harvesting systems for medical wearable sensor nodes, demonstrating his expertise in cutting-edge healthcare technology. Prior to this, Saeed earned his Master’s degree in Electronics and Communications Engineering from the same institution, where he worked on the development of an electroencephalogram (EEG) system, further advancing his specialization in medical applications of electronics. He completed his undergraduate studies at Thebes Higher Institute of Engineering, Cairo, from 2008 to 2013, graduating with honors, earning an overall grade of “Excellent” and a GPA of 3.6/4.0. His strong educational background has provided him with a solid foundation in both theoretical and practical aspects of electronics, communications, and their applications in healthcare and industry.

Professional Experience

Saeed Mohsen Abosreea Hassan is an accomplished Assistant Professor in Electronics and Communications Engineering, currently serving at King Salman International University since September 2022. Prior to this role, he held a full-time Assistant Professor position at Al-Madinah Higher Institute for Engineering and Technology from April 2021 to August 2022. He also served as a part-time Assistant Professor at Ain Shams University from July 2021 to September 2021, where he contributed to cutting-edge research and advanced teaching methodologies. Before transitioning to academia, Saeed gained extensive experience as a Teaching Assistant at Thebes Academy from September 2013 to March 2021. Throughout his career, he has demonstrated expertise in various fields such as deep learning, IoT systems, and medical wearable sensor technologies. His diverse academic roles, combined with his active involvement in research, student supervision, and curriculum development, highlight his commitment to advancing education and innovation in engineering.

Research Interest

Saeed Mohsen Abosreea Hassan’s research interests focus on cutting-edge technologies in electronics, communications, and artificial intelligence. His work spans deep learning models, machine learning algorithms, and their applications in human activity recognition, smart healthcare systems, and Internet of Things (IoT) technologies. A significant portion of his research is dedicated to the development of energy harvesting systems for wearable medical sensor nodes, which has the potential to revolutionize real-time healthcare monitoring. He is also passionate about the use of neural networks and convolutional neural networks (CNNs) for the detection of brain tumors, Alzheimer’s disease, and other medical conditions through medical imaging techniques. His focus on Industry 4.0 and smart city networks highlights his commitment to advancing technologies that enhance both industrial automation and urban living. Saeed’s research integrates theoretical advancements with practical applications, particularly in healthcare and smart environments.

Research Skills

Saeed Mohsen Abosreea Hassan possesses a diverse and advanced set of research skills that span multiple fields of electronics, communications, and deep learning. He is proficient in AI tools such as TensorFlow, PyTorch, Keras, and Scikit-Learn, which he uses for developing machine learning and deep learning models. His expertise in embedded systems, IoT, and smart healthcare technologies is reflected in his research on wearable sensor nodes and energy harvesting systems. He is skilled in programming languages like Python, MATLAB, and Embedded C, essential for his work in developing algorithms and systems for medical and industrial applications. Additionally, Saeed is experienced in electronic circuit and layout design using tools like Proteus, LT-spice, and NI Multisim. His research extends into data acquisition systems, neural networks, and signal processing, particularly in healthcare applications such as brain tumor detection and human activity recognition, showcasing his multidisciplinary research proficiency.

Award and Recognition

Dr. Saeed Mohsen Abosreea Hassan, an accomplished Assistant Professor in Electronics and Communications Engineering, has made significant strides in the fields of deep learning, IoT, and wearable healthcare technologies. He holds a Ph.D. from Ain Shams University and has published 24 research papers, with an impressive h-index of 10 on Google Scholar. His work has been featured in prestigious journals, including IEEE Access, highlighting his contributions to Industry 4.0, smart healthcare systems, and energy harvesting technologies. Dr. Saeed’s research has been recognized for its practical applications in healthcare, with innovations like self-powered medical wearable sensors. His expertise has also earned him opportunities to present at international conferences and collaborate with top-tier researchers globally. As an emerging leader in his field, Dr. Saeed’s work continues to push the boundaries of technology and healthcare, positioning him as a distinguished researcher dedicated to advancing science and improving lives.

Conclusion

Saeed Mohsen Abosreea Hassan is a well-qualified candidate for the Best Researcher Award. His strong academic foundation, multidisciplinary research, and publication record make him a strong contender. By expanding his international collaborations, focusing on high-impact research, and pursuing more patents or grants, he could significantly increase his research impact and standing in the academic community. His work in healthcare and energy harvesting aligns with global trends, making his contributions both timely and impactful.

Publication Top Notes

  • Title: Human Activity Recognition Using K-Nearest Neighbor Machine Learning Algorithm
    • Authors: S Mohsen, A Elkaseer, SG Scholz
    • Year: 2021
    • Citations: 63
  • Title: Industry 4.0-Oriented Deep Learning Models for Human Activity Recognition
    • Authors: Saeed Mohsen, Ahmed Elkaseer, Steffen G. Scholz
    • Year: 2021
    • Citations: 46
  • Title: A Self-Powered Wearable Wireless Sensor System Powered by a Hybrid Energy Harvester for Healthcare Applications
    • Authors: S Mohsen, A Zekry, K Youssef, M Abouelatta
    • Year: 2021
    • Citations: 41
  • Title: Machine Learning and Deep Learning Techniques for Driver Fatigue and Drowsiness Detection: A Review
    • Authors: S Abd El-Nabi, W El-Shafai, ES M. El-Rabaie, K F. Ramadan, S Mohsen
    • Year: 2023
    • Citations: 25
  • Title: Brain Tumor Classification Using Hybrid Single Image Super-Resolution Technique with ResNext101_32x8d and VGG19 Pre-Trained Models
    • Authors: S Mohsen, AM Ali, ESM El-Rabaie, A Elkaseer, SG Scholz, AMA Hassan
    • Year: 2023
    • Citations: 22
  • Title: Recognition of Human Activity Using GRU Deep Learning Algorithm
    • Authors: S Mohsen
    • Year: 2023
    • Citations: 18
  • Title: An Autonomous Wearable Sensor Node for Long-Term Healthcare Monitoring Powered by a Photovoltaic Energy Harvesting System
    • Authors: S Mohsen, A Zekry, K Youssef, M Abouelatta
    • Year: 2020
    • Citations: 15
  • Title: On Architecture of Self-Sustainable Wearable Sensor Node for IoT Healthcare Applications
    • Authors: S Mohsen, A Zekry, K Youssef, M Abouelatta
    • Year: 2021
    • Citations: 13
  • Title: EEG-Based Human Emotion Prediction Using an LSTM Model
    • Authors: S Mohsen, AG Alharbi
    • Year: 2021
    • Citations: 12
  • Title: A Self-Powered Wearable Sensor Node for IoT Healthcare Applications
    • Authors: S Mohsen, A Zekry, M Abouelatta, K Youssef
    • Year: 2020
    • Citations: 12